Detection_2 Computer Vision Model
Dataset Version
Generated on May 11, 2026
Notes: "v2_maize_detection - Split: 210 train/ 60 val/ 30 test. Preprocessing: tile 2x2, resize to 640x640. Augmentation: blur up to 2.5px, 0.1% noise, gain variance 0.05. Using 2x multiplier (2,040 total images)."
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TXT annotations and YAML config used with YOLO26.
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TXT annotations and YAML config used with YOLOv12.
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TXT annotations and YAML config used with YOLOv11.
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COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
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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).
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TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
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2040 Total Images
View All Images
Dataset Split
Train Set 82%
1680Images
Valid Set 12%
240Images
Test Set 6%
120Images
Preprocessing
Tile: 2 rows x 2 columns
Auto-Orient: Applied
Resize: Fit (black edges) in 640x640
Random Sample: Include 100% train, 100% valid, 100% test
Filter Null: Do not filter any null images.
Augmentations
Outputs per training example: 2
Flip: Horizontal
Rotation: Between -15° and +15°
Saturation: Between -30% and +30%
Brightness: Between -25% and +25%
Blur: Up to 1.5px
Mosaic: Applied
Camera Gain: Variance: 0.05
Bounding Box: Flip: Horizontal
Bounding Box: Rotation: Between -15° and +15°
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: Camera Gain: Variance: 0.05