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video_id
large_stringclasses
1 value
frame_index
int64
0
558
timestamp_sec
int64
0
2.79k
class_label
large_stringclasses
13 values
bounding_box
listlengths
4
4
confidence_score
float64
0.25
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YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

Video Detection Index

The dataset contains extracting object part detections from a car exterior video. The detection result are stored in a structured Parquet file, we store all detected car parts in a Parquet table so that we can look up the timestamps where each part appears in the video.

Detector

We use a YOLOv8 model trained on a car parts dataset to detect specific exterior components such as the front bumper, hood, mirrors, and wheels.

Sampling

Frames are sampled every 5 seconds and processed with a YOLOv8 model. Frames are sampled every 5 seconds every 5 seconds. timestamp_sec = frame_index × 5

Data Schema

Each row in the Parquet file corresponds to a single detection.

Column name Type Description
video_id string YouTube video identifier.
frame_index int Index of the sampled frame.
timestamp_sec int Time position in seconds.
class_label string Detected car exterior component (front_bumper, hood, mirror).
bounding_box list[float] Bounding box in pixel coordinates: [x_min, y_min, x_max, y_max].
confidence_score float Detector confidence score for the bounding box.

Usage

We detect the car part in the query image and use the label to look up the timestamps where this part appears in the video.

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