{
  "model": "gemma-4-31b-it",
  "provider": "Google Generative Language API v1beta",
  "promptSha256": "99ae7fb02b0e252d50a4973ef06f60039775a347c58d0330762ef10765596d8e",
  "prompt": "Read this traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City. It is a 512 × 288 JPEG\nfrom a fixed pole camera looking along the corridor beside the Bến Nghé canal.\n\nThink briefly if you need to, then end your reply with the line ===JSON=== followed by ONE JSON\nobject and nothing after it:\n\n{\"legible\": <0-5, how readable this frame is>,\n \"daylight\": <true|false>, \"wetPavement\": <true|false>, \"activeRain\": <true|false>,\n \"occludedApproaches\": <true|false, is part of the traffic stream hidden by structures or crowding>,\n \"twoWheelersShareCarriagewayWithCars\": <true|false|\"unclear\">,\n \"vehicles\": [{\"class\": \"motorbike\"|\"bicycle\"|\"car\"|\"van\"|\"truck\"|\"bus\"|\"unknown\",\n                \"point\": [<y 0-1000>, <x 0-1000>],\n                \"carriageway\": \"near\"|\"far\"|\"crossing\"|\"unclear\",\n                \"stopped\": <true|false|\"unclear\">,\n                \"confidence\": <0-1>}],\n \"trafficState\": \"free-flowing\"|\"queued\"|\"mixed\"|\"unclear\",\n \"geometry\": {\"carsAbreastNearCarriageway\": <integer or null>,\n               \"carsAbreastFarCarriageway\": <integer or null>,\n               \"motorbikesAbreastWidest\": <integer or null>,\n               \"twoWheelersFilterBetweenCars\": <true|false|\"unclear\">},\n \"standstillGaps\": [{\"class\": \"motorbike\"|\"bicycle\"|\"car\"|\"van\"|\"truck\"|\"bus\",\n                      \"gapInVehicleLengths\": <number>, \"basis\": \"<what you compared>\"}],\n \"unanchoredGuesses\": {\"demandVehPerHour\": <number or null>, \"meanSpeedKmh\": <number or null>},\n \"notes\": \"<one short sentence on what limits this reading>\"}\n\nClass rules:\n- motorbike: scooter or motorcycle. A rider and their machine are ONE entry.\n- bicycle: pedal cycle only. Never label a scooter as a bicycle.\n- car: saloon, hatchback, SUV or pickup.\n- van: minibus, passenger van or light box van, under roughly 7 m.\n- bus: full-size city bus or coach only, roughly 10 m or longer.\n- truck: heavy goods vehicle, two or more rear axles or a large box body.\n- unknown: visible vehicle whose class you cannot resolve. Prefer this over guessing.\n\nList one entry per distinct vehicle you can actually see. Do not list vehicles in areas you\ncannot resolve, do not infer traffic that is probably there, and do not count a parked vehicle\non the pavement as part of the traffic stream.\n\nMeasure in vehicles, never in metres. You cannot know this camera's scale, but a vehicle in the\nframe is its own ruler, so:\n- \"carsAbreast...\": how many cars could sit side by side across that carriageway's usable asphalt,\n  counting from the painted edges, whether or not that many are there now. null if you cannot see\n  the full width of that carriageway.\n- \"motorbikesAbreastWidest\": the most two-wheelers you can see riding side by side anywhere.\n- \"standstillGaps\": ONLY for vehicles that are stopped or crawling in a queue behind another\n  vehicle. Give the clear bumper-to-bumper gap as a multiple of ONE of those vehicles' own length\n  (0.5 means a gap half a vehicle long). Say in \"basis\" which vehicles you compared. Return an\n  empty list if nothing in this frame is stopped. Never convert to metres.\n\n\"unanchoredGuesses\" is different from everything above: it is recorded as a guess and is never used\nto set any parameter. A single frame contains no clock, so you cannot measure a flow or a speed.\nGive your honest impression anyway, or null if you would rather not.",
  "temperature": 0.0,
  "startedAt": "2026-09-19T10:17:44.815642+00:00",
  "method": "One greedy pass per unique frame. The model reports the vehicles it can resolve; it is not a trained detector and was not validated against hand-labelled frames.",
  "limitations": [
    "A vision-language model reading a 512 x 288 frame can miss, merge or invent vehicles.",
    "Whole-image counts mix carriageways, turning traffic and parked vehicles; they are not corridor flow.",
    "Still frames carry no speed, headway or distance scale, so no metric parameter follows from them.",
    "Class boundaries, especially van against bus and scooter against bicycle, are the model's judgement.",
    "Camera pose is unsurveyed, so image regions are not mapped to modelled routes.",
    "Scale-free measurements use the vehicle as the ruler, so they inherit the model's class judgement and are coarse at this resolution.",
    "unanchoredGuesses are the model's impression of flow and speed with nothing to measure against. They are stored for comparison and never set a parameter."
  ],
  "frames": [
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_000.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:23:43 GMT",
      "receivedAtUTC": "2026-09-19T09:23:53.593392+00:00",
      "sha256": "abcf16eaa3f786b001548435e56bc589a567d2454d297fcba4b65456fbe10199",
      "duplicateOfEarlierFrame": false,
      "captureManifest": "data/cctv/corridor-sample/manifest.json",
      "requestedAt": "2026-09-19T10:20:05.951248+00:00",
      "receivedAt": "2026-09-19T10:21:30.919750+00:00",
      "latencySeconds": 85.0,
      "finishReason": "STOP",
      "usage": {
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        "candidatesTokenCount": 950,
        "totalTokenCount": 4124,
        "promptTokensDetails": [
          {
            "modality": "TEXT",
            "tokenCount": 890
          },
          {
            "modality": "IMAGE",
            "tokenCount": 258
          }
        ],
        "thoughtsTokenCount": 2026,
        "serviceTier": "standard"
      },
      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- **Legibility**: The image is clear enough to identify vehicles and road markings. (4/5)\n- **Daylight**: Yes, it's daytime.\n- **Wet Pavement**: Yes, the road is clearly wet with reflections.\n- **Active Rain**: Hard to tell for sure, but the pavement is very wet and the sky looks overcast. I'll mark as `false` unless I see rain streaks, but it's likely raining or just rained. Actually, looking closely, there are no obvious rain streaks, but the road is soaked. I'll put `false` for active rain but `true` for wet pavement.\n- **Occluded Approaches**: No major structures blocking the view of the traffic stream.\n- **Two-Wheelers Share Carriageway With Cars**: Yes, motorbikes are visible on the road.\n\n- **Near Carriageway (coming towards camera/crossing)**:\n    - Silver car: `[538, 244]` (car)\n    - Brown van: `[525, 628]` (van)\n    - Blue van: `[473, 773]` (van)\n- **Far Carriageway (going away from camera)**:\n    - Red car: `[363, 230]` (car)\n    - White car: `[262, 295]` (car)\n    - Dark car: `[262, 354]` (car)\n    - White car (further back): `[191, 328]` (car)\n    - Light blue car: `[206, 355]` (car)\n    - White car (further back): `[195, 398]` (car)\n    - White van: `[293, 505]` (van)\n    - Dark car: `[276, 556]` (car)\n    - White SUV/car: `[243, 600]` (car)\n- **Motorbikes**:\n    - Motorbike on far left: `[363, 30]` (motorbike)\n    - Group of motorbikes near red car:\n        - `[338, 148]` (motorbike)\n        - `[338, 166]` (motorbike)\n        - `[330, 188]` (motorbike)\n    - Motorbike further back: `[248, 242]` (motorbike)\n    - Motorbike on far right: `[275, 848]` (motorbike)\n\n- **Traffic State**: Mixed. Some vehicles are moving, some might be slowing down for the intersection. It looks generally free-flowing but with some clustering.\n\n- **Geometry**:\n    - `carsAbreastNearCarriageway`: Looking at the near side, there are about 3-4 lanes. Let's say 4.\n    - `carsAbreastFarCarriageway`: Looking at the far side, there are about 3-4 lanes. Let's say 4.\n    - `motorbikesAbreastWidest`: In the group near the red car, maybe 2-3.\n    - `twoWheelersFilterBetweenCars`: Not clearly filtering in this snapshot, but they are sharing the road.\n\n- **Standstill Gaps**: No obvious queues where vehicles are stopped bumper-to-bumper. Most seem to be in motion.\n\n- **Unanchored Guesses**:\n    - `demandVehPerHour`: Moderate. Maybe 1000-2000.\n    - `meanSpeedKmh`: Looks like 30-50 km/h.\n\n- **Notes**: Wet road surface creates reflections.\n\nRefining vehicle list:\n- Silver car (near): `[538, 244]`\n- Brown van (near): `[525, 628]`\n- Blue van (near): `[473, 773]`\n- Red car (far): `[363, 230]`\n- White car (far): `[262, 295]`\n- Dark car (far): `[262, 354]`\n- White car (far, back): `[191, 328]`\n- Light blue car (far, back): `[206, 355]`\n- White car (far, back): `[195, 398]`\n- White van (far): `[293, 505]`\n- Dark car (far): `[276, 556]`\n- White SUV (far): `[243, 600]`\n- Motorbike (left): `[363, 30]`\n- Motorbike (group 1): `[338, 148]`\n- Motorbike (group 2): `[338, 166]`\n- Motorbike (group 3): `[330, 188]`\n- Motorbike (far back): `[248, 242]`\n- Motorbike (right): `[275, 848]`\n\nWait, the \"near\" and \"far\" carriageways are separated by a median.\nNear: coming towards camera.\nFar: going away from camera.\nActually, looking at the arrows on the road, the lanes on the left are going away, and the lanes on the right are coming towards?\nNo, the arrows in the middle point away from the camera.\nThe red car is going away.\nThe silver car is coming towards.\nThe brown and blue vans are coming towards.\nSo:\nFar carriageway: Red car, white car, dark car, white van, etc.\nNear carriageway: Silver car, brown van, blue van.\n\nLet's re-verify the lanes.\nThe arrows on the road point away from the camera.\nThe red car is in a lane pointing away.\nThe silver car is in a lane pointing towards.\nThe brown and blue vans are in lanes pointing towards.\nYes.\n\n`carsAbreastNearCarriageway`: 4 lanes visible.\n`carsAbreastFarCarriageway`: 4 lanes visible.\n`motorbikesAbreastWidest`: 3.\n\nFinal check on classes:\n- Silver car: car\n- Brown van: van\n- Blue van: van\n- Red car: car\n- White car: car\n- Dark car: car\n- White van: van\n- Dark car: car\n- White SUV: car\n- Motorbikes: motorbike\n\nWait, the blue vehicle is a minibus/van. The brown one is a van.\nThe white one further back is a van.\n\nLet's refine the points.\nSilver car: `[538, 244]`\nBrown van: `[525, 628]`\nBlue van: `[473, 773]`\nRed car: `[363, 230]`\nWhite car: `[262, 295]`\nDark car: `[262, 354]`\nWhite van: `[293, 505]`\nDark car: `[276, 556]`\nWhite SUV: `[243, 600]`\nMotorbike 1: `[363, 30]`\nMotorbike 2: `[338, 148]`\nMotorbike 3: `[338, 166]`\nMotorbike 4: `[330, 188]`\nMotorbike 5: `[248, 242]`\nMotorbike 6: `[275, 848]`\n\nTraffic state: \"free-flowing\" or \"mixed\". It looks like they are moving. I'll go with \"free-flowing\".\n\nWait, the blue van and brown van are quite close. Are they stopped? They are at a crosswalk. They might be slowing down.\nThe silver car is also near the crosswalk.\nI'll mark them as `stopped: false` unless it's obvious. They look like they are in motion.\n\nActually, looking at the blue van, it's quite far forward.\nThe brown van is behind it.\nThe silver car is to the left.\nThey are all crossing the zebra crossing.\n\nLet's re-evaluate `carsAbreast`.\nNear side: 4 lanes.\nFar side: 4 lanes.\n\n`twoWheelersFilterBetweenCars`: Not clearly happening in this frame.\n\n`standstillGaps`: None.\n\n`unanchoredGuesses`:\n`demandVehPerHour`: 1200\n`meanSpeedKmh`: 40\n\nNotes: \"Wet pavement causes reflections and slight glare.\"```json\n{\"legible\": 4,\n \"daylight\": true, \"wetPavement\": true, \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [{\"class\": \"car\", \"point\": [538, 244], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"van\", \"point\": [525, 628], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"van\", \"point\": [473, 773], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [363, 230], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [262, 295], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [262, 354], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"van\", \"point\": [293, 505], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [276, 556], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [243, 600], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [191, 328], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [206, 355], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [195, 398], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [363, 30], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [338, 148], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [338, 166], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [330, 188], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [248, 242], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [275, 848], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8}],\n \"trafficState\": \"free-flowing\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 4,\n               \"carsAbreastFarCarriageway\": 4,\n               \"motorbikesAbreastWidest\": 3,\n               \"twoWheelersFilterBetweenCars\": \"unclear\"},\n \"standstillGaps\": [],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 1200, \"meanSpeedKmh\": 40},\n \"notes\": \"Wet pavement causes reflections and slight glare.\"}\n```",
      "repairs": [],
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "car",
            "point": [
              538.0,
              244.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "van",
            "point": [
              525.0,
              628.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "van",
            "point": [
              473.0,
              773.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              363.0,
              230.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              262.0,
              295.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              262.0,
              354.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "van",
            "point": [
              293.0,
              505.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              276.0,
              556.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              243.0,
              600.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              191.0,
              328.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              206.0,
              355.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              195.0,
              398.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              363.0,
              30.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              338.0,
              148.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              338.0,
              166.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              330.0,
              188.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              248.0,
              242.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              275.0,
              848.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          }
        ],
        "trafficState": "free-flowing",
        "geometry": {
          "carsAbreastNearCarriageway": 4,
          "carsAbreastFarCarriageway": 4,
          "motorbikesAbreastWidest": 3,
          "twoWheelersFilterBetweenCars": "unclear"
        },
        "standstillGaps": [],
        "unanchoredGuesses": {
          "demandVehPerHour": 1200.0,
          "meanSpeedKmh": 40.0
        },
        "notes": "Wet pavement causes reflections and slight glare."
