Dataset Versions
Versions
2024-10-29 11:39pm
v25
· 2 months ago
2024-10-29 3:43pm
v24
· 2 months ago
2024-10-29 3:42pm
v23
· 2 months ago
2024-10-28 11:59pm
v22
· 2 months ago
2024-10-28 11:08pm
v21
· 2 months ago
2024-10-28 3:12pm
v20
· 2 months ago
2024-10-27 11:08pm
v19
· 2 months ago
2024-10-27 11:02pm
v18
· 2 months ago
2024-10-27 10:26pm
v17
· 2 months ago
2024-10-27 7:15pm
v16
· 2 months ago
2024-10-27 3:52pm
v15
· 2 months ago
2024-10-27 3:49pm
v14
· 2 months ago
2024-10-27 2:32pm
v13
· 2 months ago
2024-10-27 12:51pm
v12
· 2 months ago
2024-10-26 6:58pm
v11
· 2 months ago
2024-10-26 6:11pm
v10
· 2 months ago
2024-10-24 3:37pm
v9
· 2 months ago
2024-10-23 3:38pm
v8
· 2 months ago
2024-10-22 3:58pm
v7
· 2 months ago
2024-10-21 3:45pm
v6
· 2 months ago
2024-10-12 6:07pm
v5
· 2 months ago
2024-10-12 5:12pm
v4
· 2 months ago
2024-10-12 5:11pm
v3
· 2 months ago
2024-10-12 2:58pm
v2
· 2 months ago
2024-09-28 1:11am
v1
· 3 months ago
v7
2024-10-22 3:58pm
Generated on Oct 22, 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.
636 Total Images
View All ImagesDataset Split
Train Set 87%
555Images
Valid Set 8%
54Images
Test Set 4%
27Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Grayscale: Apply to 15% of images
Saturation: Between -20% and +20%
Noise: Up to 0.3% of pixels