Dataset Versions
Versions
2024-01-07 8:19pm
v25
· a year ago
2024-01-05 8:17pm
v24
· a year ago
2024-01-05 8:15pm
v23
· a year ago
2024-01-05 12:27am
v22
· a year ago
2024-01-05 12:26am
v21
· a year ago
2024-01-05 12:25am
v20
· a year ago
2024-01-05 12:25am
v19
· a year ago
2024-01-05 12:24am
v18
· a year ago
2024-01-05 12:24am
v17
· a year ago
2024-01-05 12:23am
v16
· a year ago
2024-01-05 12:22am
v15
· a year ago
2024-01-05 12:21am
v14
· a year ago
2024-01-05 12:20am
v13
· a year ago
2024-01-05 12:20am
v12
· a year ago
2024-01-05 12:18am
v11
· a year ago
2024-01-05 12:18am
v10
· a year ago
2024-01-05 12:17am
v9
· a year ago
2024-01-05 12:16am
v8
· a year ago
2024-01-05 12:14am
v7
· a year ago
2024-01-05 12:14am
v6
· a year ago
2024-01-05 12:11am
v5
· a year ago
2024-01-05 12:09am
v4
· a year ago
2024-01-05 12:04am
v3
· a year ago
2024-01-04 11:41pm
v2
· a year ago
2023-12-21 1:23pm
v1
· a year ago
v25
2024-01-07 8:19pm
Generated on Jan 7, 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.
223 Total Images
View All ImagesDataset Split
Train Set 70%
156Images
Valid Set 20%
45Images
Test Set 10%
22Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (reflect edges) in 640x640
Augmentations
Outputs per training example: 3
Rotation: Between -10° and +10°
Shear: ±10° Horizontal, ±10° Vertical
Brightness: Between -20% and +20%
Blur: Up to 2.5px
Noise: Up to 1.41% of pixels