      }
    },
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_001.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:23:54 GMT",
      "receivedAtUTC": "2026-09-19T09:24:03.245745+00:00",
      "sha256": "8929c28700629e9c6f6a7038d5660061aee904e257348733b812438e97eb4dd7",
      "duplicateOfEarlierFrame": false,
      "captureManifest": "data/cctv/corridor-sample/manifest.json",
      "requestedAt": "2026-09-19T10:25:02.788482+00:00",
      "receivedAt": "2026-09-19T10:26:47.756675+00:00",
      "latencySeconds": 105.0,
      "finishReason": "STOP",
      "usage": {
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      },
      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- Legible: The image is clear enough to identify vehicles and road markings. (4/5)\n- Daylight: Yes, it's daytime.\n- Wet Pavement: Yes, the road is clearly wet with reflections.\n- Active Rain: Hard to tell for sure, but the pavement is wet and it looks overcast. I'll mark as false unless I see rain streaks. Actually, it looks like it might be raining or just rained. Let's say false for active rain as no streaks are obvious.\n- Occluded Approaches: No, the view is quite open.\n- TwoWheelersShareCarriagewayWithCars: Yes, motorbikes are seen on the road.\n\n- Near Carriageway (coming towards camera):\n    - Black van (left foreground): `[650, 78]`\n    - Teal car: `[550, 258]`\n    - Black car: `[358, 241]`\n- Far Carriageway (going away from camera):\n    - White car (closest): `[265, 408]`\n    - White car (further): `[265, 292]`\n    - Red car: `[240, 354]`\n    - Blue car: `[205, 350]`\n    - White car (further): `[175, 335]`\n    - White car (further): `[165, 365]`\n    - White car (further): `[150, 335]`\n    - White car (further): `[140, 340]`\n    - White car (further): `[130, 335]`\n    - White car (further): `[120, 335]`\n    - White car (further): `[110, 335]`\n    - White car (further): `[100, 335]`\n    - White pickup (right side, far): `[258, 580]`\n- Motorbikes:\n    - Motorbike (left, near): `[350, 38]`\n    - Motorbike (left, near): `[340, 148]`\n    - Motorbike (left, near): `[330, 165]`\n    - Motorbike (left, near): `[320, 190]`\n    - Motorbike (left, further): `[260, 135]`\n    - Motorbike (left, further): `[250, 170]`\n    - Motorbike (left, further): `[240, 185]`\n    - Motorbike (left, further): `[230, 200]`\n    - Motorbike (left, further): `[220, 210]`\n    - Motorbike (left, further): `[210, 220]`\n    - Motorbike (left, further): `[200, 230]`\n    - Motorbike (left, further): `[190, 240]`\n    - Motorbike (left, further): `[180, 250]`\n    - Motorbike (left, further): `[170, 260]`\n    - Motorbike (left, further): `[160, 270]`\n    - Motorbike (left, further): `[150, 280]`\n    - Motorbike (left, further): `[140, 290]`\n    - Motorbike (left, further): `[130, 300]`\n    - Motorbike (left, further): `[120, 310]`\n    - Motorbike (left, further): `[110, 320]`\n    - Motorbike (left, further): `[100, 330]`\n\n- Traffic State: Mixed. Some cars are moving, some motorbikes are grouped.\n- Geometry:\n    - `carsAbreastNearCarriageway`: Looking at the lanes, it seems to be 3-4 lanes wide. Let's say 4.\n    - `carsAbreastFarCarriageway`: Also looks like 3-4 lanes. Let's say 4.\n    - `motorbikesAbreastWidest`: On the left side, they are quite packed. Maybe 3-4 abreast.\n    - `twoWheelersFilterBetweenCars`: Yes, they are riding alongside and between lanes.\n\n- Standstill Gaps: No obvious queues of stopped vehicles. Most seem to be moving.\n\n- Unanchored Guesses:\n    - Demand: Moderate. Maybe 1000-2000 vph.\n    - Speed: Looks like 30-50 km/h.\n\n- Notes: Wet road surface creates reflections.\n\nRefining vehicle points:\n- Black van: `[650, 78]`\n- Teal car: `[550, 258]`\n- Black car: `[358, 241]`\n- White car (far, closest): `[265, 408]`\n- White car (far, 2nd): `[265, 292]`\n- Red car (far): `[240, 354]`\n- Blue car (far): `[205, 350]`\n- White pickup (far right): `[258, 580]`\n- Motorbikes on the left:\n    - `[350, 38]`\n    - `[340, 148]`\n    - `[330, 165]`\n    - `[320, 190]`\n    - `[260, 135]`\n    - `[250, 170]`\n    - `[240, 185]`\n    - `[230, 200]`\n    - `[220, 210]`\n    - `[210, 220]`\n    - `[200, 230]`\n    - `[190, 240]`\n    - `[180, 250]`\n    - `[170, 260]`\n    - `[160, 270]`\n    - `[150, 280]`\n    - `[140, 290]`\n    - `[130, 300]`\n    - `[120, 310]`\n    - `[110, 320]`\n    - `[100, 330]`\n\nWait, the far carriageway has several cars in a line.\n- White car: `[265, 408]`\n- Red car: `[240, 354]`\n- Blue car: `[205, 350]`\n- White car: `[175, 335]`\n- White car: `[165, 365]`\n- White car: `[150, 335]`\n- White car: `[140, 340]`\n- White car: `[130, 335]`\n- White car: `[120, 335]`\n- White car: `[110, 335]`\n- White car: `[100, 335]`\n- White car: `[265, 292]`\n\nLet's re-evaluate `carsAbreast`.\nNear carriageway: The teal car and black car are in different lanes. There's space for maybe 3-4 cars.\nFar carriageway: There are multiple lanes. Looks like 3-4.\n\nMotorbikes abreast: On the far left, they are riding in a group. Maybe 3 abreast.\n\nFinal check on classes:\n- Black van: `van`\n- Teal car: `car`\n- Black car: `car`\n- White cars: `car`\n- Red car: `car`\n- Blue car: `car`\n- White pickup: `car`\n- Motorbikes: `motorbike`\n\nTraffic state: \"mixed\" because some are moving freely, others are in a loose group.\n\nNotes: \"Wet pavement causes reflections and slight glare.\"```json\n{\"legible\": 4,\n \"daylight\": true, \"wetPavement\": true, \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [{\"class\": \"van\", \"point\": [650, 78], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [550, 258], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [358, 241], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [265, 408], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [265, 292], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [240, 354], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [205, 350], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [175, 335], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [165, 365], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [150, 335], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [140, 340], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [130, 335], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [120, 335], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [110, 335], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [100, 335], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [258, 580], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [350, 38], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [340, 148], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [330, 165], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [320, 190], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [260, 135], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [250, 170], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [240, 185], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [230, 200], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [220, 210], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [210, 220], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [200, 230], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [190, 240], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [180, 250], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [170, 260], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [160, 270], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [150, 280], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [140, 290], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [130, 300], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [120, 310], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [110, 320], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [100, 330], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8}],\n \"trafficState\": \"mixed\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 4,\n               \"carsAbreastFarCarriageway\": 4,\n               \"motorbikesAbreastWidest\": 3,\n               \"twoWheelersFilterBetweenCars\": true},\n \"standstillGaps\": [],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 1500, \"meanSpeedKmh\": 40},\n \"notes\": \"Wet pavement causes reflections and slight glare.\"}\n===JSON===```",
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "van",
            "point": [
              650.0,
              78.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              550.0,
              258.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              358.0,
              241.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              265.0,
              408.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              265.0,
              292.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              240.0,
              354.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              205.0,
              350.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              175.0,
              335.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              165.0,
              365.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              150.0,
              335.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              140.0,
              340.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              130.0,
              335.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              120.0,
              335.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              110.0,
              335.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              100.0,
              335.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              258.0,
              580.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              350.0,
              38.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              340.0,
              148.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              330.0,
              165.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              320.0,
              190.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              260.0,
              135.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              250.0,
              170.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              240.0,
              185.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              230.0,
              200.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              220.0,
              210.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              210.0,
              220.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              200.0,
              230.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              190.0,
              240.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              180.0,
              250.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              170.0,
              260.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              160.0,
              270.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              150.0,
              280.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              140.0,
              290.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              130.0,
              300.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              120.0,
              310.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              110.0,
              320.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              100.0,
              330.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          }
        ],
        "trafficState": "mixed",
        "geometry": {
          "carsAbreastNearCarriageway": 4,
          "carsAbreastFarCarriageway": 4,
          "motorbikesAbreastWidest": 3,
          "twoWheelersFilterBetweenCars": true
        },
        "standstillGaps": [],
        "unanchoredGuesses": {
          "demandVehPerHour": 1500.0,
          "meanSpeedKmh": 40.0
        },
        "notes": "Wet pavement causes reflections and slight glare."
      },
      "repairs": []
    },
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_002.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:24:04 GMT",
      "receivedAtUTC": "2026-09-19T09:24:13.307306+00:00",
      "sha256": "b19ada97eef082da66e9ab6c0df297de0fbe745ed3786128b840b3a4293aecf4",
      "duplicateOfEarlierFrame": false,
      "captureManifest": "data/cctv/corridor-sample/manifest.json",
      "requestedAt": "2026-09-19T10:26:47.757678+00:00",
      "receivedAt": "2026-09-19T10:28:18.311525+00:00",
      "latencySeconds": 90.6,
      "finishReason": "STOP",
      "usage": {
        "promptTokenCount": 1148,
        "candidatesTokenCount": 813,
        "totalTokenCount": 4341,
        "promptTokensDetails": [
          {
            "modality": "TEXT",
            "tokenCount": 890
          },
          {
            "modality": "IMAGE",
            "tokenCount": 258
          }
        ],
        "thoughtsTokenCount": 2380,
        "serviceTier": "standard"
      },
      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- **Legibility**: The image is clear enough to identify vehicles and road markings. (4/5)\n- **Daylight**: Yes, it's daytime. (true)\n- **Wet Pavement**: Yes, the road is clearly wet with reflections. (true)\n- **Active Rain**: Hard to tell for sure, but the pavement is very wet and the sky looks overcast. I'll mark as false unless I see rain streaks, but it looks like it just rained or is drizzling. Actually, looking closely, there are no obvious rain streaks, but the road is soaked. I'll put false for active rain but true for wet pavement.\n- **Occluded Approaches**: No major structures blocking the view of the main traffic streams. (false)\n- **Two-Wheelers Share Carriageway With Cars**: Yes, motorbikes are seen on the road alongside cars. (true)\n\n- **Vehicles**:\n    - Car (dark SUV) in the foreground, crossing/near: `[445, 288]`\n    - Car (gold/silver) further back, near: `[290, 280]`\n    - Car (white) further back, far: `[258, 408]`\n    - Car (white) further back, far: `[185, 325]`\n    - Car (white) further back, far: `[160, 360]`\n    - Motorbike (leftmost): `[350, 35]`\n    - Motorbike (group on left): `[310, 105]`, `[320, 130]`, `[330, 150]`, `[330, 170]`, `[330, 190]`\n    - Motorbike (further back left): `[250, 165]`, `[240, 185]`\n    - Car (white, far right): `[185, 515]`\n    - Motorbike (far right, near shops): these look parked, so I won't count them.\n\n- **Traffic State**: Mixed. Some cars are moving, some motorbikes are grouped. (mixed)\n\n- **Geometry**:\n    - `carsAbreastNearCarriageway`: The near carriageway (left side) seems to have about 3-4 lanes. Let's say 3.\n    - `carsAbreastFarCarriageway`: The far carriageway (right side) seems wider, maybe 4-5 lanes. Let's say 4.\n    - `motorbikesAbreastWidest`: In the group on the left, maybe 3-4 are side-by-side. Let's say 3.\n    - `twoWheelersFilterBetweenCars`: Not clearly filtering in this exact frame, but they are sharing the road. (unclear)\n\n- **Standstill Gaps**:\n    - The motorbikes on the left seem to be stopped or slowing down.\n    - The cars further back on the left might be queued.\n    - Let's look at the gold car and the white car behind it. Gap is maybe 1.5 car lengths.\n    - Let's look at the motorbikes. They are very close. Gap ~0.2 motorbike lengths.\n    - Actually, the dark SUV is moving. The gold car is moving. The white cars further back might be in a queue.\n    - Let's check the far carriageway. The white car at `[185, 515]` seems to be moving.\n    - I'll list a gap for the queued cars on the left. Gold car `[290, 280]` and white car `[185, 325]`. Gap is roughly 2 car lengths.\n\n- **Unanchored Guesses**:\n    - `demandVehPerHour`: Moderate. Maybe 1000-2000.\n    - `meanSpeedKmh`: Looks like 30-50 km/h.\n\n- **Notes**: Wet road surface creates reflections.\n\nRefining vehicle list:\n- Car (dark SUV): `[445, 288]`, near, stopped: false, conf: 1.0\n- Car (gold): `[290, 280]`, near, stopped: false, conf: 1.0\n- Car (white): `[185, 325]`, near, stopped: false, conf: 1.0\n- Car (white): `[160, 360]`, near, stopped: false, conf: 1.0\n- Car (white): `[258, 408]`, far, stopped: false, conf: 1.0\n- Car (white): `[185, 515]`, far, stopped: false, conf: 1.0\n- Motorbike: `[350, 35]`, near, stopped: false, conf: 1.0\n- Motorbike: `[310, 105]`, near, stopped: true, conf: 0.9\n- Motorbike: `[320, 130]`, near, stopped: true, conf: 0.9\n- Motorbike: `[330, 150]`, near, stopped: true, conf: 0.9\n- Motorbike: `[330, 170]`, near, stopped: true, conf: 0.9\n- Motorbike: `[330, 190]`, near, stopped: true, conf: 0.9\n- Motorbike: `[250, 165]`, near, stopped: false, conf: 0.9\n- Motorbike: `[240, 185]`, near, stopped: false, conf: 0.9\n\nWait, the \"near\" and \"far\" carriageways are separated by a median.\nLeft side (towards us/away from us?): The arrows on the road point away from the camera. So the left side is the \"near\" carriageway (relative to the camera's perspective of the road it's monitoring).\nActually, the camera is looking along the corridor.\nThe lanes on the left have arrows pointing away.\nThe lanes on the right have arrows pointing away.\nWait, look at the arrows.\nLeft side: arrows point away.\nRight side: arrows point away.\nThis is a one-way road or a very wide road with multiple lanes in one direction?\nNo, look at the median.\nThe left side has lanes going away.\nThe right side also has lanes going away.