Dataset Versions
Versions
2024-01-24 11:46am
v32
· 10 months ago
2024-01-24 10:58am
v31
· 10 months ago
2024-01-24 9:47am
v30
· 10 months ago
2024-01-14 11:15am
v29
· 10 months ago
2024-01-14 11:07am
v28
· 10 months ago
2024-01-14 11:02am
v27
· 10 months ago
2024-01-14 11:02am
v26
· 10 months ago
2024-01-12 12:49pm
v23
· 10 months ago
2024-01-12 12:47pm
v21
· 10 months ago
2024-01-12 12:47pm
v20
· 10 months ago
2024-01-10 6:40pm
v14
· 10 months ago
2024-01-10 6:17pm
v13
· 10 months ago
2024-01-10 12:30pm
v12
· 10 months ago
2024-01-09 10:55am
v11
· 10 months ago
2024-01-09 9:45am
v10
· 10 months ago
2023-12-04 4:40pm
v9
· a year ago
2023-11-21 3:29pm
v8
· a year ago
2023-11-17 1:24pm
v7
· a year ago
2023-11-17 12:21pm
v6
· a year ago
2023-10-31 11:57am
v5
· a year ago
2023-10-26 3:59pm
v4
· a year ago
2023-10-24 4:40pm
v3
· a year ago
2023-10-24 4:36pm
v2
· a year ago
2023-10-19 3:24pm
v1
· a year ago
v12
2024-01-10 12:30pm
Generated on Jan 10, 2024
Popular Download Formats
YOLOv11
TXT annotations and YAML config used with YOLOv11.
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
3195 Total Images
View All ImagesDataset Split
Train Set 88%
2799Images
Valid Set 8%
266Images
Test Set 4%
130Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 550x550
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Noise: Up to 1.5% of pixels