Dataset Versions
v9
2024-12-08 6:44pm
Generated on Dec 8, 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
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6968 Total Images
View All Images
Dataset Split
Train Set 86%
5976Images
Valid Set 9%
608Images
Test Set 6%
384Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 24-70% Horizontal Region, 25-71% Vertical Region
Dynamic Crop: Class: keisha
Resize: Stretch to 640x640
Grayscale: Applied
Tile: 2 rows x 2 columns
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±12° Horizontal, ±16° Vertical
Grayscale: Apply to 17% of images
Brightness: Between -24% and +24%
Exposure: Between -14% and +14%
Blur: Up to 2.5px
Noise: Up to 1.83% of pixels
Cutout: 3 boxes with 10% size each
Bounding Box: Blur: Up to 2.5px