Dataset Versions
Versions
2023-03-25 12:58pm
v24
· 2 years ago
2023-03-25 12:35pm
v23
· 2 years ago
2023-03-25 12:35pm
v22
· 2 years ago
2023-03-25 11:59am
v21
· 2 years ago
2023-03-24 9:45am
v20
· 2 years ago
2023-03-23 9:51pm
v19
· 2 years ago
2023-03-23 9:50pm
v18
· 2 years ago
2023-03-23 5:02pm
v17
· 2 years ago
2023-03-23 5:01pm
v16
· 2 years ago
2023-03-23 4:16pm
v15
· 2 years ago
2023-03-23 4:13pm
v14
· 2 years ago
2023-03-23 3:51pm
v13
· 2 years ago
2023-03-23 3:51pm
v12
· 2 years ago
2023-03-23 3:51pm
v11
· 2 years ago
2023-03-23 3:50pm
v10
· 2 years ago
2023-03-23 3:44pm
v9
· 2 years ago
2023-03-23 10:10am
v8
· 2 years ago
2023-03-23 3:19am
v7
· 2 years ago
2023-03-23 3:19am
v6
· 2 years ago
2023-03-22 11:53pm
v5
· 2 years ago
2023-03-22 11:45pm
v4
· 2 years ago
2023-03-22 11:30pm
v3
· 2 years ago
2023-03-22 11:26pm
v2
· 2 years ago
2023-03-22 11:18pm
v1
· 2 years ago
v3
2023-03-22 11:30pm
Generated on Mar 22, 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.
1797 Total Images
View All Images
Dataset Split
Train Set 91%
1629Images
Valid Set 5%
85Images
Test Set 5%
83Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Augmentations
Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Shear: ±15° Horizontal, ±15° Vertical
Exposure: Between -25% and +25%
Cutout: 3 boxes with 10% size each
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise