Dataset Versions
Versions
2024-07-13 1:39pm
v30
· 4 months ago
2024-07-13 1:39pm
v29
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v28
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v27
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v26
· 4 months ago
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v25
· 4 months ago
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v24
· 4 months ago
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v23
· 4 months ago
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v22
· 4 months ago
2024-07-13 1:38pm
v21
· 4 months ago
2024-07-13 1:38pm
v20
· 4 months ago
2024-07-13 1:38pm
v19
· 4 months ago
2024-07-13 1:38pm
v18
· 4 months ago
2024-07-13 1:38pm
v17
· 4 months ago
2024-07-13 1:38pm
v16
· 4 months ago
2024-07-13 1:38pm
v15
· 4 months ago
2024-07-13 1:38pm
v14
· 4 months ago
2024-07-13 1:38pm
v13
· 4 months ago
2024-07-13 1:14pm
v12
· 4 months ago
2024-07-13 1:10pm
v11
· 4 months ago
2024-07-13 12:38pm
v10
· 4 months ago
2024-07-13 12:37pm
v9
· 4 months ago
2024-07-13 12:37pm
v8
· 4 months ago
2024-07-13 12:37pm
v7
· 4 months ago
2024-07-13 12:37pm
v6
· 4 months ago
2024-07-13 12:37pm
v5
· 4 months ago
2024-07-13 12:37pm
v4
· 4 months ago
2024-07-13 12:37pm
v3
· 4 months ago
2024-07-13 12:37pm
v2
· 4 months ago
2024-07-13 12:14pm
v1
· 4 months ago
v10
2024-07-13 12:38pm
Generated on Jul 13, 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.
192 Total Images
View All ImagesDataset Split
Train Set 88%
168Images
Valid Set 8%
16Images
Test Set 4%
8Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 512x512
Augmentations
Outputs per training example: 3
Blur: Up to 0.9px
Noise: Up to 0.22% of pixels