Dataset Versions
Versions
2023-03-03 12:54pm
v24
· 2 years ago
2023-03-03 12:07pm
v23
· 2 years ago
2023-02-28 3:20pm
v22
· 2 years ago
2022-07-18 2:02pm
v21
· 2 years ago
2022-07-18 1:52pm
v20
· 2 years ago
2022-07-18 11:24am
v19
· 2 years ago
2022-07-15 1:14pm
v18
· 2 years ago
2022-07-15 1:02pm
v17
· 2 years ago
2022-07-15 9:02am
v16
· 2 years ago
2022-07-15 8:52am
v15
· 2 years ago
2022-07-15 8:47am
v14
· 2 years ago
2022-07-15 8:44am
v13
· 2 years ago
2022-07-15 8:39am
v12
· 2 years ago
2022-07-15 8:36am
v11
· 2 years ago
2022-07-15 8:35am
v10
· 2 years ago
2022-07-01 4:17pm
v9
· 2 years ago
2022-07-01 4:13pm
v8
· 2 years ago
2022-07-01 3:58pm
v7
· 2 years ago
2022-07-01 2:52pm
v6
· 2 years ago
2022-06-30 3:43pm
v5
· 2 years ago
2022-06-29 5:13pm
v4
· 2 years ago
2022-06-29 1:16pm
v3
· 2 years ago
2022-06-29 1:07pm
v2
· 2 years ago
2022-06-22 7:50pm
v1
· 2 years ago
v21
2022-07-18 2:02pm
Generated on Jul 18, 2022
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.
882 Total Images
View All ImagesDataset Split
Train Set 97%
852Images
Valid Set 2%
20Images
Test Set 1%
10Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (black edges) in 640x640
Augmentations
Outputs per training example: 3
Hue: Between -87° and +87°
Brightness: Between -36% and +36%
Noise: Up to 5% of pixels