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@@ -58,3 +58,140 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+jsons/P10_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P10_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P10_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P10_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P11_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P11_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P11_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P11_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P12_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P12_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P12_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P12_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P13_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P13_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P13_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P13_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P14_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P14_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P14_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P14_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P15_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P15_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P16_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P16_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P16_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P16_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P17_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P17_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P17_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P17_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P18_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P18_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P18_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P18_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P19_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P19_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P19_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P19_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P1_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P1_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P1_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P1_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P20_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P20_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P20_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P20_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P21_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P21_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P21_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P21_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P22_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P22_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P22_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P22_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P23_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P23_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P23_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P23_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P24_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P24_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P24_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P24_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P25_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P25_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P25_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P25_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P26_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P26_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P26_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P26_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P27_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P27_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P27_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P27_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P28_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P28_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P28_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P28_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P29_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P29_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P29_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P29_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P2_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P2_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P2_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P2_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P30_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P30_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P30_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P30_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P31_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P31_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P31_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P32_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P32_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P32_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P32_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P33_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P33_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P33_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P33_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P34_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P34_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P34_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P34_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P35_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P35_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P35_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P35_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P3_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P3_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P3_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P3_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P4_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P4_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P4_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P4_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P5_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P5_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P5_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P5_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P6_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P6_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P6_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P6_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P7_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P7_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P7_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P7_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P8_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P8_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P8_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P8_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P9_sunfacing/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P9_sunfacing/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P9_sunoccluded/eye0_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text
+jsons/P9_sunoccluded/eye1_contours_reviewed.json filter=lfs diff=lfs merge=lfs -text

IRdata.csv

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+participant,sunfacing_ir,sunoccluded_ir
+P1,108.1,62.2
+P2,9.8,5.9
+P3,27.5,16.5
+P4,341.7,62.7
+P5,204.2,101.9
+P6,303.8,81.9
+P7,309.2,79.0
+P8,110.9,42.3
+P9,32.4,22.8
+P10,255.5,21.7
+P11,322.1,73.1
+P12,38.2,21.4
+P13,61.9,45.9
+P14,107.3,71.3
+P15,198.1,69.5
+P16,377.9,81.9
+P17,146.4,56.7
+P18,297.1,37.0
+P19,271.0,71.4
+P20,262.9,112.3
+P21,203.4,97.8
+P22,226.3,81.1
+P23,111.4,58.5
+P24,412.6,101.5
+P25,281.4,92.1
+P26,184.9,67.6
+P27,145.2,50.1
+P28,305.7,84.6
+P29,280.0,87.9
+P30,275.8,88.8
+P31,273.7,85.9
+P32,323.1,80.1
+P33,346.6,68.9
+P34,245.7,65.3
+P35,298.4,78.2