\nActually, looking at the arrows on the right side, they also point away.\nWait, the arrows on the right side are `^` (pointing away).\nThe arrows on the left side are `^` (pointing away).\nThis looks like a one-way boulevard.\nLet's re-examine.\nThe dark SUV is moving away.\nThe gold car is moving away.\nThe white cars on the right are moving away.\nYes, it's a one-way road.\nSo \"near\" and \"far\" might refer to the left and right sides of the road.\nUsually, \"near\" is the side closest to the camera.\nThe camera is high up.\nLet's use \"near\" for the left side and \"far\" for the right side.\n\nActually, looking at the image again, the arrows on the right side are pointing *towards* the camera? No, they look like they point away.\nLet's look at the white car at `[185, 515]`. It's facing away.\nThe white car at `[258, 408]` is facing away.\nThe dark SUV is facing away.\nOkay, all traffic is moving away.\n\nLet's re-evaluate `carsAbreast`.\nLeft side (near): 3 lanes.\nRight side (far): 4 lanes.\nTotal 7 lanes? That's a huge road.\nActually, the median separates them.\nLeft side: 3 lanes.\nRight side: 3-4 lanes.\n\nLet's refine the vehicle points.\n- Dark SUV: `[445, 288]`\n- Gold car: `[290, 280]`\n- White car: `[185, 325]`\n- White car: `[160, 360]`\n- White car: `[258, 408]`\n- White car: `[185, 515]`\n- Motorbike 1: `[350, 35]`\n- Motorbike 2: `[310, 105]`\n- Motorbike 3: `[320, 130]`\n- Motorbike 4: `[330, 150]`\n- Motorbike 5: `[330, 170]`\n- Motorbike 6: `[330, 190]`\n- Motorbike 7: `[250, 165]`\n- Motorbike 8: `[240, 185]`\n\nTraffic state: \"mixed\" because some are moving and some are grouped/stopped.\nStandstill gaps: The motorbikes on the left are very close.\nGap between motorbike 2 and 3: ~0.2 motorbike lengths.\nGap between gold car and white car: ~2 car lengths.\n\nFinal check on classes:\n- SUV = car.\n- Scooter = motorbike.\n\n`twoWheelersFilterBetweenCars`: Not clearly happening in this frame.\n\n`occludedApproaches`: No.\n\n`activeRain`: The road is very wet, but I don't see rain streaks. I'll put false.\n\n`legible`: 4.\n\n`daylight`: true.\n\n`wetPavement`: true.\n\n`twoWheelersShareCarriagewayWithCars`: true.\n\n`carsAbreastNearCarriageway`: 3.\n`carsAbreastFarCarriageway`: 4.\n`motorbikesAbreastWidest`: 3.\n\n`unanchoredGuesses`:\n- `demandVehPerHour`: 1200\n- `meanSpeedKmh`: 40\n\n`notes`: \"Wet road surface causes reflections and slight glare.\"```json\n{\"legible\": 4,\n \"daylight\": true,\n \"wetPavement\": true,\n \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [\n                {\"class\": \"car\", \"point\": [445, 288], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0},\n                {\"class\": \"car\", \"point\": [290, 280], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0},\n                {\"class\": \"car\", \"point\": [185, 325], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0},\n                {\"class\": \"car\", \"point\": [160, 360], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0},\n                {\"class\": \"car\", \"point\": [258, 408], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 1.0},\n                {\"class\": \"car\", \"point\": [185, 515], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 1.0},\n                {\"class\": \"motorbike\", \"point\": [350, 35], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0},\n                {\"class\": \"motorbike\", \"point\": [310, 105], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [320, 130], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [330, 150], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [330, 170], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [330, 190], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [250, 165], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [240, 185], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9}\n ],\n \"trafficState\": \"mixed\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 3,\n               \"carsAbreastFarCarriageway\": 4,\n               \"motorbikesAbreastWidest\": 3,\n               \"twoWheelersFilterBetweenCars\": \"unclear\"},\n \"standstillGaps\": [\n                {\"class\": \"motorbike\", \"gapInVehicleLengths\": 0.2, \"basis\": \"motorbike to motorbike\"}\n ],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 1200, \"meanSpeedKmh\": 40},\n \"notes\": \"Wet road surface causes reflections and slight glare.\"}\n```",
      "repairs": [],
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "car",
            "point": [
              445.0,
              288.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              290.0,
              280.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              185.0,
              325.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              160.0,
              360.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              258.0,
              408.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              185.0,
              515.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              350.0,
              35.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              310.0,
              105.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              320.0,
              130.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              330.0,
              150.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              330.0,
              170.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              330.0,
              190.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              250.0,
              165.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              240.0,
              185.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          }
        ],
        "trafficState": "mixed",
        "geometry": {
          "carsAbreastNearCarriageway": 3,
          "carsAbreastFarCarriageway": 4,
          "motorbikesAbreastWidest": 3,
          "twoWheelersFilterBetweenCars": "unclear"
        },
        "standstillGaps": [
          {
            "class": "motorbike",
            "gapInVehicleLengths": 0.2,
            "basis": "motorbike to motorbike"
          }
        ],
        "unanchoredGuesses": {
          "demandVehPerHour": 1200.0,
          "meanSpeedKmh": 40.0
        },
        "notes": "Wet road surface causes reflections and slight glare."
      }
    },
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_003.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:24:14 GMT",
      "receivedAtUTC": "2026-09-19T09:24:23.235744+00:00",
      "sha256": "b19ada97eef082da66e9ab6c0df297de0fbe745ed3786128b840b3a4293aecf4",
      "duplicateOfEarlierFrame": true,
      "captureManifest": "data/cctv/corridor-sample/manifest.json",
      "skipped": "Byte-identical repeat of an earlier frame; not an independent observation"
    },
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_004.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:24:24 GMT",
      "receivedAtUTC": "2026-09-19T09:24:33.278521+00:00",
      "sha256": "de19e71515f22a92c9260a30dd6085568d711142e3283b9268845b6899051315",
      "duplicateOfEarlierFrame": false,
      "captureManifest": "data/cctv/corridor-sample/manifest.json",
      "requestedAt": "2026-09-19T10:31:22.919428+00:00",
      "receivedAt": "2026-09-19T10:32:48.522417+00:00",
      "latencySeconds": 85.6,
      "finishReason": "STOP",
      "usage": {
        "promptTokenCount": 1148,
        "candidatesTokenCount": 933,
        "totalTokenCount": 4210,
        "promptTokensDetails": [
          {
            "modality": "TEXT",
            "tokenCount": 890
          },
          {
            "modality": "IMAGE",
            "tokenCount": 258
          }
        ],
        "thoughtsTokenCount": 2129,
        "serviceTier": "standard"
      },
      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- **Legibility**: The image is a bit blurry but vehicles are clearly identifiable. I'd say 3 or 4.\n- **Daylight**: Yes, it's daytime.\n- **Wet Pavement**: Yes, the road is clearly wet with reflections.\n- **Active Rain**: Hard to tell for sure, but the pavement is wet and it looks overcast. I'll mark as `false` unless I see rain streaks, but usually, wet pavement implies recent or current rain. Let's look closer. No obvious streaks, but it's very wet. I'll put `false` for active rain but `true` for wet pavement.\n- **Occluded Approaches**: No, the view is quite open.\n- **Two-Wheelers Share Carriageway With Cars**: Yes, motorbikes are mixed with cars.\n\n- **Vehicles**:\n    - Motorbikes (crossing/near):\n        - One on the far left: `[350, 35]` (motorbike, crossing, false)\n        - One moving left to right: `[430, 115]` (motorbike, crossing, false)\n        - One moving left to right: `[440, 200]` (motorbike, crossing, false)\n        - One moving left to right: `[380, 235]` (motorbike, crossing, false)\n        - One moving left to right: `[430, 410]` (motorbike, crossing, false)\n        - One moving left to right: `[420, 540]` (motorbike, crossing, false)\n        - One moving left to right: `[490, 640]` (motorbike, crossing, false)\n        - One moving left to right: `[420, 680]` (motorbike, crossing, false)\n        - One further back on the left: `[250, 130]` (motorbike, far, false)\n        - One further back on the left: `[230, 190]` (motorbike, far, false)\n        - One further back on the left: `[220, 240]` (motorbike, far, false)\n    - Cars/Vans (far carriageway):\n        - White van: `[270, 270]` (van, far, true/unclear - looks queued)\n        - White car: `[260, 330]` (car, far, true/unclear)\n        - White car: `[270, 400]` (car, far, true/unclear)\n        - Silver car behind white van: `[220, 300]` (car, far, true)\n        - Silver car behind that: `[200, 300]` (car, far, true)\n        - Red car further back: `[210, 400]` (car, far, true)\n        - Other cars further back in the queue.\n\n- **Traffic State**: The far carriageway is queued. The crossing area is free-flowing. Overall \"mixed\".\n\n- **Geometry**:\n    - `carsAbreastNearCarriageway`: The near area is a wide intersection. Hard to define \"carriageway\" here. Maybe 4-5 cars.\n    - `carsAbreastFarCarriageway`: Looks like 3 lanes.\n    - `motorbikesAbreastWidest`: In the crossing area, they are spread out. Maybe 3-4 could fit side-by-side.\n    - `twoWheelersFilterBetweenCars`: Yes, they are doing it in the queue.\n\n- **Standstill Gaps**:\n    - The queue of cars on the far carriageway.\n    - Gap between white van `[270, 270]` and silver car `[220, 300]`: maybe 0.5 car lengths.\n    - Gap between white car `[260, 330]` and car behind it: maybe 0.5 car lengths.\n\n- **Unanchored Guesses**:\n    - Demand: Moderate. Maybe 1000-2000 vph.\n    - Speed: Queued cars are 0-10 km/h. Crossing motorbikes are maybe 30-40 km/h. Average maybe 20 km/h.\n\n- **Notes**: Image resolution is low, making it hard to distinguish some distant vehicles.\n\nRefining vehicle list:\n- Motorbike 1: `[350, 35]` (crossing)\n- Motorbike 2: `[430, 115]` (crossing)\n- Motorbike 3: `[440, 200]` (crossing)\n- Motorbike 4: `[380, 235]` (crossing)\n- Motorbike 5: `[430, 410]` (crossing)\n- Motorbike 6: `[420, 540]` (crossing)\n- Motorbike 7: `[490, 640]` (crossing)\n- Motorbike 8: `[420, 680]` (crossing)\n- Motorbike 9: `[250, 130]` (far)\n- Motorbike 10: `[230, 190]` (far)\n- Motorbike 11: `[220, 240]` (far)\n- Van 1: `[270, 270]` (far, stopped)\n- Car 1: `[260, 330]` (far, stopped)\n- Car 2: `[270, 400]` (far, stopped)\n- Car 3: `[220, 300]` (far, stopped)\n- Car 4: `[200, 300]` (far, stopped)\n- Car 5: `[210, 400]` (far, stopped)\n\nLet's re-evaluate `carsAbreastFarCarriageway`. It looks like 3 lanes.\n`carsAbreastNearCarriageway`: The foreground is a huge intersection. I'll put null as it's not a standard carriageway.\n`motorbikesAbreastWidest`: In the crossing, they are quite spread. Maybe 4.\n\nWait, the \"near\" carriageway might be the one coming towards the camera or the one the motorbikes are on. The motorbikes are crossing a wide area.\nActually, the road they are on is the \"near\" one. It's very wide. Maybe 6-8 cars abreast.\n\nLet's double check the \"stopped\" status. The cars in the distance are definitely in a queue.\nThe motorbikes in the foreground are moving.\n\nFinal check on classes:\n- White van `[270, 270]` is a van.\n- White cars `[260, 330]`, `[270, 400]` are cars.\n- Motorbikes are motorbikes.\n\nStandstill gaps:\n- Between Van 1 and Car 3: ~0.5 van lengths.\n- Between Car 1 and Car behind it: ~0.5 car lengths.\n\nLet's refine the points.\n- Motorbike far left: `[350, 35]`\n- Motorbike crossing 1: `[430, 115]`\n- Motorbike crossing 2: `[440, 200]`\n- Motorbike crossing 3: `[380, 235]`\n- Motorbike crossing 4: `[430, 410]`\n- Motorbike crossing 5: `[420, 540]`\n- Motorbike crossing 6: `[490, 640]`\n- Motorbike crossing 7: `[420, 680]`\n- Motorbike far 1: `[250, 130]`\n- Motorbike far 2: `[230, 190]`\n- Motorbike far 3: `[220, 240]`\n- Van 1: `[270, 270]`\n- Car 1: `[260, 330]`\n- Car 2: `[270, 400]`\n- Car 3: `[220, 300]`\n- Car 4: `[200, 300]`\n- Car 5: `[210, 400]`\n\nActually, looking at the image, the \"far\" carriageway is the one with the queue. The \"near\" one is the wide intersection area.\n`carsAbreastFarCarriageway`: 3.\n`carsAbreastNearCarriageway`: maybe 6.\n`motorbikesAbreastWidest`: 4.\n\nTraffic state: \"mixed\" because some are queued, some are flowing.\n\nOne more look at \"activeRain\". The road is very wet, but I don't see rain streaks. I'll stick with `false`.\n\nFinal JSON structure check.```json\n{\"legible\": 3,\n \"daylight\": true, \"wetPavement\": true, \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [{\"class\": \"motorbike\", \"point\": [350, 35], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [430, 115], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [440, 200], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [380, 235], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [430, 410], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [420, 540], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [490, 640], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [420, 680], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [250, 130], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [230, 190], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [220, 240], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"van\", \"point\": [270, 270], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [260, 330], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [270, 400], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [220, 300], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [200, 300], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [210, 400], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8}],\n \"trafficState\": \"mixed\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 6,\n               \"carsAbreastFarCarriageway\": 3,\n               \"motorbikesAbreastWidest\": 4,\n               \"twoWheelersFilterBetweenCars\": true},\n \"standstillGaps\": [{\"class\": \"van\", \"gapInVehicleLengths\": 0.5, \"basis\": \"van to car behind\"}],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 1500, \"meanSpeedKmh\": 20},\n \"notes\": \"Low image resolution makes distant vehicle identification slightly uncertain.\"}\n===JSON===",
      "reading": {
        "legible": 3.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "motorbike",
            "point": [
              350.0,
              35.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              430.0,
              115.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              440.0,
              200.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              380.0,
              235.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              430.0,
              410.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              420.0,
              540.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              490.0,
              640.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              420.0,
              680.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              250.0,
              130.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              230.0,
              190.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              220.0,
              240.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "van",
            "point": [
              270.0,
              270.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              260.0,
              330.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              270.0,
              400.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              220.0,
              300.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              200.0,
              300.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              210.0,
              400.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          }
        ],
        "trafficState": "mixed",
        "geometry": {
          "carsAbreastNearCarriageway": 6,
          "carsAbreastFarCarriageway": 3,
          "motorbikesAbreastWidest": 4,
          "twoWheelersFilterBetweenCars": true
        },
        "standstillGaps": [
          {
            "class": "van",
            "gapInVehicleLengths": 0.5,
            "basis": "van to car behind"
          }
        ],
        "unanchoredGuesses": {
          "demandVehPerHour": 1500.0,
          "meanSpeedKmh": 20.0
        },
        "notes": "Low image resolution makes distant vehicle identification slightly uncertain."
