Dataset Versions
Versions
2024-11-21 4:20pm
v54
· 2 days ago
2024-11-21 4:17pm
v53
· 2 days ago
2024-11-21 4:16pm
v52
· 2 days ago
2024-11-21 4:16pm
v51
· 2 days ago
2024-11-21 12:48pm
v50
· 2 days ago
2024-10-03 12:56pm
v49
· 2 months ago
2024-10-03 9:22am
v48
· 2 months ago
2024-10-02 12:12pm
v47
· 2 months ago
2024-10-01 8:52pm
v45
· 2 months ago
2024-09-30 3:59pm
v41
· 2 months ago
SUPERAUG
v33
· 2 months ago
Downregulated augs
v32
· 2 months ago
NewfullAUG
v31
· 3 months ago
Full Aug
v30
· 3 months ago
2024-08-27 12:08pm
v28
· 3 months ago
2024-08-26 1:21pm
v27
· 3 months ago
All augmentations
v26
· 5 months ago
2024-06-21 10:41pm
v25
· 5 months ago
Bounding box aug. Lower adjusted
v24
· 5 months ago
Bounding boxes augmentation test
v23
· 5 months ago
Maxed Augmentation
v22
· 5 months ago
2024-06-18 10:37am
v21
· 5 months ago
Full augmentation
v20
· 5 months ago
Auto-adjust contrast
v17
· 5 months ago
RAW NO AUG
v15
· 5 months ago
Changedv2_newDataset
v10
· 6 months ago
v50
2024-11-21 12:48pm
Generated on Nov 21, 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.
2628 Total Images
View All Images
Dataset Split
Train Set 87%
2298Images
Valid Set 8%
217Images
Test Set 4%
113Images
Preprocessing
Auto-Orient: Applied
Static Crop: 10-80% Horizontal Region, 10-80% Vertical Region
Resize: Fit within 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 2% Maximum Zoom
Rotation: Between -4° and +4°
Shear: ±2° Horizontal, ±2° Vertical
Grayscale: Apply to 4% of images
Hue: Between -4° and +4°
Saturation: Between -10% and +10%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 0.7px
Noise: Up to 0.65% of pixels