Dataset Versions
Versions
2024-05-23 10:52pm
v61
· 7 months ago
2024-05-23 10:45pm
v60
· 7 months ago
2024-05-23 10:42pm
v59
· 7 months ago
2024-05-23 9:00am
v58
· 7 months ago
2024-05-22 10:34pm
v57
· 7 months ago
2024-05-22 12:37am
v56
· 7 months ago
2024-05-15 8:15pm
v55
· 7 months ago
2024-03-20 6:12pm
v54
· 9 months ago
2024-03-18 12:08am
v53
· 9 months ago
2024-03-17 2:15pm
v52
· 9 months ago
2024-03-14 12:09pm
v51
· 9 months ago
2024-03-13 5:33pm
v50
· 9 months ago
2024-03-13 5:11pm
v49
· 9 months ago
2024-03-13 11:50am
v48
· 9 months ago
2024-03-06 10:30pm
v47
· 10 months ago
2024-03-05 6:02pm
v46
· 10 months ago
2024-03-05 12:19am
v45
· 10 months ago
2024-03-04 8:06pm
v41
· 10 months ago
2024-03-04 6:58pm
v40
· 10 months ago
2024-01-15 10:55pm
v35
· a year ago
2024-01-15 2:07am
v32
· a year ago
2024-01-15 1:13am
v31
· a year ago
2024-01-15 12:21am
v30
· a year ago
v57
2024-05-22 10:34pm
Generated on May 22, 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.
2751 Total Images
View All Images
Dataset Split
Train Set 77%
2118Images
Valid Set 23%
633Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Grayscale: Apply to 15% of images
Saturation: Between -30% and +30%
Noise: Up to 1.84% of pixels