Dataset Versions
Versions
2024-03-28 3:56pm
v72
· 8 months ago
2024-03-28 3:54pm
v71
· 8 months ago
2024-03-28 3:53pm
v70
· 8 months ago
2024-03-26 1:02pm
v69
· 8 months ago
2024-03-26 12:51pm
v68
· 8 months ago
2024-03-26 10:40am
v66
· 8 months ago
2024-03-26 10:35am
v65
· 8 months ago
2024-03-26 10:31am
v64
· 8 months ago
2024-03-25 8:57pm
v62
· 8 months ago
2024-03-25 8:55pm
v61
· 8 months ago
2024-03-25 8:55pm
v60
· 8 months ago
2024-03-25 8:52pm
v59
· 8 months ago
2024-03-25 1:12pm
v48
· 8 months ago
2024-03-25 1:10pm
v47
· 8 months ago
2024-03-25 1:09pm
v46
· 8 months ago
2024-03-24 4:58pm
v37
· 8 months ago
2024-03-24 4:57pm
v36
· 8 months ago
2024-03-24 4:57pm
v35
· 8 months ago
2024-03-24 9:39am
v33
· 8 months ago
2024-03-24 9:13am
v29
· 8 months ago
2024-03-24 12:33am
v25
· 8 months ago
2024-03-23 11:58pm
v24
· 8 months ago
2024-03-23 11:57pm
v23
· 8 months ago
2024-03-23 11:57pm
v22
· 8 months ago
v47
2024-03-25 1:10pm
Generated on Mar 25, 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.
812 Total Images
View All Images
Dataset Split
Train Set 86%
702Images
Valid Set 14%
110Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 2
Noise: Up to 1% of pixels