Dataset Versions
Versions
2023-07-31 1:17pm
v30
· a year ago
2023-07-31 11:51am
v29
· a year ago
2023-07-31 11:44am
v28
· a year ago
2023-07-31 11:44am
v27
· a year ago
2023-07-31 11:43am
v26
· a year ago
2023-07-31 11:41am
v25
· a year ago
2023-07-31 11:40am
v24
· a year ago
2023-07-31 11:39am
v23
· a year ago
2023-07-31 11:39am
v22
· a year ago
2023-07-31 11:38am
v21
· a year ago
2023-07-31 11:34am
v20
· a year ago
2023-07-31 11:27am
v19
· a year ago
2023-07-31 11:27am
v18
· a year ago
2023-07-31 11:26am
v17
· a year ago
2023-07-31 11:25am
v16
· a year ago
2023-07-31 11:25am
v15
· a year ago
2023-07-31 11:24am
v14
· a year ago
2023-07-31 10:54am
v13
· a year ago
2023-07-31 10:53am
v12
· a year ago
2023-07-31 10:53am
v11
· a year ago
2023-07-31 10:52am
v10
· a year ago
2023-07-31 10:51am
v9
· a year ago
2023-07-31 10:50am
v8
· a year ago
2023-07-31 10:49am
v7
· a year ago
2023-07-31 10:48am
v6
· a year ago
2023-07-31 10:47am
v5
· a year ago
2023-07-31 10:46am
v4
· a year ago
2023-07-31 10:45am
v3
· a year ago
2023-07-31 10:45am
v2
· a year ago
2023-07-31 10:44am
v1
· a year ago
v19
2023-07-31 11:27am
Generated on Jul 31, 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.
2 Total Images
View All Images
Dataset Split
Train Set 100%
2Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Augmentations
Outputs per training example: 2
Noise: Up to 4% of pixels