README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+  - other
+tags:
+  - eye-tracking
+  - pupil-segmentation
+  - ambient-light
+  - infrared
+  - pupil
+  - wearable
+size_categories:
+  - 1M<n<10M
+---
+
+# AmbientEye Dataset
+
+**AmbientEye** is a large-scale eye-tracking dataset collected exclusively outdoors under natural ambient sunlight — without any active infrared illuminator. It is designed to benchmark pupil segmentation methods under varying, uncontrolled NIR irradiance conditions that arise in real-world outdoor use.
+
+---
+
+## Overview
+
+| Property | Value |
+|---|---|
+| Participants | 35 |
+| Sessions | 70 (2 per participant) |
+| Total frames | 2,625,169 |
+| Conditions | `sunfacing`, `sunoccluded` |
+| Camera resolution | 400 × 400 px (monochrome IR) |
+| Frame rate | 120 fps |
+| Cameras per session | 2 (medial `eye0`, lateral `eye1`) |
+| Calibration trials | 80 per session |
+| IR illumination | **None** — ambient sunlight only |
+
+---
+
+## Conditions
+
+Each participant completed two sessions in different lighting orientations:
+
+| Condition | Description | IR irradiance (mean ± range) |
+|---|---|---|
+| `sunfacing` | Participant faces toward the sun (higher NIR) | 220 µW/cm² (9.8 – 412.6) |
+| `sunoccluded` | Participant faces away from the sun (lower NIR) | 66.5 µW/cm² (5.9 – 112.3) |
+
+The large irradiance range across participants reflects real-world variability in sun angle, cloud cover, and participant orientation.
+
+---
+
+## Participants
+
+35 participants (19 male, 16 female), ages 17–34 (mean 23.3).
+
+| Ethnicity | Count |
+|---|---|
+| Asian | 20 |
+| White | 8 |
+| Black or African American | 4 |
+| Middle Eastern or North African | 1 |
+| Hispanic, Latino, or Spanish | 1 |
+| Eastern African | 1 |
+
+3 participants wore makeup. Full demographics are in `participant.csv`.
+
+---
+
+## Dataset Structure
+
+```
+AmbientEyeDataset/
+├── video/                              # Raw IR video files
+│   └── {PID}_{condition}/              # e.g. P1_sunfacing, P1_sunoccluded
+│       ├── eye0.mp4                    # Medial camera (nose side), 400×400 px, 120 fps
+│       └── eye1.mp4                    # Lateral camera (ear side), 400×400 px, 120 fps
+├── frames/                             # Extracted video frames (JPEG)
+│   └── {PID}_{condition}/
+│       ├── eye0/
+│       │   ├── frame_00000.jpg
+│       │   └── ...
+│       └── eye1/
+│           ├── frame_00000.jpg
+│           └── ...
+├── jsons/                              # Human-reviewed SAM2 segmentation contours
+│   └── {PID}_{condition}/
+│       ├── eye0_contours_reviewed.json
+│       └── eye1_contours_reviewed.json
+├── meta/                               # Session timing and calibration metadata
+│   └── {PID}_{condition}/
+│       ├── calibration_log.json        # 80-trial stimulus targets + timestamps
+│       └── info.player.json            # Recording timing (duration, start times)
+├── sample_contour/                     # Sample videos with contour overlays
+│   └── {PID}_{condition}/
+│       ├── eye0.mp4
+│       └── eye1.mp4
+├── participant.csv                     # Participant demographics (N=35)
+├── IRdata.csv                          # Per-session NIR irradiance measurements
+├── session_recording_info.csv          # Per-session date, time, weather, temperature
+└── solar_position_reference.md         # Solar azimuth/altitude tables per recording date
+```
+
+---
+
+## File Descriptions
+
+### `video/{PID}_{condition}/eye0.mp4` / `eye1.mp4`
+400×400 px monochrome IR video at 120 fps from two OV6211 cameras embedded in the Xreal Air 2 Glasses.
+- `eye0` — medial camera (nose side)
+- `eye1` — lateral camera (ear side)
+
+Captured under natural ambient illumination only. No active IR LED is used.
+
+### `frames/{PID}_{condition}/eye{0,1}/frame_XXXXX.jpg`
+Individual frames extracted from the corresponding `eye0.mp4` / `eye1.mp4` video, zero-padded five-digit frame index. Provided for workflows that do not require video decoding.
+
+### `jsons/{PID}_{condition}/eye0_contours_reviewed.json` / `eye1_contours_reviewed.json`
+SAM2 pupil segmentation contours, reviewed and corrected by human annotators. Each file contains:
+```json
+{
+  "video": "eye0.mp4",
+  "fps": 120.0,
+  "width": 400,
+  "height": 400,
+  "frames": [
+    {
+      "frame": 0,
+      "contours": [
+        { "points": [[x, y], ...], "area": 1234.5 }
+      ]
+    },
+    ...
+  ]
+}
+```
+
+### `meta/{PID}_{condition}/calibration_log.json`
+80 stimulus trials per session. Each entry records the screen position `(x, y)` of the shrinking-circle stimulus and the Pupil-synchronized timestamp of the participant's keypress response. Used for aligning eye video frames to known viewing directions.
+```json
+{
+  "trials": [
+    { "trial": 1, "pos": [683, 606], "click_ts": 165097.33 },
+    ...
+  ]
+}
+```
+
+### `meta/{PID}_{condition}/info.player.json`
+Recording timing fields only:
+```json
+{
+  "duration_s": 171.79,
+  "start_time_synced_s": 165082.55,
+  "start_time_system_s": 1776402507.93
+}
+```
+- `start_time_synced_s` — Pupil-synchronized clock at recording start
+- `start_time_system_s` — Unix timestamp at recording start
+- `duration_s` — total recording duration in seconds
+
+### `participant.csv`
+Participant demographics: ID (P1–P35), gender, age, ethnicity, country, makeup.
+
+### `IRdata.csv`
+Measured NIR irradiance (µW/cm²) per participant for each condition (`sunfacing_ir`, `sunoccluded_ir`), confirming ambient light levels at recording time.
+
+### `session_recording_info.csv`
+Per-session metadata: recording date, anonymized start/end times, duration (minutes), weather condition, and temperature (°C / °F).
+
+### `solar_position_reference.md`
+Hourly solar azimuth and altitude tables for each recording date, with per-session estimates linearly interpolated to each session's start time. Can be joined to `session_recording_info.csv` on `Participant` + `Session`.
+
+### `sample_contour/{PID}_{condition}/eye{0,1}.mp4`
+Short sample videos with SAM2 contour overlays rendered on the raw IR frames, provided for quick visual quality inspection.
+
+---
+
+## Usage
+
+```python
+import json, cv2
+
+session = "P1_sunfacing"
+
+# Load contours
+with open(f"jsons/{session}/eye0_contours_reviewed.json") as f:
+    contours = json.load(f)
+
+# Load video
+cap = cv2.VideoCapture(f"video/{session}/eye0.mp4")
+
+for frame_data in contours["frames"]:
+    cap.set(cv2.CAP_PROP_POS_FRAMES, frame_data["frame"])
+    ret, img = cap.read()
+    if not ret:
+        break
+    for c in frame_data["contours"]:
+        pts = [[int(p[0]), int(p[1])] for p in c["points"]]
+        # draw / process contour ...
+
+cap.release()
+```
+
+---
+
+## License
+
+This dataset is released under the [Creative Commons Attribution Non-Commercial 4.0 (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/) license.
+
+You are free to share and adapt the material for non-commercial purposes, provided appropriate credit is given.
+
+---
+
+## Citation
+
+If you use AmbientEye in your research, please cite:
+
+```bibtex
+@dataset{ambienteye2026,
+  title   = {AmbientEye: A Dataset for Pupil Segmentation under Natural Ambient Infrared Illumination},
+  year    = {2026},
+  url     = {https://huggingface.co/datasets/migHug/AmbientEye},
+  license = {CC BY-NC 4.0}
+}
+```