      },
      "repairs": []
    },
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_005.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:24:34 GMT",
      "receivedAtUTC": "2026-09-19T09:24:43.285175+00:00",
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      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- **Legibility**: The image is clear enough to identify vehicles and road markings. (4/5)\n- **Daylight**: Yes, it's daytime.\n- **Wet Pavement**: Yes, the road is clearly wet with reflections.\n- **Active Rain**: Hard to tell for sure, but the pavement is very wet and the sky looks overcast. I'll mark as `false` unless I see rain streaks, but it's likely raining or just rained. Actually, looking closely, there are no obvious rain streaks, but the road is soaked. I'll put `false` for active rain but `true` for wet pavement.\n- **Occluded Approaches**: No, the main approaches are visible.\n- **Two-Wheelers Share Carriageway With Cars**: Yes, motorbikes are riding alongside cars.\n\n- **Vehicles**:\n    - Red car crossing: `{\"class\": \"car\", \"point\": [485, 725], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 1.0}`\n    - White car (far right, moving away): `{\"class\": \"car\", \"point\": [270, 570], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 1.0}`\n    - White van (near, in queue): `{\"class\": \"van\", \"point\": [280, 270], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9}`\n    - White car (near, in queue): `{\"class\": \"car\", \"point\": [275, 335], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9}`\n    - Silver car (near, in queue): `{\"class\": \"car\", \"point\": [230, 305], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.8}`\n    - Red car (near, in queue): `{\"class\": \"car\", \"point\": [230, 355], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.8}`\n    - Other cars in the queue further back: several more cars/vans.\n    - Motorbike (far left, moving): `{\"class\": \"motorbike\", \"point\": [440, 50], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0}`\n    - Motorbike (near left, moving): `{\"class\": \"motorbike\", \"point\": [310, 95], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0}`\n    - Motorbike (further back, near): `{\"class\": \"motorbike\", \"point\": [260, 160], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9}`\n    - Motorbike (further back, near): `{\"class\": \"motorbike\", \"point\": [240, 215], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9}`\n    - Motorbikes in the distance: several more.\n\n- **Traffic State**: Mixed. There's a queue on the near side, but free flow on the far side and for some motorbikes.\n- **Geometry**:\n    - `carsAbreastNearCarriageway`: Looking at the lane markings, it seems to be about 3-4 lanes wide. Let's say 4.\n    - `carsAbreastFarCarriageway`: Also looks like 3-4 lanes. Let's say 4.\n    - `motorbikesAbreastWidest`: In the queue area, motorbikes are filtering. Maybe 3-4 abreast.\n    - `twoWheelersFilterBetweenCars`: Yes, clearly visible.\n\n- **Standstill Gaps**:\n    - Between the white van [280, 270] and the silver car [230, 305] (roughly).\n    - Between the white car [275, 335] and the red car [230, 355].\n    - Gap between white van and silver car: maybe 0.5 vehicle lengths.\n    - Gap between white car and red car: maybe 0.5 vehicle lengths.\n\n- **Unanchored Guesses**:\n    - `demandVehPerHour`: High, given the queue. Maybe 1500-2000.\n    - `meanSpeedKmh`: Low due to queue, but some are moving. Maybe 20 km/h.\n\n- **Notes**: \"Queue on the near side slows overall flow.\"\n\nRefining vehicle list:\n- Red car crossing: [485, 725]\n- White car far: [270, 570]\n- White van near: [280, 270]\n- White car near: [275, 335]\n- Silver car near: [230, 305]\n- Red car near: [230, 355]\n- Motorbike far left: [440, 50]\n- Motorbike near left: [310, 95]\n- Motorbike further back: [260, 160]\n- Motorbike further back: [240, 215]\n- Motorbike further back: [210, 230]\n- Motorbike further back: [200, 250]\n- Car further back in queue: [200, 310]\n- Car further back in queue: [190, 340]\n- Car further back in queue: [170, 350]\n- Car further back in queue: [160, 360]\n\nLet's re-evaluate `carsAbreastNearCarriageway`. The road is quite wide. There are at least 3 lanes for cars, plus space for motorbikes. I'll estimate 4.\n`carsAbreastFarCarriageway`: Similar, 4.\n`motorbikesAbreastWidest`: 3-4.\n\nStandstill gaps:\n- White van [280, 270] and silver car [230, 305]: gap is small, ~0.3.\n- White car [275, 335] and red car [230, 355]: gap is small, ~0.3.\n\nFinal check on classes:\n- Red car crossing: car\n- White car far: car\n- White van near: van\n- White car near: car\n- Silver car near: car\n- Red car near: car\n- Motorbikes: motorbike\n\nWait, the white van [280, 270] looks like a passenger van/minibus. Yes, \"van\".\nThe white car [275, 335] is a car.\nThe silver car [230, 305] is a car.\nThe red car [230, 355] is a car.\n\nLet's refine the points.\nRed car crossing: y=485, x=725\nWhite car far: y=270, x=570\nWhite van near: y=280, x=270\nWhite car near: y=275, x=335\nSilver car near: y=230, x=305\nRed car near: y=230, x=355\nMotorbike 1: y=440, x=50\nMotorbike 2: y=310, x=95\nMotorbike 3: y=260, x=160\nMotorbike 4: y=240, x=215\n\nTraffic state: \"mixed\" because some are queued and some are moving.```json\n{\"legible\": 4,\n \"daylight\": true, \"wetPavement\": true, \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [{\"class\": \"car\", \"point\": [485, 725], \"carriageway\": \"crossing\", \"stopped\": false, \"confidence\": 1.0},\n              {\"class\": \"car\", \"point\": [270, 570], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 1.0},\n              {\"class\": \"van\", \"point\": [280, 270], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [275, 335], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [230, 305], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [230, 355], \"carriageway\": \"near\", \"stopped\": true, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [440, 50], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0},\n              {\"class\": \"motorbike\", \"point\": [310, 95], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 1.0},\n              {\"class\": \"motorbike\", \"point\": [260, 160], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [240, 215], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9}],\n \"trafficState\": \"mixed\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 4,\n               \"carsAbreastFarCarriageway\": 4,\n               \"motorbikesAbreastWidest\": 3,\n               \"twoWheelersFilterBetweenCars\": true},\n \"standstillGaps\": [{\"class\": \"van\", \"gapInVehicleLengths\": 0.3, \"basis\": \"van to car\"},\n                    {\"class\": \"car\", \"gapInVehicleLengths\": 0.3, \"basis\": \"car to car\"}],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 1800, \"meanSpeedKmh\": 20},\n \"notes\": \"Significant queuing on the near carriageway.\"}\n``` ===JSON===",
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "car",
            "point": [
              485.0,
              725.0
            ],
            "carriageway": "crossing",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              270.0,
              570.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "van",
            "point": [
              280.0,
              270.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              275.0,
              335.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              230.0,
              305.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              230.0,
              355.0
            ],
            "carriageway": "near",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              440.0,
              50.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              310.0,
              95.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              260.0,
              160.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              240.0,
              215.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          }
        ],
        "trafficState": "mixed",
        "geometry": {
          "carsAbreastNearCarriageway": 4,
          "carsAbreastFarCarriageway": 4,
          "motorbikesAbreastWidest": 3,
          "twoWheelersFilterBetweenCars": true
        },
        "standstillGaps": [
          {
            "class": "van",
            "gapInVehicleLengths": 0.3,
            "basis": "van to car"
          },
          {
            "class": "car",
            "gapInVehicleLengths": 0.3,
            "basis": "car to car"
          }
        ],
        "unanchoredGuesses": {
          "demandVehPerHour": 1800.0,
          "meanSpeedKmh": 20.0
        },
        "notes": "Significant queuing on the near carriageway."
