file_name stringlengths 23 23 | image unknown | video_id stringclasses 1
value | frame_number int64 0 31.7k | timestamp float64 0 529 | road_type stringclasses 2
values | weather stringclasses 2
values | scene stringclasses 2
values | has_car int64 1 1 | has_motorcycle int64 0 1 | has_truck int64 0 1 | has_bus int64 0 1 | has_pedestrian int64 0 1 | has_bicycle int64 0 0 | has_traffic_light int64 0 1 | has_traffic_sign int64 0 1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
GX012073_frame_0000.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 0 | 0 | rural | clear | other | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
GX012073_frame_0001.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 299 | 4.988317 | rural | clear | highway | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
GX012073_frame_0002.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 598 | 9.976633 | highway | clear | other | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
GX012073_frame_0003.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 897 | 14.96495 | rural | clear | other | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
GX012073_frame_0004.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 1,196 | 19.953267 | highway | clear | other | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
GX012073_frame_0005.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 1,495 | 24.941583 | rural | clear | other | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
GX012073_frame_0006.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 1,794 | 29.9299 | highway | clear | other | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
GX012073_frame_0007.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 2,093 | 34.918217 | highway | clear | other | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
GX012073_frame_0008.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 2,392 | 39.906533 | highway | clear | other | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 |
GX012073_frame_0009.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | GX012073 | 2,691 | 44.89485 | highway | clear | other | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
End of preview. Expand in Data Studio
DriveThruThailand Labeled Dataset
Dataset Description
A collection of 107 screenshots from DriveThruThailand videos with labels.
Features
Each image includes the following features:
- file_name: File name
- image_path: Path to the image within the dataset
- video_id: Source video ID
- frame_number: Frame number in the source video
- timestamp: Timestamp in seconds
- road_type: Road type classification (highway, urban)
- weather: Weather condition (clear, cloudy)
- scene: Scene type (city, countryside)
File Structure
/images/: Contains all the imagesmetadata.csv: Contains metadata for all images
Usage
This dataset can be used with Hugging Face's datasets library:
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("notewee/drivethruthailand-labeled")
# Access metadata
metadata = pd.read_csv(dataset["metadata.csv"])
# Access images
image_paths = metadata["image_path"].tolist()
License
CC-BY-4.0
- Downloads last month
- 109