Dataset Versions
Versions
2023-03-07 3:01pm
v28
· 2 years ago
2023-03-06 7:34pm
v27
· 2 years ago
2023-03-06 7:31pm
v26
· 2 years ago
2023-03-06 2:59pm
v25
· 2 years ago
2023-03-06 2:55pm
v24
· 2 years ago
2023-03-06 2:54pm
v23
· 2 years ago
2023-03-06 1:29pm
v22
· 2 years ago
2023-03-06 11:22am
v21
· 2 years ago
2023-03-06 11:19am
v20
· 2 years ago
2023-03-06 11:14am
v19
· 2 years ago
2023-03-06 11:12am
v18
· 2 years ago
2023-03-06 10:45am
v17
· 2 years ago
2023-03-05 11:16am
v16
· 2 years ago
2023-03-04 9:14pm
v15
· 2 years ago
2023-03-03 9:38pm
v14
· 2 years ago
2023-03-03 4:08pm
v13
· 2 years ago
2023-03-03 3:53pm
v12
· 2 years ago
2023-03-03 3:38pm
v11
· 2 years ago
2023-03-03 3:23pm
v10
· 2 years ago
2023-03-03 2:58pm
v9
· 2 years ago
2023-03-03 2:40pm
v8
· 2 years ago
2023-03-03 2:18pm
v7
· 2 years ago
2023-03-03 1:55pm
v6
· 2 years ago
2023-03-03 1:30pm
v5
· 2 years ago
2023-03-03 1:09pm
v4
· 2 years ago
2023-03-03 12:49pm
v3
· 2 years ago
2023-03-03 12:31pm
v2
· 2 years ago
2023-03-02 10:03am
v1
· 2 years ago
v13
2023-03-03 4:08pm
Generated on Mar 3, 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.
1030 Total Images
View All Images
Dataset Split
Train Set 88%
903Images
Valid Set 8%
84Images
Test Set 4%
43Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Grayscale: Apply to 25% of images
Saturation: Between -25% and +25%
Brightness: Between -54% and +54%
Blur: Up to 6px
Noise: Up to 15% of pixels