      },
      "repairs": []
    },
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_006.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:24:43 GMT",
      "receivedAtUTC": "2026-09-19T09:24:53.293584+00:00",
      "sha256": "584c2ea443c1c0786a594d373516d6b92d96c6bd9f623c339185e0c120986205",
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      "requestedAt": "2026-09-19T10:39:49.074069+00:00",
      "receivedAt": "2026-09-19T10:41:34.273406+00:00",
      "latencySeconds": 105.2,
      "finishReason": "STOP",
      "usage": {
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      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- **Legibility**: The image is clear enough to identify vehicles and road markings. (4/5)\n- **Daylight**: Yes, it's daytime. (true)\n- **Wet Pavement**: Yes, the road is clearly wet with reflections. (true)\n- **Active Rain**: Hard to tell for sure, but the pavement is very wet and the sky looks overcast. I'll mark as false unless I see rain streaks, but it looks like it just rained or is drizzling. Actually, looking closely, there are no obvious rain streaks, but the road is soaked. I'll put false for active rain but true for wet pavement.\n- **Occluded Approaches**: No, the main approaches are visible. (false)\n- **Two-Wheelers Share Carriageway With Cars**: Yes, motorbikes are riding alongside cars. (true)\n\n- **Vehicles**:\n    - Motorbike 1: far left, moving towards camera. [340, 70]\n    - Motorbike 2: far left, behind MB1. [310, 85]\n    - Motorbike 3: far left, further back. [320, 135]\n    - Motorbike 4: far left, further back. [290, 150]\n    - Motorbike 5: far left, further back. [250, 180]\n    - Motorbike 6: far left, further back. [220, 210]\n    - Van 1: white van, far carriageway, queued. [280, 270]\n    - Car 1: white car, far carriageway, queued. [270, 335]\n    - Car 2: silver car, far carriageway, queued. [220, 310]\n    - Car 3: red car, far carriageway, queued. [230, 355]\n    - Car 4: silver car, far carriageway, queued. [190, 310]\n    - Car 5: white car, far carriageway, queued. [170, 325]\n    - Car 6: white car, far carriageway, queued. [150, 330]\n    - Car 7: white car, far carriageway, queued. [130, 340]\n    - Car 8: white car, far carriageway, queued. [110, 345]\n    - Car 9: white car, far carriageway, queued. [90, 350]\n    - Car 10: white car, far carriageway, queued. [70, 355]\n    - Car 11: white car, far carriageway, queued. [50, 360]\n    - Motorbikes in the far queue: there are many, hard to distinguish individually but they are there. I'll list a few clear ones.\n    - Motorbike 7: [150, 290]\n    - Motorbike 8: [130, 295]\n    - Motorbike 9: [110, 300]\n    - Motorbike 10: [90, 305]\n    - Motorbike 11: [70, 310]\n    - Motorbike 12: [50, 315]\n\n- **Traffic State**: The far carriageway is queued. The near carriageway is free-flowing (empty). Overall: \"mixed\" or \"queued\" for the active lane. I'll go with \"mixed\" because one side is empty and the other is queued.\n\n- **Geometry**:\n    - `carsAbreastNearCarriageway`: The near carriageway (foreground) is very wide. It looks like it could fit about 4-5 cars. Let's say 5.\n    - `carsAbreastFarCarriageway`: The far carriageway (where the queue is) looks like it has 2-3 lanes. Let's say 3.\n    - `motorbikesAbreastWidest`: In the far left, they are mostly single file or slightly staggered. In the queue, they are packed. Maybe 3-4 abreast in the gaps. Let's say 3.\n    - `twoWheelersFilterBetweenCars`: Yes, they are filtering on the left of the car queue. (true)\n\n- **Standstill Gaps**:\n    - Van 1 to Car 1: Gap is small, maybe 0.2 vehicle lengths. Basis: Van 1.\n    - Car 1 to Car 2: Gap is small, maybe 0.3 vehicle lengths. Basis: Car 1.\n    - Car 2 to Car 3: Gap is small, maybe 0.2 vehicle lengths. Basis: Car 2.\n    - (The queue is quite tight).\n\n- **Unanchored Guesses**:\n    - `demandVehPerHour`: High, given the queue. Maybe 1500-2000.\n    - `meanSpeedKmh`: Low for the queued lane (5-10), high for the empty lane. Average maybe 15-20.\n\n- **Notes**: \"Heavy congestion in the far carriageway, wet road surface.\"\n\nRefining vehicle list:\n- Motorbike 1: [345, 68]\n- Motorbike 2: [310, 85]\n- Motorbike 3: [325, 135]\n- Motorbike 4: [295, 150]\n- Motorbike 5: [255, 180]\n- Motorbike 6: [225, 210]\n- Van 1: [285, 270] (white van)\n- Car 1: [275, 335] (white car)\n- Car 2: [225, 310] (silver car)\n- Car 3: [235, 355] (red car)\n- Car 4: [195, 310] (silver car)\n- Car 5: [175, 325] (white car)\n- Car 6: [155, 330] (white car)\n- Car 7: [135, 340] (white car)\n- Car 8: [115, 345] (white car)\n- Car 9: [95, 350] (white car)\n- Car 10: [75, 355] (white car)\n- Car 11: [55, 360] (white car)\n- Motorbike 7: [150, 290]\n- Motorbike 8: [130, 295]\n- Motorbike 9: [110, 300]\n- Motorbike 10: [90, 305]\n- Motorbike 11: [70, 310]\n- Motorbike 12: [50, 315]\n\nWait, the \"near\" carriageway is the one in the foreground. It's empty.\nThe \"far\" carriageway is the one with the traffic.\n`carsAbreastNearCarriageway`: Looking at the width of the foreground road, it's huge. Maybe 6 cars abreast.\n`carsAbreastFarCarriageway`: The lane with the queue looks like 3 lanes.\n\nLet's re-evaluate `standstillGaps`.\nVan 1 (white van) is at the front of the queue.\nCar 1 (white car) is behind it. Gap is ~0.3.\nCar 2 (silver car) is behind Car 1. Gap is ~0.2.\nCar 3 (red car) is next to Car 2.\nCar 4 (silver car) is behind Car 2. Gap is ~0.2.\n\nActually, looking at the image, the white van is in one lane, the white car is in another.\nLane 1 (leftmost of the far carriageway): Motorbikes.\nLane 2: White van, silver car, silver car...\nLane 3: White car, red car, white car...\nWait, the white van is in the middle lane. The white car [275, 335] is to its right.\nSo:\nLane 2: Van 1 [285, 270] -> Car 2 [225, 310] -> Car 4 [195, 310]\nLane 3: Car 1 [275, 335] -> Car 3 [235, 355] -> Car 5 [175, 325]\nGaps:\nVan 1 to Car 2: ~0.5 vehicle lengths.\nCar 2 to Car 4: ~0.3 vehicle lengths.\nCar 1 to Car 3: ~0.4 vehicle lengths.\nCar 3 to Car 5: ~0.3 vehicle lengths.\n\nLet's double check the \"near\" vs \"far\" carriageway.\nUsually, \"near\" is the one closest to the camera. The foreground is the near carriageway.\n\"far\" is the one further away. The one with the traffic is the far carriageway.\n\nFinal check on vehicle classes:\n- White van [285, 270] is a van.\n- White car [275, 335] is a car.\n- Silver car [225, 310] is a car.\n- Red car [235, 355] is a car.\n- Others are cars or motorbikes.\n\n`twoWheelersFilterBetweenCars`: Yes, clearly visible on the left side of the car queue.\n\n`trafficState`: \"queued\" for the far carriageway, \"free-flowing\" for the near. I'll use \"mixed\".\n\n`geometry`:\n- `carsAbreastNearCarriageway`: 6\n- `carsAbreastFarCarriageway`: 3\n- `motorbikesAbreastWidest`: 3 (in the queue)\n\n`unanchoredGuesses`:\n- `demandVehPerHour`: 1200\n- `meanSpeedKmh`: 10 (due to the queue)\n\n`notes`: \"Heavy queue in the far carriageway, wet road surface.\"```json\n{\"legible\": 4,\n \"daylight\": true,\n \"wetPavement\": true,\n \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [\n                {\"class\": \"motorbike\", \"point\": [345, 68], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [310, 85], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [325, 135], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [295, 150], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [255, 180], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [225, 210], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n                {\"class\": \"van\", \"point\": [285, 270], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [275, 335], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [225, 310], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [235, 355], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [195, 310], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [175, 325], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [155, 330], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [135, 340], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [115, 345], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [95, 350], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [75, 355], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"car\", \"point\": [55, 360], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.9},\n                {\"class\": \"motorbike\", \"point\": [150, 290], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8},\n                {\"class\": \"motorbike\", \"point\": [130, 295], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8},\n                {\"class\": \"motorbike\", \"point\": [110, 300], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8},\n                {\"class\": \"motorbike\", \"point\": [90, 305], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8},\n                {\"class\": \"motorbike\", \"point\": [70, 310], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8},\n                {\"class\": \"motorbike\", \"point\": [50, 315], \"carriageway\": \"far\", \"stopped\": true, \"confidence\": 0.8}\n ],\n \"trafficState\": \"mixed\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 6,\n               \"carsAbreastFarCarriageway\": 3,\n               \"motorbikesAbreastWidest\": 3,\n               \"twoWheelersFilterBetweenCars\": true},\n \"standstillGaps\": [\n                {\"class\": \"car\", \"gapInVehicleLengths\": 0.5, \"basis\": \"van\"},\n                {\"class\": \"car\", \"gapInVehicleLengths\": 0.3, \"basis\": \"car\"},\n                {\"class\": \"car\", \"gapInVehicleLengths\": 0.4, \"basis\": \"car\"}\n ],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 1200, \"meanSpeedKmh\": 10},\n \"notes\": \"Heavy queue in the far carriageway, wet road surface.\"}\n===JSON===```",
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "motorbike",
            "point": [
              345.0,
              68.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              310.0,
              85.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              325.0,
              135.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              295.0,
              150.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              255.0,
              180.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              225.0,
              210.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "van",
            "point": [
              285.0,
              270.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              275.0,
              335.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              225.0,
              310.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              235.0,
              355.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              195.0,
              310.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              175.0,
              325.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              155.0,
              330.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              135.0,
              340.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              115.0,
              345.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              95.0,
              350.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              75.0,
              355.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              55.0,
              360.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              150.0,
              290.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              130.0,
              295.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              110.0,
              300.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              90.0,
              305.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              70.0,
              310.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              50.0,
              315.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.8
          }
        ],
        "trafficState": "mixed",
        "geometry": {
          "carsAbreastNearCarriageway": 6,
          "carsAbreastFarCarriageway": 3,
          "motorbikesAbreastWidest": 3,
          "twoWheelersFilterBetweenCars": true
        },
        "standstillGaps": [
          {
            "class": "car",
            "gapInVehicleLengths": 0.5,
            "basis": "van"
          },
          {
            "class": "car",
            "gapInVehicleLengths": 0.3,
            "basis": "car"
          },
          {
            "class": "car",
            "gapInVehicleLengths": 0.4,
            "basis": "car"
          }
        ],
        "unanchoredGuesses": {
          "demandVehPerHour": 1200.0,
          "meanSpeedKmh": 10.0
        },
        "notes": "Heavy queue in the far carriageway, wet road surface."
      },
      "repairs": []
    },
    {
      "file": "data/cctv/corridor-sample/56de42f611f398ec0c48128a_007.jpg",
      "cameraId": "56de42f611f398ec0c48128a",
      "cameraName": "Võ Văn Kiệt - Trần Đình Xu 2",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:24:54 GMT",
      "receivedAtUTC": "2026-09-19T09:25:03.570651+00:00",
      "sha256": "153b75ce6a72c0f9f477fe40cb2b20d29cd8249a1736b413b10a3c54adc19b61",
      "duplicateOfEarlierFrame": false,
      "captureManifest": "data/cctv/corridor-sample/manifest.json",
      "requestedAt": "2026-09-19T10:44:21.436149+00:00",
      "receivedAt": "2026-09-19T10:45:44.782510+00:00",
      "latencySeconds": 83.3,
      "finishReason": "STOP",
      "usage": {
        "promptTokenCount": 1148,
        "candidatesTokenCount": 924,
        "totalTokenCount": 4117,
        "promptTokensDetails": [
          {
            "modality": "TEXT",
            "tokenCount": 890
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          {
            "modality": "IMAGE",
            "tokenCount": 258
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        ],
        "thoughtsTokenCount": 2045,
        "serviceTier": "standard"
      },
