Dataset Versions
Versions
2023-04-16 2:40pm
v28
· 2 years ago
2023-04-16 2:03pm
v27
· 2 years ago
2023-04-15 2:59pm
v26
· 2 years ago
2023-04-15 2:33pm
v25
· 2 years ago
2023-04-15 1:49pm
v24
· 2 years ago
2023-04-14 11:00am
v23
· 2 years ago
2023-03-24 3:17pm
v22
· 2 years ago
2023-03-23 10:24pm
v20
· 2 years ago
2023-03-20 12:45pm
v17
· 2 years ago
2023-03-19 7:34pm
v15
· 2 years ago
2023-03-19 5:24pm
v13
· 2 years ago
2023-03-13 10:50am
v9
· 2 years ago
512x512_size
v8
· 2 years ago
v6
v6
· 2 years ago
2023-03-11 1:15pm
v5
· 2 years ago
2023-03-10 8:01am
v1
· 2 years ago
v13
2023-03-19 5:24pm
Generated on Mar 19, 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.
1917 Total Images
View All Images
Dataset Split
Train Set 93%
1788Images
Valid Set 3%
60Images
Test Set 4%
69Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (reflect edges) in 416x416
Modify Classes: 9 remapped, 0 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Shear: ±15° Horizontal, ±15° Vertical
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Blur: Up to 0.5px
Noise: Up to 1% of pixels
Cutout: 3 boxes with 16% size each