Dataset Versions
Versions
2024-12-10 11:17am
v23
· 12 days ago
2024-12-10 10:29am
v22
· 12 days ago
2024-12-10 10:18am
v21
· 12 days ago
2024-12-10 9:25am
v20
· 12 days ago
2024-12-10 8:44am
v19
· 12 days ago
2024-12-09 11:33pm
v18
· 12 days ago
2024-12-09 11:07pm
v17
· 12 days ago
2024-12-09 10:05pm
v16
· 13 days ago
2024-12-09 9:45pm
v15
· 13 days ago
2024-12-09 9:15pm
v14
· 13 days ago
2024-12-09 8:58pm
v13
· 13 days ago
2024-12-09 8:43pm
v12
· 13 days ago
2024-12-09 8:20pm
v11
· 13 days ago
2024-12-09 8:18pm
v9
· 13 days ago
2024-12-09 8:16pm
v8
· 13 days ago
2024-12-09 8:16pm
v7
· 13 days ago
2024-12-09 8:15pm
v6
· 13 days ago
2024-12-09 7:11pm
v5
· 13 days ago
2024-12-09 6:25pm
v4
· 13 days ago
2024-12-05 4:19pm
v3
· 17 days ago
2024-11-28 4:10pm
v1
· 24 days ago
v23
2024-12-10 11:17am
Generated on Dec 10, 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.
315 Total Images
View All Images
Dataset Split
Train Set 90%
282Images
Valid Set 10%
33Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (black edges) in 1024x1024
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require at least 60% of images to contain annotations.
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -15° and +15°
Hue: Between -10° and +10°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%