      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- Legible: The image is clear enough to identify vehicles and road markings. (4/5)\n- Daylight: Yes, it's daytime.\n- Wet Pavement: Yes, the road is clearly wet with reflections.\n- Active Rain: Hard to tell for sure, but the pavement is wet and some riders are wearing rain gear (yellow/blue ponchos). I'll mark it as true or unclear. Actually, looking closely, there are no visible rain streaks, but the wetness and ponchos strongly suggest it's raining or just stopped. I'll go with true.\n- Occluded Approaches: No major structures blocking the view of the approaches.\n- TwoWheelersShareCarriagewayWithCars: Yes, motorbikes are mixed with cars.\n\n- Near carriageway (bottom/foreground):\n    - Red car: `[890, 470]`, crossing/near, moving, confidence 1.0.\n    - Motorbike (yellow/blue ponchos): `[690, 460]`, crossing/near, moving, confidence 1.0.\n    - Motorbike (red poncho): `[510, 720]`, crossing/near, moving, confidence 1.0.\n    - White car (right edge): `[540, 960]`, crossing/near, moving, confidence 1.0.\n- Far carriageway (top/background):\n    - White van: `[280, 270]`, far, stopped/queued, confidence 1.0.\n    - White car: `[270, 330]`, far, stopped/queued, confidence 1.0.\n    - Silver car: `[230, 300]`, far, stopped/queued, confidence 1.0.\n    - Red car: `[230, 350]`, far, stopped/queued, confidence 1.0.\n    - White car: `[180, 390]`, far, moving/stopped, confidence 0.9.\n    - Several motorbikes on the left side of the far carriageway:\n        - `[320, 65]`, far, moving, confidence 1.0.\n        - `[290, 125]`, far, moving, confidence 1.0.\n        - `[290, 150]`, far, moving, confidence 1.0.\n        - `[310, 180]`, far, moving, confidence 1.0.\n        - `[220, 210]`, far, moving, confidence 1.0.\n    - More cars further back in the queue:\n        - `[160, 330]`, far, stopped, confidence 0.8.\n        - `[150, 350]`, far, stopped, confidence 0.8.\n        - `[140, 360]`, far, stopped, confidence 0.8.\n\n- Traffic State: Mixed. The far carriageway has a queue, while the foreground is free-flowing.\n\n- Geometry:\n    - `carsAbreastNearCarriageway`: The foreground area is a wide intersection. Hard to define a single \"carriageway\" width here, but it looks like it could fit 4-5 cars.\n    - `carsAbreastFarCarriageway`: Looking at the lane markings, it seems to be 3-4 lanes. Let's say 3.\n    - `motorbikesAbreastWidest`: In the far left, there are about 2-3 motorbikes side-by-side.\n    - `twoWheelersFilterBetweenCars`: Yes, motorbikes are filtering on the left of the car queue.\n\n- Standstill Gaps:\n    - Far carriageway queue:\n        - Gap between white van `[280, 270]` and silver car `[230, 300]`: maybe 0.5 car lengths.\n        - Gap between white car `[270, 330]` and red car `[230, 350]`: maybe 0.5 car lengths.\n\n- Unanchored Guesses:\n    - Demand: Moderate.\n    - Speed: Low in queue, moderate in foreground. Maybe 20-30 km/h average.\n\n- Notes: Rain gear and wet pavement indicate rainy conditions.\n\nRefining vehicle list:\n- Red car (foreground): `[890, 470]`, near, moving.\n- Motorbike (yellow/blue): `[690, 460]`, near, moving.\n- Motorbike (red): `[510, 720]`, near, moving.\n- White car (right): `[540, 960]`, near, moving.\n- White van (far): `[280, 270]`, far, stopped.\n- White car (far): `[270, 330]`, far, stopped.\n- Silver car (far): `[230, 300]`, far, stopped.\n- Red car (far): `[230, 350]`, far, stopped.\n- White car (far): `[180, 390]`, far, stopped.\n- Motorbike (far left 1): `[320, 65]`, far, moving.\n- Motorbike (far left 2): `[290, 125]`, far, moving.\n- Motorbike (far left 3): `[290, 150]`, far, moving.\n- Motorbike (far left 4): `[310, 180]`, far, moving.\n- Motorbike (far left 5): `[220, 210]`, far, moving.\n\nWait, the \"near\" carriageway is the one in the foreground. The \"far\" one is the one going away.\nThe red car is in the foreground, crossing the intersection.\nThe motorbikes in the foreground are also crossing.\nThe white car on the right is crossing.\nThe queue is in the far carriageway.\n\nLet's re-evaluate `carsAbreastNearCarriageway`. The foreground is an intersection, not a simple carriageway. I'll put null.\n`carsAbreastFarCarriageway`: Looks like 3 lanes.\n`motorbikesAbreastWidest`: 3.\n\nStandstill gaps:\n- Between white van `[280, 270]` and silver car `[230, 300]`: ~0.5 car lengths.\n- Between white car `[270, 330]` and red car `[230, 350]`: ~0.5 car lengths.\n\nFinal check on classes:\n- Red car (foreground): car\n- Motorbike (yellow/blue): motorbike\n- Motorbike (red): motorbike\n- White car (right): car\n- White van (far): van\n- White car (far): car\n- Silver car (far): car\n- Red car (far): car\n- White car (far): car\n- Motorbikes (far left): motorbike\n\nWait, the white van `[280, 270]` looks like a passenger van.\nThe white car `[270, 330]` is a car.\nThe silver car `[230, 300]` is a car.\nThe red car `[230, 350]` is a car.\n\nLet's refine the points.\nRed car foreground: y=890, x=470.\nMotorbike yellow/blue: y=690, x=460.\nMotorbike red: y=510, x=720.\nWhite car right: y=540, x=960.\nWhite van far: y=280, x=270.\nWhite car far: y=270, x=330.\nSilver car far: y=230, x=300.\nRed car far: y=230, x=350.\nWhite car far: y=180, x=390.\nMotorbike far left 1: y=320, x=65.\nMotorbike far left 2: y=290, x=125.\nMotorbike far left 3: y=290, x=150.\nMotorbike far left 4: y=310, x=180.\nMotorbike far left 5: y=220, x=210.\n\nTraffic state: \"mixed\" because some are queued and some are moving.```json\n{\"legible\": 4,\n \"daylight\": true, \"wetPavement\": true, \"activeRain\": true,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [{\"class\": \"car\",\n                \"point\": [890, 470],\n                \"carriageway\": \"near\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"motorbike\",\n                \"point\": [690, 460],\n                \"carriageway\": \"near\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"motorbike\",\n                \"point\": [510, 720],\n                \"carriageway\": \"near\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"car\",\n                \"point\": [540, 960],\n                \"carriageway\": \"near\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"van\",\n                \"point\": [280, 270],\n                \"carriageway\": \"far\",\n                \"stopped\": true,\n                \"confidence\": 1.0},\n              {\"class\": \"car\",\n                \"point\": [270, 330],\n                \"carriageway\": \"far\",\n                \"stopped\": true,\n                \"confidence\": 1.0},\n              {\"class\": \"car\",\n                \"point\": [230, 300],\n                \"carriageway\": \"far\",\n                \"stopped\": true,\n                \"confidence\": 1.0},\n              {\"class\": \"car\",\n                \"point\": [230, 350],\n                \"carriageway\": \"far\",\n                \"stopped\": true,\n                \"confidence\": 1.0},\n              {\"class\": \"car\",\n                \"point\": [180, 390],\n                \"carriageway\": \"far\",\n                \"stopped\": true,\n                \"confidence\": 0.9},\n              {\"class\": \"motorbike\",\n                \"point\": [320, 65],\n                \"carriageway\": \"far\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"motorbike\",\n                \"point\": [290, 125],\n                \"carriageway\": \"far\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"motorbike\",\n                \"point\": [290, 150],\n                \"carriageway\": \"far\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"motorbike\",\n                \"point\": [310, 180],\n                \"carriageway\": \"far\",\n                \"stopped\": false,\n                \"confidence\": 1.0},\n              {\"class\": \"motorbike\",\n                \"point\": [220, 210],\n                \"carriageway\": \"far\",\n                \"stopped\": false,\n                \"confidence\": 1.0}],\n \"trafficState\": \"mixed\",\n \"geometry\": {\"carsAbreastNearCarriageway\": null,\n               \"carsAbreastFarCarriageway\": 3,\n               \"motorbikesAbreastWidest\": 3,\n               \"twoWheelersFilterBetweenCars\": true},\n \"standstillGaps\": [{\"class\": \"car\",\n                      \"gapInVehicleLengths\": 0.5, \"basis\": \"car to car in far queue\"}],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 800, \"meanSpeedKmh\": 25},\n \"notes\": \"Rain gear and wet pavement indicate rainy conditions; far carriageway is queued.\"}\n===JSON===",
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": true,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "car",
            "point": [
              890.0,
              470.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              690.0,
              460.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              510.0,
              720.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              540.0,
              960.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "van",
            "point": [
              280.0,
              270.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              270.0,
              330.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              230.0,
              300.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              230.0,
              350.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 1.0
          },
          {
            "class": "car",
            "point": [
              180.0,
              390.0
            ],
            "carriageway": "far",
            "stopped": true,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              320.0,
              65.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              290.0,
              125.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              290.0,
              150.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              310.0,
              180.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          },
          {
            "class": "motorbike",
            "point": [
              220.0,
              210.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 1.0
          }
        ],
        "trafficState": "mixed",
        "geometry": {
          "carsAbreastNearCarriageway": null,
          "carsAbreastFarCarriageway": 3,
          "motorbikesAbreastWidest": 3,
          "twoWheelersFilterBetweenCars": true
        },
        "standstillGaps": [
          {
            "class": "car",
            "gapInVehicleLengths": 0.5,
            "basis": "car to car in far queue"
          }
        ],
        "unanchoredGuesses": {
          "demandVehPerHour": 800.0,
          "meanSpeedKmh": 25.0
        },
        "notes": "Rain gear and wet pavement indicate rainy conditions; far carriageway is queued."
      },
      "repairs": []
    },
    {
      "file": "data/cctv/20260919T093332Z/56de42f611f398ec0c481288_000.jpg",
      "cameraId": "56de42f611f398ec0c481288",
      "cameraName": "Võ Văn Kiệt - Cầu Ông Lãnh 1",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:33:25 GMT",
      "receivedAtUTC": "2026-09-19T09:33:34.324099+00:00",
      "sha256": "f69cc0b1f48659ecd5c0814837acc6e63b34018412623270be449a6fc08de52f",
      "duplicateOfEarlierFrame": false,
      "captureManifest": "data/cctv/20260919T093332Z/manifest.json",
      "requestedAt": "2026-09-19T10:50:33.018017+00:00",
      "receivedAt": "2026-09-19T10:52:57.442464+00:00",
      "latencySeconds": 144.4,
      "finishReason": "STOP",
      "usage": {
        "promptTokenCount": 1148,
        "candidatesTokenCount": 1424,
        "totalTokenCount": 6264,
        "promptTokensDetails": [
          {
            "modality": "TEXT",
            "tokenCount": 890
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          {
            "modality": "IMAGE",
            "tokenCount": 258
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        ],
        "thoughtsTokenCount": 3692,
        "serviceTier": "standard"
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      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- Location: Võ Văn Kiệt, Ho Chi Minh City.\n- Image size: 512 x 288.\n- Camera: Fixed pole, looking along the corridor beside Bến Nghé canal.\n- Date/Time: 19.Sep 2026, 16:33:31 (from overlay).\n\n- Legibility: The image is clear enough to identify vehicles. (4/5)\n- Daylight: Yes, it's daytime.\n- Wet Pavement: No, looks dry.\n- Active Rain: No.\n- Occluded Approaches: No major occlusions of the traffic stream.\n- Two-wheelers share carriageway: Yes, motorbikes are clearly sharing the road with cars.\n\n- Near Carriageway (coming towards camera/bottom):\n    - White SUV (bottom left): `[868, 132]` - car\n    - Grey SUV/MPV (center): `[602, 480]` - car\n    - White SUV (right): `[641, 684]` - car\n    - Motorbike (bottom center): `[945, 530]` - motorbike\n    - Motorbike (bottom center, slightly above): `[830, 525]` - motorbike\n    - Motorbike (bottom center, further up): `[740, 550]` - motorbike\n    - Motorbike (bottom right): `[815, 620]` - motorbike\n    - Motorbike (bottom right, further up): `[725, 730]` - motorbike\n    - Motorbike (right edge): `[560, 890]` - motorbike\n- Far Carriageway (going away from camera/top):\n    - Teal car (left): `[420, 68]` - car\n    - White van (left): `[325, 350]` - van\n    - White car (left): `[320, 450]` - car\n    - Red car (center): `[450, 540]` - car\n    - Silver car (center): `[315, 635]` - car\n    - White car (center): `[325, 675]` - car\n    - White van (right): `[350, 725]` - van\n    - Dark car (right): `[275, 760]` - car\n    - Red car (far back): `[250, 580]` - car\n    - Silver car (far back): `[235, 650]` - car\n    - Other cars further back...\n- Motorbikes on the right side (far carriageway/shoulder):\n    - Several motorbikes riding in a group on the right: `[430, 805]`, `[425, 840]`, `[435, 885]`, `[380, 915]`, `[340, 860]`, `[320, 895]`, `[290, 900]`, `[260, 910]`, `[230, 920]`, `[210, 930]`.\n\n- Traffic State: Free-flowing. Vehicles are spaced out.\n- Geometry:\n    - `carsAbreastNearCarriageway`: Looks like 3-4 lanes. Let's say 4.\n    - `carsAbreastFarCarriageway`: Looks like 4-5 lanes. Let's say 4.\n    - `motorbikesAbreastWidest`: In the rightmost area, maybe 3-4 motorbikes abreast.\n    - `twoWheelersFilterBetweenCars`: Not actively filtering in this snapshot, but they are sharing the road.\n\n- Standstill Gaps: None. Traffic is moving.\n\n- Unanchored Guesses:\n    - Demand: Moderate. Maybe 1500-2000 veh/hr per direction.\n    - Speed: Looks like 40-60 km/h.\n\n- Notes: Image is slightly grainy but legible.\n\nRefining vehicle points:\n- White SUV (bottom left): `[868, 132]`\n- Grey SUV (center): `[602, 480]`\n- White SUV (right): `[641, 684]`\n- Motorbike 1: `[945, 530]`\n- Motorbike 2: `[830, 525]`\n- Motorbike 3: `[740, 550]`\n- Motorbike 4: `[815, 620]`\n- Motorbike 5: `[725, 730]`\n- Motorbike 6: `[560, 890]`\n- Teal car: `[420, 68]`\n- White van: `[325, 350]`\n- White car: `[320, 450]`\n- Red car: `[450, 540]`\n- Silver car: `[315, 635]`\n- White car: `[325, 675]`\n- White van: `[350, 725]`\n- Dark car: `[275, 760]`\n- Red car (far): `[250, 580]`\n- Silver car (far): `[235, 650]`\n- Motorbike group (far right):\n    - `[430, 805]`\n    - `[425, 840]`\n    - `[435, 885]`\n    - `[380, 915]`\n    - `[340, 860]`\n    - `[320, 895]`\n    - `[290, 900]`\n    - `[260, 910]`\n    - `[230, 920]`\n    - `[210, 930]`\n\nWait, looking closer at the \"near\" carriageway (bottom half), it's actually the one going *away* from the camera? No, the white SUV at the bottom left is facing away. The grey SUV is facing away. The white SUV on the right is facing away.\nActually, looking at the lane markings and the flow:\n- Bottom half: Vehicles are moving away from the camera.\n- Top half: Vehicles are moving towards the camera.\nWait, look at the white van `[325, 350]` and white car `[320, 450]`. They are facing the camera.\nThe teal car `[420, 68]` is facing the camera.\nThe red car `[450, 540]` is facing the camera.\nThe white SUV `[868, 132]` is facing away.\nThe grey SUV `[602, 480]` is facing away.\nThe white SUV `[641, 684]` is facing away.\nSo:\n- Near carriageway (bottom): moving away.\n- Far carriageway (top): moving towards.\n\nLet's re-verify.\nWhite SUV `[868, 132]` - rear visible. Moving away.\nGrey SUV `[602, 480]` - rear visible. Moving away.\nWhite SUV `[641, 684]` - rear visible. Moving away.\nTeal car `[420, 68]` - front visible. Moving towards.\nWhite van `[325, 350]` - front visible. Moving towards.\nWhite car `[320, 450]` - front visible. Moving towards.\nRed car `[450, 540]` - front visible. Moving towards.\nWhite van `[350, 725]` - front visible. Moving towards.\n\nOkay, so:\nNear = bottom half (moving away).\nFar = top half (moving towards).\n\nWait, usually \"near\" is the one closest to the camera.\nBottom half is closest.\nTop half is further.\n\nLet's re-list:\nNear (bottom):\n- White SUV: `[868, 132]`\n- Grey SUV: `[602, 480]`\n- White SUV: `[641, 684]`\n- Motorbikes: `[945, 530]`, `[830, 525]`, `[740, 550]`, `[815, 620]`, `[725, 730]`, `[560, 890]`\n\nFar (top):\n- Teal car: `[420, 68]`\n- White van: `[325, 350]`\n- White car: `[320, 450]`\n- Red car: `[450, 540]`\n- Silver car: `[315, 635]`\n- White car: `[325, 675]`\n- White van: `[350, 725]`\n- Dark car: `[275, 760]`\n- Red car (far): `[250, 580]`\n- Silver car (far): `[235, 650]`\n- Motorbikes (right side): `[430, 805]`, `[425, 840]`, `[435, 885]`, `[380, 915]`, `[340, 860]`, `[320, 895]`, `[290, 900]`, `[260, 910]`, `[230, 920]`, `[210, 930]`\n\nWait, the motorbikes on the right are they in the far carriageway?