CowsDetection Computer Vision Dataset
Popular Download Formats
YOLO26
TXT annotations and YAML config used with YOLO26.
YOLOv12
TXT annotations and YAML config used with YOLOv12.
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.
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Some images failed during generation
363 images (46%) failed to generate. The result of this training run may be different from others. We recommend regenerating the version and contact support if the issue persists.
764 Total Images
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Dataset Split
Train Set 97%
741Images
Valid Set 2%
12Images
Test Set 1%
11Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Cutout: 4 boxes with 10% size each
Mosaic: Applied
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -31% and +31%
Bounding Box: Noise: Up to 5% of pixels