Dataset Versions
Versions
2023-02-25 12:21pm
v28
· 2 years ago
2023-02-25 12:21pm
v27
· 2 years ago
2023-02-25 12:21pm
v26
· 2 years ago
2023-02-25 12:21pm
v25
· 2 years ago
2023-02-25 12:21pm
v24
· 2 years ago
2023-02-25 12:21pm
v23
· 2 years ago
2023-02-25 12:21pm
v22
· 2 years ago
2023-02-25 12:21pm
v21
· 2 years ago
2023-02-25 12:21pm
v20
· 2 years ago
2023-02-25 12:21pm
v19
· 2 years ago
2023-02-25 12:21pm
v18
· 2 years ago
2023-02-25 12:21pm
v17
· 2 years ago
2023-02-25 12:21pm
v16
· 2 years ago
2023-02-25 12:21pm
v15
· 2 years ago
2023-02-25 12:21pm
v14
· 2 years ago
2023-02-25 12:21pm
v13
· 2 years ago
2023-02-25 12:21pm
v12
· 2 years ago
2023-02-25 12:21pm
v11
· 2 years ago
2023-02-25 12:21pm
v10
· 2 years ago
2023-02-25 12:21pm
v9
· 2 years ago
2023-02-25 12:21pm
v8
· 2 years ago
2023-02-25 12:21pm
v7
· 2 years ago
2023-02-25 12:13pm
v6
· 2 years ago
2023-02-25 12:12pm
v5
· 2 years ago
2023-02-25 12:11pm
v4
· 2 years ago
2023-02-25 11:45am
v3
· 2 years ago
2023-02-25 11:44am
v2
· 2 years ago
2023-02-25 11:43am
v1
· 2 years ago
v13
2023-02-25 12:21pm
Generated on Feb 25, 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.
171 Total Images
View All ImagesDataset Split
Train Set 100%
171Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Blur: Up to 1px
Noise: Up to 5% of pixels