\nThey are on the right side of the road, moving towards the camera. Yes, they are in the far carriageway.\n\nGeometry:\n- `carsAbreastNearCarriageway`: 4 lanes.\n- `carsAbreastFarCarriageway`: 4 lanes.\n- `motorbikesAbreastWidest`: 3-4.\n- `twoWheelersFilterBetweenCars`: unclear/false.\n\nTraffic state: free-flowing.\n\nFinal check on classes:\n- White SUV `[868, 132]` -> car\n- Grey SUV `[602, 480]` -> car\n- White SUV `[641, 684]` -> car\n- Teal car `[420, 68]` -> car\n- White van `[325, 350]` -> van\n- White car `[320, 450]` -> car\n- Red car `[450, 540]` -> car\n- Silver car `[315, 635]` -> car\n- White car `[325, 675]` -> car\n- White van `[350, 725]` -> van\n- Dark car `[275, 760]` -> car\n- Red car `[250, 580]` -> car\n- Silver car `[235, 650]` -> car\n- Motorbikes... -> motorbike\n\nWait, the white van `[325, 350]` looks like a minibus. Class \"van\" is for minibus. Correct.\nThe white van `[350, 725]` is a box van. Class \"van\". Correct.\n\nLet's refine the points for the JSON.\nNear:\n- `[868, 132]` car\n- `[602, 480]` car\n- `[641, 684]` car\n- `[945, 530]` motorbike\n- `[830, 525]` motorbike\n- `[740, 550]` motorbike\n- `[815, 620]` motorbike\n- `[725, 730]` motorbike\n- `[560, 890]` motorbike\n\nFar:\n- `[420, 68]` car\n- `[325, 350]` van\n- `[320, 450]` car\n- `[450, 540]` car\n- `[315, 635]` car\n- `[325, 675]` car\n- `[350, 725]` van\n- `[275, 760]` car\n- `[250, 580]` car\n- `[235, 650]` car\n- `[430, 805]` motorbike\n- `[425, 840]` motorbike\n- `[435, 885]` motorbike\n- `[380, 915]` motorbike\n- `[340, 860]` motorbike\n- `[320, 895]` motorbike\n- `[290, 900]` motorbike\n- `[260, 910]` motorbike\n- `[230, 920]` motorbike\n- `[210, 930]` motorbike\n\nWait, looking at the image again, the motorbikes on the right are moving *away* from the camera?\nNo, they are facing the camera. Look at the riders' helmets and the front of the bikes.\nActually, looking at the motorbikes at `[430, 805]`, `[425, 840]`, `[435, 885]`, they are facing the camera.\nThe ones further back `[210, 930]` are also facing the camera.\nYes, they are in the far carriageway.\n\nWait, the motorbikes at the bottom `[945, 530]` etc. are they moving towards or away?\nThey are facing away from the camera.\nSo:\nBottom half = Near = moving away.\nTop half = Far = moving towards.\n\nWait, the teal car `[420, 68]` is in the top half, facing the camera.\nThe white van `[325, 350]` is in the top half, facing the camera.\nYes.\n\nOne more check on `carsAbreast`.\nNear carriageway: I see 4 lanes.\nFar carriageway: I see 4 lanes.\nMotorbikes abreast: In the rightmost group, maybe 3.\n\nTraffic state: free-flowing.\n\nFinal JSON structure check.\n`legible`: 4\n`daylight`: true\n`wetPavement`: false\n`activeRain`: false\n`occludedApproaches`: false\n`twoWheelersShareCarriagewayWithCars`: true\n`vehicles`: [...]\n`trafficState`: \"free-flowing\"\n`geometry`: { \"carsAbreastNearCarriageway\": 4, \"carsAbreastFarCarriageway\": 4, \"motorbikesAbreastWidest\": 3, \"twoWheelersFilterBetweenCars\": false }\n`standstillGaps`: []\n`unanchoredGuesses`: { \"demandVehPerHour\": 1800, \"meanSpeedKmh\": 50 }\n`notes`: \"Clear view of traffic flow in both directions.\"```json\n{\"legible\": 4,\n \"daylight\": true, \"wetPavement\": false, \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [{\"class\": \"car\", \"point\": [868, 132], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [602, 480], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [641, 684], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [945, 530], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [830, 525], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [740, 550], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [815, 620], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [725, 730], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [560, 890], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [420, 68], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"van\", \"point\": [325, 350], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [320, 450], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [450, 540], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [315, 635], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [325, 675], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"van\", \"point\": [350, 725], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [275, 760], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [250, 580], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [235, 650], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"motorbike\", \"point\": [430, 805], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [425, 840], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [435, 885], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [380, 915], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [340, 860], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [320, 895], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [290, 900], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [260, 910], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [230, 920], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [210, 930], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9}],\n \"trafficState\": \"free-flowing\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 4,\n               \"carsAbreastFarCarriageway\": 4,\n               \"motorbikesAbreastWidest\": 3,\n               \"twoWheelersFilterBetweenCars\": false},\n \"standstillGaps\": [],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 1800, \"meanSpeedKmh\": 50},\n \"notes\": \"Clear view of traffic flow in both directions.\"}\n===JSON===",
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": false,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "car",
            "point": [
              868.0,
              132.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              602.0,
              480.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              641.0,
              684.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              945.0,
              530.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              830.0,
              525.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              740.0,
              550.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              815.0,
              620.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              725.0,
              730.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              560.0,
              890.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              420.0,
              68.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "van",
            "point": [
              325.0,
              350.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              320.0,
              450.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              450.0,
              540.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              315.0,
              635.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
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              675.0
            ],
            "carriageway": "far",
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            "confidence": 0.9
          },
          {
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            "point": [
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              725.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              275.0,
              760.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              250.0,
              580.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              235.0,
              650.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "motorbike",
            "point": [
              430.0,
              805.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              425.0,
              840.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              435.0,
              885.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              380.0,
              915.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              340.0,
              860.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              320.0,
              895.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              290.0,
              900.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              260.0,
              910.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              230.0,
              920.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              210.0,
              930.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          }
        ],
        "trafficState": "free-flowing",
        "geometry": {
          "carsAbreastNearCarriageway": 4,
          "carsAbreastFarCarriageway": 4,
          "motorbikesAbreastWidest": 3,
          "twoWheelersFilterBetweenCars": false
        },
        "standstillGaps": [],
        "unanchoredGuesses": {
          "demandVehPerHour": 1800.0,
          "meanSpeedKmh": 50.0
        },
        "notes": "Clear view of traffic flow in both directions."
      },
      "repairs": []
    },
    {
      "file": "data/cctv/20260919T093332Z/56de42f611f398ec0c481288_001.jpg",
      "cameraId": "56de42f611f398ec0c481288",
      "cameraName": "Võ Văn Kiệt - Cầu Ông Lãnh 1",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:33:35 GMT",
      "receivedAtUTC": "2026-09-19T09:33:43.969079+00:00",
      "sha256": "f69cc0b1f48659ecd5c0814837acc6e63b34018412623270be449a6fc08de52f",
      "duplicateOfEarlierFrame": true,
      "captureManifest": "data/cctv/20260919T093332Z/manifest.json",
      "skipped": "Byte-identical repeat of an earlier frame; not an independent observation"
    },
    {
      "file": "data/cctv/20260919T093332Z/56de42f611f398ec0c481288_002.jpg",
      "cameraId": "56de42f611f398ec0c481288",
      "cameraName": "Võ Văn Kiệt - Cầu Ông Lãnh 1",
      "cameraTimeSource": "Sat, 19 Sep 2026 09:33:44 GMT",
      "receivedAtUTC": "2026-09-19T09:33:54.030092+00:00",
      "sha256": "1e4e6c8f41693fb344aa33155f186005a6981b270574c6badf2630f2526d57a8",
      "duplicateOfEarlierFrame": false,
      "captureManifest": "data/cctv/20260919T093332Z/manifest.json",
      "requestedAt": "2026-09-19T10:59:50.454144+00:00",
      "receivedAt": "2026-09-19T11:03:18.778892+00:00",
      "latencySeconds": 208.3,
      "finishReason": "STOP",
      "usage": {
        "promptTokenCount": 1148,
        "candidatesTokenCount": 1554,
        "totalTokenCount": 8593,
        "promptTokensDetails": [
          {
            "modality": "TEXT",
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      "rawText": "The user wants a detailed analysis of a traffic camera frame from Võ Văn Kiệt, Ho Chi Minh City.\n\n- **Legibility**: The image is clear enough to identify vehicles and their types. (4/5)\n- **Daylight**: Yes, it's daytime.\n- **Wet Pavement**: The pavement looks dark and reflective, suggesting it's wet.\n- **Active Rain**: No visible rain streaks, but the pavement is wet.\n- **Occluded Approaches**: No major structures blocking the view of the traffic stream.\n- **Two-Wheelers Share Carriageway With Cars**: Yes, motorbikes are clearly sharing the road with cars.\n\n- **Near Carriageway (closest to camera)**:\n    - White van/MPV (left): `[656, 101]`\n    - White SUV (middle): `[585, 374]`\n    - Motorbike (yellow helmet): `[725, 471]`\n    - Motorbike (purple cover): `[763, 551]`\n    - Motorbike (tan jacket): `[883, 595]`\n    - Motorbike (red helmet): `[938, 474]`\n    - Motorbike (black jacket): `[943, 374]`\n    - Motorbike (blue jacket): `[796, 728]`\n    - Motorbike (white jacket): `[600, 675]`\n    - Motorbike (black jacket): `[583, 574]`\n    - Motorbike (black jacket): `[538, 671]`\n    - Motorbike (white jacket): `[563, 732]`\n    - Motorbike (black jacket): `[643, 758]`\n    - Motorbike (black jacket): `[543, 821]`\n    - Motorbike (black jacket): `[466, 743]`\n    - Motorbike (black jacket): `[425, 798]`\n    - Motorbike (black jacket): `[381, 855]`\n    - Motorbike (black jacket): `[378, 897]`\n\n- **Far Carriageway (opposite direction)**:\n    - Black car (left): `[423, 135]`\n    - White car (left): `[443, 211]`\n    - Silver SUV (middle): `[308, 468]`\n    - Black car (middle): `[363, 545]`\n    - Black SUV (middle): `[395, 601]`\n    - Red car (middle): `[341, 674]`\n    - Black car (right): `[293, 636]`\n    - Black car (right): `[287, 724]`\n    - Blue car (right): `[308, 767]`\n    - Red car (far): `[258, 571]`\n    - White car (far): `[221, 654]`\n    - Black car (far): `[211, 705]`\n    - White car (far): `[235, 752]`\n    - White car (far): `[201, 748]`\n\n- **Traffic State**: Free-flowing. Vehicles are spaced out and moving.\n\n- **Geometry**:\n    - `carsAbreastNearCarriageway`: Looking at the lane markings, it seems to be about 4-5 lanes wide. Let's say 4.\n    - `carsAbreastFarCarriageway`: Also looks like 4-5 lanes. Let's say 4.\n    - `motorbikesAbreastWidest`: In the near carriageway, there are several motorbikes side-by-side. At most, maybe 3-4.\n    - `twoWheelersFilterBetweenCars`: Yes, they are positioned between the cars.\n\n- **Standstill Gaps**: None, traffic is moving.\n\n- **Unanchored Guesses**:\n    - `demandVehPerHour`: High, typical for HCMC. Maybe 2000-3000.\n    - `meanSpeedKmh`: Looks like 30-50 km/h.\n\n- **Notes**: Wet pavement might affect visibility of some lane markings.\n\nRefining vehicle points:\n- White van (near): `[656, 101]`\n- White SUV (near): `[585, 374]`\n- Motorbike 1 (near): `[725, 471]`\n- Motorbike 2 (near): `[763, 551]`\n- Motorbike 3 (near): `[883, 595]`\n- Motorbike 4 (near): `[938, 474]`\n- Motorbike 5 (near): `[943, 374]`\n- Motorbike 6 (near): `[796, 728]`\n- Motorbike 7 (near): `[600, 675]`\n- Motorbike 8 (near): `[583, 574]`\n- Motorbike 9 (near): `[538, 671]`\n- Motorbike 10 (near): `[563, 732]`\n- Motorbike 11 (near): `[643, 758]`\n- Motorbike 12 (near): `[543, 821]`\n- Motorbike 13 (near): `[466, 743]`\n- Motorbike 14 (near): `[425, 798]`\n- Motorbike 15 (near): `[381, 855]`\n- Motorbike 16 (near): `[378, 897]`\n\n- Black car (far): `[423, 135]`\n- White car (far): `[443, 211]`\n- Silver SUV (far): `[308, 468]`\n- Black car (far): `[363, 545]`\n- Black SUV (far): `[395, 601]`\n- Red car (far): `[341, 674]`\n- Black car (far): `[293, 636]`\n- Black car (far): `[287, 724]`\n- Blue car (far): `[308, 767]`\n- Red car (far): `[258, 571]`\n- White car (far): `[221, 654]`\n- Black car (far): `[211, 705]`\n- White car (far): `[235, 752]`\n- White car (far): `[201, 748]`\n\nWait, the \"near\" carriageway is the one with the white SUV and motorbikes. The \"far\" one is the one with the black car on the left and others moving away/towards.\nActually, looking at the image:\n- The road on the right (closest to camera) is the \"near\" carriageway.\n- The road on the left (separated by a median) is the \"far\" carriageway.\nWait, the camera is on a pole. The road with the white SUV is the one closest to the camera's perspective of the flow.\nActually, the road on the right is the one with the motorbikes and the white SUV. The road on the left is the one with the black car `[423, 135]`.\nLet's re-evaluate.\nNear carriageway: The one with the white SUV `[585, 374]` and the motorbikes.\nFar carriageway: The one with the black car `[423, 135]` and white car `[443, 211]`.\n\nWait, the white SUV `[585, 374]` is in the same direction as the motorbikes.\nThe black car `[423, 135]` is in the opposite direction.\nSo:\nNear = right side of image.\nFar = left side of image.\n\nLet's re-list:\nNear:\n- White SUV: `[585, 374]`\n- White van: `[656, 101]` (Wait, this is in the same flow as the SUV)\n- Motorbikes: all the ones on the right.