Dataset Versions

v1

Garbage Dataset1

Generated on Mar 8, 2022

Popular Download Formats

Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
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.

Dataset Split

Train Set 93%
57348Images
Valid Set 4%
2228Images
Test Set 3%
2152Images

Preprocessing

Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 21-69% Horizontal Region, 30-75% Vertical Region
Resize: Stretch to 416x416
Grayscale: Applied
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 62% Maximum Zoom
Rotation: Between -40° and +40°
Shear: ±23° Horizontal, ±25° Vertical
Brightness: Between -72% and +72%
Blur: Up to 14.25px
Noise: Up to 19% of pixels
Mosaic: Applied
Bounding Box: Flip: Horizontal
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Rotation: Between -40° and +40°
Bounding Box: Shear: ±23° Horizontal, ±24° Vertical
Bounding Box: Brightness: Between -63% and +63%
Bounding Box: Blur: Up to 14.25px
Bounding Box: Noise: Up to 19% of pixels