Dataset Versions
Versions
2024-08-25 11:18am
v28
· 2 months ago
2024-08-25 11:18am
v27
· 2 months ago
2024-08-25 11:17am
v26
· 2 months ago
2024-08-25 11:16am
v25
· 2 months ago
2024-08-25 11:16am
v24
· 2 months ago
2024-08-25 11:15am
v23
· 2 months ago
2024-08-25 11:14am
v22
· 2 months ago
2024-08-25 11:13am
v21
· 2 months ago
2024-08-25 11:11am
v20
· 2 months ago
2024-08-24 8:57am
v19
· 2 months ago
2024-08-24 8:56am
v18
· 2 months ago
2024-08-24 8:55am
v17
· 2 months ago
2024-08-24 8:54am
v16
· 2 months ago
2024-08-24 8:53am
v15
· 2 months ago
2024-08-24 8:52am
v14
· 2 months ago
2024-08-24 8:52am
v13
· 2 months ago
2024-08-24 8:51am
v12
· 2 months ago
2024-08-24 8:50am
v11
· 2 months ago
2024-08-24 8:49am
v10
· 2 months ago
2024-08-24 8:47am
v9
· 2 months ago
2024-08-24 8:46am
v8
· 2 months ago
2024-08-22 7:34pm
v7
· 2 months ago
2024-08-22 7:31pm
v6
· 2 months ago
2024-08-22 7:28pm
v5
· 2 months ago
2024-08-22 6:06pm
v4
· 2 months ago
2024-08-21 9:43am
v3
· 2 months ago
2024-07-28 1:10pm
v2
· 3 months ago
2024-07-28 1:09pm
v1
· 3 months ago
v12
2024-08-24 8:51am
Generated on Aug 24, 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.
85 Total Images
View All ImagesDataset Split
Train Set 71%
60Images
Valid Set 12%
10Images
Test Set 18%
15Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Shear: ±10° Horizontal, ±10° Vertical
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