extract_frames.py

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+"""
+Extract all frames from video/ as JPEG files into frames/.
+Run once; idempotent (skips sessions already fully extracted).
+
+Usage: python extract_frames.py
+"""
+import cv2
+from pathlib import Path
+from config import VIDEO_DIR, FRAMES_DIR
+
+sessions = sorted(d for d in VIDEO_DIR.iterdir() if d.is_dir())
+print(f"{len(sessions)} sessions found")
+
+for si, sess_dir in enumerate(sessions):
+    for eye in (0, 1):
+        src = sess_dir / f"eye{eye}.mp4"
+        if not src.exists():
+            print(f"[SKIP] {sess_dir.name}/eye{eye} — no mp4")
+            continue
+
+        out_dir = FRAMES_DIR / sess_dir.name / f"eye{eye}"
+
+        cap = cv2.VideoCapture(str(src))
+        total = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+
+        if out_dir.exists() and len(list(out_dir.glob("frame_*.jpg"))) == total:
+            print(f"[DONE] ({si+1}/{len(sessions)}) {sess_dir.name}/eye{eye} — already extracted")
+            cap.release()
+            continue
+
+        out_dir.mkdir(parents=True, exist_ok=True)
+        fi = 0
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                break
+            cv2.imwrite(str(out_dir / f"frame_{fi:05d}.jpg"), frame,
+                        [cv2.IMWRITE_JPEG_QUALITY, 95])
+            fi += 1
+        cap.release()
+        print(f"[OK] ({si+1}/{len(sessions)}) {sess_dir.name}/eye{eye} — {fi} frames")
+
+print("Done")

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