Dataset Versions
Versions
2024-01-12 9:27am
v26
· a year ago
2024-01-11 1:41pm
v25
· a year ago
2024-01-11 1:39pm
v24
· a year ago
2024-01-11 1:06pm
v23
· a year ago
2024-01-11 12:28pm
v22
· a year ago
2024-01-11 12:23pm
v21
· a year ago
2024-01-11 12:20pm
v20
· a year ago
2024-01-11 12:19pm
v19
· a year ago
2024-01-11 12:18pm
v18
· a year ago
2024-01-11 9:01am
v17
· a year ago
2024-01-11 8:45am
v16
· a year ago
2024-01-11 8:32am
v15
· a year ago
2023-12-08 10:02am
v14
· a year ago
2023-11-29 3:32pm
v13
· a year ago
2023-11-29 3:27pm
v12
· a year ago
2023-11-29 3:26pm
v11
· a year ago
2023-11-29 3:13pm
v10
· a year ago
2023-11-29 3:06pm
v9
· a year ago
2023-11-29 12:02pm
v8
· a year ago
2023-11-29 11:21am
v7
· a year ago
2023-11-29 11:02am
v6
· a year ago
2023-11-29 10:59am
v5
· a year ago
2023-11-29 10:57am
v4
· a year ago
2023-11-29 10:56am
v3
· a year ago
2023-11-29 10:55am
v2
· a year ago
2023-11-29 10:54am
v1
· a year ago
v7
2023-11-29 11:21am
Generated on Nov 29, 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.
10 Total Images
View All ImagesDataset Split
Train Set 60%
6Images
Valid Set 30%
3Images
Test Set 10%
1Images
Preprocessing
No preprocessing steps were applied.
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Brightness: Between -25% and +25%