potato classification Dataset
Versions
PDD_V15_EXPOSURE_25-06-2024
v15
· 3 months ago
PDD_V14_BRGHT_SAT_ROTCNTR_EXP_24-06-2024
v14
· 3 months ago
PDD_V13_BRGHT_SAT_ROTCNTR_EXP_24-06-2024
v13
· 3 months ago
PDD_BRGHT_SAT_ROTCNTR_EXPOSURE_22-06-2024
v12
· 3 months ago
Working dataset Version
v11
· 3 months ago
2024-06-20 5:45pm
v10
· 3 months ago
PDD_BRGHT-SAT-V1_19-06-2024
v9
· 3 months ago
PDD_STD-SETUP_07-06-2024
v8
· 4 months ago
PDD_EXPOSURE-640_07-06-2024
v7
· 4 months ago
PDD_V3_TILING-ONLY_06-06-2024
v3
· 4 months ago
PDD_V2_05-06-2024
v2
· 4 months ago
PDD_V1_05-06-2024
v1
· 4 months ago
v13
PDD_V13_BRGHT_SAT_ROTCNTR_EXP_24-06-2024
Generated on Jun 23, 2024
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YOLOv9
TXT annotations and YAML config used with YOLOv9.
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Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
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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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2932 Total Images
View All Images
Dataset Split
Train Set 89%
2613Images
Valid Set 7%
200Images
Test Set 4%
119Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (white edges) in 256x256
Filter Null: Require at least 50% of images to contain annotations.
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Counter-Clockwise
Saturation: Between -15% and +15%
Brightness: Between 0% and +5%
Exposure: Between -15% and +15%