Orange Trees Computer Vision Model

byDTTask:
Object Detection
License:CC BY 4.0
Versions
Dataset Version
v1

2026-06-03 11:58am

Generated on Jun 3, 2026

Dataset Split

Train Set 40%
920Images
Valid Set 26%
596Images
Test Set 35%
788Images

Preprocessing

Tile: 2 rows x 2 columns
Auto-Orient: Applied
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Contrast Stretching
Random Sample: Include 100% train, 100% valid, 100% test

Augmentations

Outputs per training example: 2
Flip: Horizontal
90° Rotate: Applied
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels
Cutout: 3 boxes with 10% size each
Mosaic: Applied
Motion Blur: Length 100px, Angle: 0°, Frames: 1
Camera Gain: Variance: 0.05
Bounding Box: Flip: Horizontal
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Shear: ±10° Horizontal, ±10° Vertical
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Exposure: Between -10% and +10%
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 0.1% of pixels
Bounding Box: Motion Blur: Length 100px, Angle: 0°, Frames: 1
Bounding Box: Camera Gain: Variance: 0.05

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