Datasets:
video_id stringclasses 1 value | frame_index int64 0 502 ⌀ | timestamp_sec float64 0 1k ⌀ | class_label stringclasses 17 values | class_id int64 0 22 ⌀ | confidence_score float64 0.3 0.91 ⌀ | x_min float64 0 3.56k ⌀ | y_min float64 0 2.03k ⌀ | x_max float64 235 3.84k ⌀ | y_max float64 293 2.16k ⌀ | detector_name stringclasses 1 value | frame_width int64 3.84k 3.84k ⌀ | frame_height int64 2.16k 2.16k ⌀ | clip_embedding listlengths 512 512 ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
YcvECxtXoxQ | 0 | 0 | front_right_door | 14 | 0.8334 | 1,122 | 523 | 1,908 | 1,699 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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0.04306030273... |
YcvECxtXoxQ | 0 | 0 | wheel | 22 | 0.7435 | 253 | 1,231 | 2,811 | 2,079 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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0.021270... |
YcvECxtXoxQ | 0 | 0 | front_glass | 10 | 0.6226 | 1,673 | 545 | 2,779 | 939 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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0.02684020996093... |
YcvECxtXoxQ | 0 | 0 | back_left_door | 3 | 0.5028 | 523 | 520 | 1,235 | 1,567 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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... |
YcvECxtXoxQ | 0 | 0 | back_right_door | 6 | 0.4983 | 525 | 513 | 1,231 | 1,568 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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0.025... |
YcvECxtXoxQ | 0 | 0 | back_left_light | 4 | 0.4857 | 159 | 829 | 250 | 968 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.006336212158203125,
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0.02452... |
YcvECxtXoxQ | 1 | 2 | front_right_door | 14 | 0.8305 | 1,122 | 523 | 1,908 | 1,696 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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0.00872039794921875,... |
YcvECxtXoxQ | 1 | 2 | wheel | 22 | 0.7492 | 252 | 1,232 | 2,852 | 2,078 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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-0.00600433349609375,
0.0190887451171... |
YcvECxtXoxQ | 1 | 2 | front_glass | 10 | 0.7141 | 1,671 | 546 | 2,826 | 940 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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-0.02764892578125,
0.02532958984375,... |
YcvECxtXoxQ | 1 | 2 | right_mirror | 19 | 0.6869 | 3,041 | 461 | 3,231 | 721 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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-0.01390838623046875,
-0.0... |
YcvECxtXoxQ | 1 | 2 | back_left_door | 3 | 0.5043 | 523 | 520 | 1,235 | 1,567 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
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0.02960205078125,
0.050506591796875,
0.0008206367492675781,
... |
YcvECxtXoxQ | 1 | 2 | back_right_door | 6 | 0.502 | 525 | 513 | 1,231 | 1,568 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.0129852294921875,
0.037353515625,
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0.05517578125,
0.035369873046875,
0.0513916015625,
-0.0087890625,
0.0248870849609... |
YcvECxtXoxQ | 1 | 2 | back_left_light | 4 | 0.483 | 159 | 830 | 250 | 969 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.01026153564453125,
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0.03... |
YcvECxtXoxQ | 2 | 4 | front_glass | 10 | 0.9139 | 1,283 | 342 | 2,650 | 684 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.0209808349609375,
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0.04608154296875,
-0.0213470458984375,
-0.001798629... |
YcvECxtXoxQ | 2 | 4 | right_mirror | 19 | 0.7355 | 2,619 | 572 | 2,769 | 679 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.0140533447265625,
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0.0094451904296875,
-0.018524169921875,
0.0634765625,
-0.020660400390625,
-0.010688781... |
YcvECxtXoxQ | 2 | 4 | wheel | 22 | 0.692 | 810 | 1,088 | 1,037 | 1,609 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.0130157470703125,
0.039642333984375,
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-0.004215240478515625,
0.04254150390625,
0.006076812744140625,
0.030746459... |
YcvECxtXoxQ | 2 | 4 | wheel | 22 | 0.685 | 2,686 | 1,701 | 3,161 | 1,874 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.0005593299865722656,
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0.0604248046875,
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... |
YcvECxtXoxQ | 2 | 4 | front_right_light | 15 | 0.6294 | 3,030 | 790 | 3,273 | 988 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.01084136962890625,
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0.038330078125,
-0.028167724609375,
0.0430908203125,
... |
YcvECxtXoxQ | 2 | 4 | front_right_door | 14 | 0.627 | 923 | 364 | 1,232 | 1,528 | yolov8l-seg-carparts-finetuned | 3,840 | 2,160 | [
0.0036220550537109375,
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0.046539306640625,
-0.019622802734375,
0.037658... |
End of preview. Expand
in Data Studio
RAV4 Exterior Video Detection Index
YOLOv8l-seg fine-tuned on the Ultralytics carparts-seg dataset, with CLIP ViT-B/32 embeddings extracted per detection. Built for AI Spring 2026 Assignment 2.
Pipeline
- YOLOv8l-seg fine-tuned on
carparts-seg.yaml(30 epochs, AdamW) - Frames extracted at 0.5fps from RAV4 video
- Per-detection CLIP ViT-B/32 embeddings for visual similarity retrieval
- Two-stage retrieval: class label match → CLIP cosine similarity re-ranking
detections.parquet Schema
| Field | Type | Description |
|---|---|---|
| video_id | string | YouTube video ID |
| frame_index | int | Frame number (0-based) |
| timestamp_sec | float | Time offset in seconds |
| class_label | string | Detected car part class |
| class_id | int | Numeric class id |
| confidence_score | float | YOLOv8 detection confidence |
| x_min | float | Bounding box left (px) |
| y_min | float | Bounding box top (px) |
| x_max | float | Bounding box right (px) |
| y_max | float | Bounding box bottom (px) |
| detector_name | string | Model identifier |
| frame_width | int | Frame width in pixels |
| frame_height | int | Frame height in pixels |
| clip_embedding | list | 512-dim CLIP ViT-B/32 embedding (L2 norm) |
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