Dataset Versions
Versions
2024-03-09 10:46am
v29
· 8 months ago
2024-03-07 9:49am
v28
· 8 months ago
2024-03-07 9:49am
v27
· 8 months ago
2024-03-07 9:48am
v26
· 8 months ago
2024-03-07 9:46am
v25
· 8 months ago
2024-03-07 9:45am
v24
· 8 months ago
2024-03-07 9:45am
v23
· 8 months ago
2024-03-07 9:43am
v22
· 8 months ago
2024-03-07 9:42am
v21
· 8 months ago
2024-03-07 9:40am
v20
· 8 months ago
2024-03-07 9:39am
v19
· 8 months ago
2024-03-07 9:38am
v18
· 8 months ago
2024-03-07 9:35am
v17
· 8 months ago
2024-03-02 11:46am
v16
· 8 months ago
2024-02-28 9:44am
v15
· 9 months ago
2024-02-26 8:52pm
v14
· 9 months ago
2024-02-22 4:45pm
v13
· 9 months ago
2024-02-22 4:26pm
v12
· 9 months ago
2024-02-20 11:13am
v11
· 9 months ago
2024-02-20 10:17am
v10
· 9 months ago
2024-02-02 10:09am
v9
· 9 months ago
2024-01-23 4:34pm
v8
· 10 months ago
2024-01-12 4:18pm
v7
· 10 months ago
2024-01-12 4:08pm
v6
· 10 months ago
2024-01-12 3:41pm
v5
· 10 months ago
2024-01-12 3:35pm
v4
· 10 months ago
2024-01-12 3:22pm
v3
· 10 months ago
Augmentation
v2
· 10 months ago
First version
v1
· 10 months ago
v13
2024-02-22 4:45pm
Generated on Feb 22, 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.
205 Total Images
View All Images
Dataset Split
Train Set 92%
189Images
Valid Set 4%
8Images
Test Set 4%
8Images
Preprocessing
No preprocessing steps were applied.
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -10° and +10°
Shear: ±1° Horizontal, ±1° Vertical
Grayscale: Apply to 10% of images
Hue: Between -15° and +15°
Saturation: Between -20% and +20%
Brightness: Between -10% and +10%
Exposure: Between -1% and +1%