Dataset Versions
Versions
2023-04-03 2:05pm
v31
· 2 years ago
2023-04-03 1:38pm
v30
· 2 years ago
2023-03-24 2:40pm
v29
· 2 years ago
best version except try
v28
· 2 years ago
2023-03-17 5:00pm
v27
· 2 years ago
2023-03-17 4:34pm
v26
· 2 years ago
2023-03-17 3:30pm
v25
· 2 years ago
including ty...
v24
· 2 years ago
2023-03-17 11:14am
v23
· 2 years ago
2023-03-06 4:02pm
v22
· 2 years ago
2023-03-06 3:26pm
v20
· 2 years ago
2023-03-06 3:24pm
v19
· 2 years ago
2023-03-06 3:20pm
v18
· 2 years ago
2023-03-06 3:12pm
v17
· 2 years ago
2023-03-06 3:03pm
v16
· 2 years ago
2023-03-06 2:52pm
v15
· 2 years ago
2023-03-06 12:33pm
v14
· 2 years ago
2023-03-06 12:28pm
v13
· 2 years ago
2023-03-06 12:25pm
v12
· 2 years ago
2023-03-06 12:19pm
v11
· 2 years ago
after guide assistance
v10
· 2 years ago
2023-02-27 4:10pm
v9
· 2 years ago
2023-02-27 2:43pm
v8
· 2 years ago
2023-02-27 1:35pm
v7
· 2 years ago
last
v6
· 2 years ago
2023-02-24 2:45pm
v5
· 2 years ago
2023-02-24 12:43pm
v4
· 2 years ago
2023-02-24 12:21pm
v3
· 2 years ago
2023-02-24 12:15pm
v2
· 2 years ago
2023-02-20 4:55pm
v1
· 2 years ago
v6
last
Generated on Feb 24, 2023
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.
121 Total Images
View All ImagesDataset Split
Train Set 76%
92Images
Valid Set 14%
17Images
Test Set 10%
12Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal