Dataset Versions
Versions
2022-05-12 4:08pm
v30
· 3 years ago
2022-05-12 4:06pm
v29
· 3 years ago
2022-05-11 9:37pm
v28
· 3 years ago
Cutout Set
v27
· 3 years ago
Shear Set
v26
· 3 years ago
Rotation Set
v25
· 3 years ago
Brightness Set
v24
· 3 years ago
Blur Set
v23
· 3 years ago
Noise Set
v22
· 3 years ago
Base Set
v21
· 3 years ago
2022-05-10 2:06pm
v20
· 3 years ago
2022-05-06 12:01am
v19
· 3 years ago
2022-05-05 11:58pm
v18
· 3 years ago
2022-05-05 11:55pm
v17
· 3 years ago
2022-05-05 11:17pm
v16
· 3 years ago
2022-05-05 8:51am
v15
· 3 years ago
2022-05-03 11:58pm
v14
· 3 years ago
2022-05-03 11:56pm
v13
· 3 years ago
2022-04-28 10:54am
v12
· 3 years ago
2022-04-28 9:47am
v11
· 3 years ago
2022-04-28 9:41am
v10
· 3 years ago
2022-04-27 7:34pm
v9
· 3 years ago
2022-04-27 7:32pm
v8
· 3 years ago
2022-04-08 10:33pm
v7
· 3 years ago
2022-04-05 8:43am
v6
· 3 years ago
2022-04-05 8:42am
v5
· 3 years ago
2022-04-05 8:40am
v4
· 3 years ago
2022-03-26 6:16pm
v1
· 3 years ago
v13
2022-05-03 11:56pm
Generated on May 3, 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.
1441 Total Images
View All ImagesDataset Split
Train Set 98%
1413Images
Valid Set %
0Images
Test Set 2%
28Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 416x416
Grayscale: Applied
Augmentations
Outputs per training example: 3
Brightness: Between -25% and +25%
Blur: Up to 2px
Noise: Up to 5% of pixels
Cutout: 5 boxes with 5% size each