\n\nFar:\n- Black car: `[423, 135]`\n- White car: `[443, 211]`\n- Silver SUV: `[308, 468]`\n- Black car: `[363, 545]`\n- Black SUV: `[395, 601]`\n- Red car: `[341, 674]`\n- Black car: `[293, 636]`\n- Black car: `[287, 724]`\n- Blue car: `[308, 767]`\n- Red car: `[258, 571]`\n- White car: `[221, 654]`\n- Black car: `[211, 705]`\n- White car: `[235, 752]`\n- White car: `[201, 748]`\n\nActually, looking at the lane markings, the white van `[656, 101]` and white SUV `[585, 374]` are in the same carriageway.\nThe black car `[423, 135]` is in the other carriageway.\nWait, the white van `[656, 101]` is very far left. Is it in the far carriageway?\nNo, it's moving in the same direction as the white SUV.\nLet's look at the median. The median is the green strip.\nEverything to the right of the green strip is the \"near\" carriageway.\nEverything to the left of the green strip is the \"far\" carriageway.\nSo:\nNear:\n- White SUV: `[585, 374]`\n- Motorbikes: all of them.\nFar:\n- White van: `[656, 101]` (Wait, it's to the left of the green strip)\n- Black car: `[423, 135]`\n- White car: `[443, 211]`\n- Silver SUV: `[308, 468]`\n- Black car: `[363, 545]`\n- Black SUV: `[395, 601]`\n- Red car: `[341, 674]`\n- Black car: `[293, 636]`\n- Black car: `[287, 724]`\n- Blue car: `[308, 767]`\n- Red car: `[258, 571]`\n- White car: `[221, 654]`\n- Black car: `[211, 705]`\n- White car: `[235, 752]`\n- White car: `[201, 748]`\n\nWait, the white van `[656, 101]` is definitely to the left of the green strip.\nLet's re-examine the image.\nThe green strip is the median.\nVehicles to the left of the median:\n- White van `[656, 101]`\n- Black car `[423, 135]`\n- White car `[443, 211]`\nThese are moving in one direction.\nVehicles to the right of the median:\n- White SUV `[585, 374]`\n- Motorbikes\n- Silver SUV `[308, 468]`\n- Black car `[363, 545]`\n- Black SUV `[395, 601]`\n- Red car `[341, 674]`\n- Black car `[293, 636]`\n- Black car `[287, 724]`\n- Blue car `[308, 767]`\n- Red car `[258, 571]`\n- White car `[221, 654]`\n- Black car `[211, 705]`\n- White car `[235, 752]`\n- White car `[201, 748]`\nWait, the silver SUV `[308, 468]` and others are moving in the same direction as the white SUV.\nSo the \"near\" carriageway is the one on the right.\nThe \"far\" carriageway is the one on the left.\n\nLet's re-verify the white van `[656, 101]`. It's to the left of the green strip. It's moving in the same direction as the black car `[423, 135]`.\nWait, the white van `[656, 101]` is facing the same way as the white SUV `[585, 374]`? No, it's facing left.\nActually, the white van `[656, 101]` is facing left. The black car `[423, 135]` is facing left.\nThe white SUV `[585, 374]` is facing right.\nSo:\nFar carriageway (left of median): White van `[656, 101]`, Black car `[423, 135]`, White car `[443, 211]`.\nNear carriageway (right of median): White SUV `[585, 374]`, Silver SUV `[308, 468]`, Black car `[363, 545]`, Black SUV `[395, 601]`, Red car `[341, 674]`, Black car `[293, 636]`, Black car `[287, 724]`, Blue car `[308, 767]`, Red car `[258, 571]`, White car `[221, 654]`, Black car `[211, 705]`, White car `[235, 752]`, White car `[201, 748]`, and all the motorbikes.\n\nWait, the white van `[656, 101]` is facing right. Look at the headlights/windshield. It's facing right.\nThe black car `[423, 135]` is facing right.\nThe white car `[443, 211]` is facing right.\nThe white SUV `[585, 374]` is facing right.\nThe motorbikes are facing right.\nThe silver SUV `[308, 468]` is facing right.\nWait, are they all moving in the same direction?\nNo, the road is divided.\nLet's look at the lanes.\nThe road on the left (far) has cars moving from right to left? No, they look like they are moving from left to right.\nThe road on the right (near) has cars moving from left to right.\nWait, if they are both moving left to right, it's a one-way road?\nVõ Văn Kiệt is a large boulevard, usually two-way.\nLet's look at the cars again.\nWhite van `[656, 101]`: facing right.\nBlack car `[423, 135]`: facing right.\nWhite car `[443, 211]`: facing right.\nWhite SUV `[585, 374]`: facing right.\nMotorbikes: facing right.\nSilver SUV `[308, 468]`: facing right.\nBlack car `[363, 545]`: facing right.\nBlack SUV `[395, 601]`: facing right.\nRed car `[341, 674]`: facing right.\nBlack car `[293, 636]`: facing right.\nBlack car `[287, 724]`: facing right.\nBlue car `[308, 767]`: facing right.\nRed car `[258, 571]`: facing right.\nWhite car `[221, 654]`: facing right.\nBlack car `[211, 705]`: facing right.\nWhite car `[235, 752]`: facing right.\nWhite car `[201, 748]`: facing right.\nThey all seem to be moving in the same direction (left to right). This might be a one-way section or the camera is only seeing one side of the boulevard.\nActually, looking at the far left, there's another road.\nLet's assume the \"near\" carriageway is the one with the motorbikes and the \"far\" one is the one to the left of the median.\nWait, the median separates two directions.\nIf the cars on the left are moving right, and the cars on the right are moving right, that's weird.\nLet's look closer at the black car `[423, 135]`. It's facing right.\nLet's look at the white SUV `[585, 374]`. It's facing right.\nMaybe it's a very wide one-way road? Or maybe I'm misjudging the direction.\nActually, the black car `[423, 135]` might be facing left. The headlights are on the left side of the car from our perspective.\nNo, the white van `[656, 101]` is definitely facing right.\nLet's just use \"near\" for the right side and \"far\" for the left side.\n\nNear:\n- White SUV `[585, 374]`\n- Motorbikes: `[725, 471]`, `[763, 551]`, `[883, 595]`, `[938, 474]`, `[943, 374]`, `[796, 728]`, `[600, 675]`, `[583, 574]`, `[538, 671]`, `[563, 732]`, `[643, 758]`, `[543, 821]`, `[466, 743]`, `[425, 798]`, `[381, 855]`, `[378, 897]`\n- Silver SUV `[308, 468]`\n- Black car `[363, 545]`\n- Black SUV `[395, 601]`\n- Red car `[341, 674]`\n- Black car `[293, 636]`\n- Black car `[287, 724]`\n- Blue car `[308, 767]`\n- Red car `[258, 571]`\n- White car `[221, 654]`\n- Black car `[211, 705]`\n- White car `[235, 752]`\n- White car `[201, 748]`\n\nFar:\n- White van `[656, 101]`\n- Black car `[423, 135]`\n- White car `[443, 211]`\n\nWait, the silver SUV `[308, 468]` and others are in the same carriageway as the white SUV `[585, 374]`.\nLet's re-check the median.\nThe green strip is the median.\nEverything to the right of it is one carriageway.\nEverything to the left of it is another.\nSo:\nNear (right of median): White SUV, all motorbikes, Silver SUV, Black car `[363, 545]`, Black SUV `[395, 601]`, Red car `[341, 674]`, Black car `[293, 636]`, Black car `[287, 724]`, Blue car `[308, 767]`, Red car `[258, 571]`, White car `[221, 654]`, Black car `[211, 705]`, White car `[235, 752]`, White car `[201, 748]`.\nFar (left of median): White van `[656, 101]`, Black car `[423, 135]`, White car `[443, 211]`.\n\nWait, the white van `[656, 101]` is a van.\nThe black car `[423, 135]` is a car.\nThe white car `[443, 211]` is a car.\n\nLet's refine the points.\nNear:\n- White SUV: `[585, 374]`\n- Motorbike 1: `[725, 471]`\n- Motorbike 2: `[763, 551]`\n- Motorbike 3: `[883, 595]`\n- Motorbike 4: `[938, 474]`\n- Motorbike 5: `[943, 374]`\n- Motorbike 6: `[796, 728]`\n- Motorbike 7: `[600, 675]`\n- Motorbike 8: `[583, 574]`\n- Motorbike 9: `[538, 671]`\n- Motorbike 10: `[563, 732]`\n- Motorbike 11: `[643, 758]`\n- Motorbike 12: `[543, 821]`\n- Motorbike 13: `[466, 743]`\n- Motorbike 14: `[425, 798]`\n- Motorbike 15: `[381, 855]`\n- Motorbike 16: `[378, 897]`\n- Silver SUV: `[308, 468]`\n- Black car: `[363, 545]`\n- Black SUV: `[395, 601]`\n- Red car: `[341, 674]`\n- Black car: `[293, 636]`\n- Black car: `[287, 724]`\n- Blue car: `[308, 767]`\n- Red car: `[258, 571]`\n- White car: `[221, 654]`\n- Black car: `[211, 705]`\n- White car: `[235, 752]`\n- White car: `[201, 748]`\n\nFar:\n- White van: `[656, 101]`\n- Black car: `[423, 135]`\n- White car: `[443, 211]`\n\nWait, the white van `[656, 101]` is actually a car/SUV. It looks like a white MPV. I'll call it a van.\nActually, it looks like a Toyota Innova or similar, which is often classed as a van/MPV.\n\nLet's double check the \"cars abreast\" count.\nNear carriageway: It looks like 4-5 lanes. Let's say 4.\nFar carriageway: Also looks like 4-5 lanes. Let's say 4.\nMotorbikes abreast: In the near carriageway, there are about 3-4 motorbikes riding side-by-side.\n\nFinal check on traffic state: free-flowing.\nWet pavement: yes.\nActive rain: no.\nDaylight: yes.\nLegible: 4.\nTwo wheelers share carriageway: yes.\nOccluded approaches: false.```json\n{\"legible\": 4,\n \"daylight\": true, \"wetPavement\": true, \"activeRain\": false,\n \"occludedApproaches\": false,\n \"twoWheelersShareCarriagewayWithCars\": true,\n \"vehicles\": [{\"class\": \"car\", \"point\": [585, 374], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [725, 471], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [763, 551], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [883, 595], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [938, 474], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [943, 374], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [796, 728], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [600, 675], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [583, 574], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [538, 671], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [563, 732], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [643, 758], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [543, 821], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [466, 743], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [425, 798], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [381, 855], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"motorbike\", \"point\": [378, 897], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [308, 468], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [363, 545], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [395, 601], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [341, 674], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [293, 636], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [287, 724], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [308, 767], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [258, 571], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [221, 654], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [211, 705], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [235, 752], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [201, 748], \"carriageway\": \"near\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"van\", \"point\": [656, 101], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.8},\n              {\"class\": \"car\", \"point\": [423, 135], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9},\n              {\"class\": \"car\", \"point\": [443, 211], \"carriageway\": \"far\", \"stopped\": false, \"confidence\": 0.9}],\n \"trafficState\": \"free-flowing\",\n \"geometry\": {\"carsAbreastNearCarriageway\": 4,\n               \"carsAbreastFarCarriageway\": 4,\n               \"motorbikesAbreastWidest\": 4,\n               \"twoWheelersFilterBetweenCars\": true},\n \"standstillGaps\": [],\n \"unanchoredGuesses\": {\"demandVehPerHour\": 2500, \"meanSpeedKmh\": 40},\n \"notes\": \"Wet pavement makes some lane markings less distinct.\"}\n===JSON===",
      "reading": {
        "legible": 4.0,
        "daylight": true,
        "wetPavement": true,
        "activeRain": false,
        "occludedApproaches": false,
        "twoWheelersShareCarriagewayWithCars": true,
        "vehicles": [
          {
            "class": "car",
            "point": [
              585.0,
              374.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              725.0,
              471.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              763.0,
              551.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              883.0,
              595.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              938.0,
              474.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              943.0,
              374.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              796.0,
              728.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              600.0,
              675.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              583.0,
              574.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              538.0,
              671.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              563.0,
              732.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              643.0,
              758.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              543.0,
              821.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              466.0,
              743.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              425.0,
              798.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              381.0,
              855.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "motorbike",
            "point": [
              378.0,
              897.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              308.0,
              468.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              363.0,
              545.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              395.0,
              601.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              341.0,
              674.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              293.0,
              636.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              287.0,
              724.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              308.0,
              767.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              258.0,
              571.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              221.0,
              654.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              211.0,
              705.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              235.0,
              752.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              201.0,
              748.0
            ],
            "carriageway": "near",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "van",
            "point": [
              656.0,
              101.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.8
          },
          {
            "class": "car",
            "point": [
              423.0,
              135.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          },
          {
            "class": "car",
            "point": [
              443.0,
              211.0
            ],
            "carriageway": "far",
            "stopped": false,
            "confidence": 0.9
          }
        ],
        "trafficState": "free-flowing",
        "geometry": {
          "carsAbreastNearCarriageway": 4,
          "carsAbreastFarCarriageway": 4,
          "motorbikesAbreastWidest": 4,
          "twoWheelersFilterBetweenCars": true
        },
        "standstillGaps": [],
        "unanchoredGuesses": {
          "demandVehPerHour": 2500.0,
          "meanSpeedKmh": 40.0
        },
        "notes": "Wet pavement makes some lane markings less distinct."
      },
      "repairs": []
    }
  ],
  "finishedAt": "2026-09-19T11:03:18.781211+00:00",
  "reparsedFrom": "data/vlm/gemma-pass-002",
  "reparsedAt": "2026-09-19T12:23:22.019321+00:00",
  "reparseNote": "Replies were not requested again. The prompt, model and stored text are those of the original pass; only this repository's parser changed.",
  "promptShaOfStoredReplies": "99ae7fb02b0e252d50a4973ef06f60039775a347c58d0330762ef10765596d8e"
}