Dataset Versions
Versions
2024-07-02 5:51am
v25
· 4 months ago
2024-07-02 5:51am
v24
· 4 months ago
2024-07-02 5:50am
v23
· 4 months ago
2024-07-02 5:50am
v22
· 4 months ago
2024-07-02 5:50am
v21
· 4 months ago
2024-07-02 5:49am
v20
· 4 months ago
2024-07-02 5:49am
v19
· 4 months ago
2024-07-02 5:49am
v18
· 4 months ago
2024-07-02 5:49am
v17
· 4 months ago
2024-07-02 5:48am
v16
· 4 months ago
2024-07-02 5:48am
v15
· 4 months ago
2024-07-02 5:48am
v14
· 4 months ago
2024-07-02 5:48am
v13
· 4 months ago
2024-07-02 5:47am
v12
· 4 months ago
2024-07-02 5:47am
v11
· 4 months ago
2024-07-02 5:47am
v10
· 4 months ago
2024-07-02 5:46am
v9
· 4 months ago
2024-07-02 5:46am
v8
· 4 months ago
2024-07-02 5:46am
v7
· 4 months ago
2024-07-02 5:46am
v6
· 4 months ago
2024-07-02 5:46am
v5
· 4 months ago
2024-07-02 5:45am
v4
· 4 months ago
2024-07-02 5:45am
v3
· 4 months ago
2024-07-02 5:44am
v2
· 4 months ago
2024-07-02 5:44am
v1
· 4 months ago
v17
2024-07-02 5:49am
Generated on Jul 2, 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.
71 Total Images
View All Images
Dataset Split
Train Set 72%
51Images
Valid Set 18%
13Images
Test Set 10%
7Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 960x960
Augmentations
Outputs per training example: 3
Grayscale: Apply to 10% of images