Dataset Versions
v2
2023-04-27 12:48pm
Generated on Apr 27, 2023
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.
8250 Total Images
View All Images
Dataset Split
Train Set 93%
7663Images
Valid Set 5%
424Images
Test Set 2%
163Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 320x320
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Tile: 2 rows x 2 columns
Modify Classes: 5 remapped, 0 dropped
Filter Null: Require at least 50% of images to contain annotations.
Augmentations
Outputs per training example: 3
Flip: Horizontal
Rotation: Between -5° and +5°
Shear: ±4° Horizontal, ±5° Vertical
Grayscale: Apply to 25% of images
Saturation: Between -25% and +25%
Brightness: Between -16% and +16%
Exposure: Between -10% and +10%
Blur: Up to 1.5px
Noise: Up to 2% of pixels
Cutout: 3 boxes with 10% size each
Bounding Box: Blur: Up to 1.75px