Dataset Versions
Versions
2022-08-28 6:30pm
v45
· 2 years ago
2022-08-28 6:29pm
v44
· 2 years ago
2022-08-28 6:29pm
v43
· 2 years ago
2022-08-28 6:29pm
v42
· 2 years ago
2022-08-28 6:28pm
v41
· 2 years ago
2022-08-28 6:28pm
v40
· 2 years ago
2022-08-28 6:27pm
v39
· 2 years ago
2022-08-28 6:25pm
v38
· 2 years ago
2022-08-28 6:24pm
v37
· 2 years ago
2022-08-28 6:24pm
v36
· 2 years ago
2022-08-28 6:23pm
v35
· 2 years ago
2022-08-28 6:23pm
v34
· 2 years ago
2022-08-28 6:22pm
v33
· 2 years ago
2022-08-28 6:22pm
v32
· 2 years ago
2022-08-28 6:21pm
v31
· 2 years ago
2022-08-28 6:21pm
v30
· 2 years ago
2022-08-28 6:20pm
v29
· 2 years ago
2022-08-28 6:20pm
v28
· 2 years ago
2022-08-28 6:18pm
v27
· 2 years ago
2022-08-28 6:17pm
v26
· 2 years ago
2022-08-28 6:17pm
v25
· 2 years ago
2022-08-28 6:16pm
v24
· 2 years ago
2022-08-28 6:15pm
v23
· 2 years ago
2022-08-28 6:15pm
v22
· 2 years ago
2022-08-28 6:13pm
v21
· 2 years ago
v31
2022-08-28 6:21pm
Generated on Aug 28, 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.
63 Total Images
View All Images
Dataset Split
Train Set 100%
63Images
Valid Set %
0Images
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
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Brightness: Between -25% and +25%
Noise: Up to 3% of pixels