Dataset Versions
Versions
2024-11-11 5:24am
v39
· 15 days ago
2024-11-05 10:33pm
v38
· 20 days ago
2024-11-05 2:02am
v37
· 21 days ago
2024-11-04 7:33am
v36
· 22 days ago
2024-11-04 12:24am
v35
· 22 days ago
2024-11-03 11:45pm
v34
· 22 days ago
2024-11-03 5:31am
v33
· 23 days ago
2024-11-02 6:18am
v32
· 24 days ago
2024-10-09 6:23pm
v31
· 2 months ago
2024-10-09 6:20pm
v30
· 2 months ago
2024-10-09 4:39am
v29
· 2 months ago
2024-10-09 4:11am
v28
· 2 months ago
2024-10-09 3:49am
v27
· 2 months ago
2024-10-09 3:47am
v26
· 2 months ago
2024-10-09 3:09am
v25
· 2 months ago
2024-10-07 3:33am
v24
· 2 months ago
2024-10-07 3:24am
v23
· 2 months ago
2024-10-07 3:09am
v22
· 2 months ago
2024-10-07 3:08am
v21
· 2 months ago
2024-10-07 12:36am
v20
· 2 months ago
2024-10-07 12:34am
v19
· 2 months ago
2024-10-07 12:17am
v18
· 2 months ago
2024-10-07 12:12am
v17
· 2 months ago
2024-10-06 10:12pm
v16
· 2 months ago
v35
2024-11-04 12:24am
Generated on Nov 4, 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.
1345 Total Images
View All Images
Dataset Split
Train Set 92%
1242Images
Valid Set 8%
103Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Rotation: Between -15° and +15°
Saturation: Between -25% and +25%