Dataset Versions

Versions
2022-02-01 6:23pm
v36
·
3 years ago
Data Augment: C-N-M
v35
·
3 years ago
Data Augment: Mosaic
v34
·
3 years ago
Data Augment: Cutout
v33
·
3 years ago
Data Augment: Noise
v32
·
3 years ago
Data Augment: Shear
v31
·
3 years ago
Data Augment: 90- Rotation
v30
·
3 years ago
Data Augment: H-V Flip
v29
·
3 years ago
Plastic Tile2x2 Contraststretching 75-15-10
v28
·
3 years ago
Plastic Tile3x3 75-15-10
v27
·
3 years ago
Plastic Adaptive Equalization 75-15-10
v26
·
3 years ago
Plastic Histogram Equalization 75-15-10
v25
·
3 years ago
Plastic Contrast Stretching 75-15-10
v24
·
3 years ago
Plastic Greyscale 75-15-10
v23
·
3 years ago
Plastic Tile 2x2 75-15-10
v22
·
3 years ago
Plastic No Preprocessing 85-5-10
v20
·
3 years ago
Plastic No Preprocessing 75-15-10
v19
·
3 years ago
Plastic No Preprocessing 70-15-15
v18
·
3 years ago
Plastic No Preprocessing 60-30-10
v17
·
3 years ago
Plastic No Preprocessing 60-20-20
v16
·
3 years ago
Plastic Sample tile 2x2 grayscale
v15
·
3 years ago
Plastic Sample tile 2x2 adaptive equalization
v14
·
3 years ago
Plastic Sample tile 2x2 histogram equalization
v13
·
3 years ago
Plastic Sample tile 2x2 - contrast stretching 80-10-10
v12
·
3 years ago
Plastic Sample Using tile2x2 80-10-10
v11
·
3 years ago
Plastic Sample Using contrast Adaptive Equalization-grayscale 80-10-10
v10
·
3 years ago
Plastic Sample Using contrast histogram Equalization - grayscale 80-10-10
v8
·
3 years ago
Plastic Sample Grayscale Preprocessing - contrast stretching 80-10-10
v7
·
3 years ago
Plastic Sample Using contrast stretching 80-10-10
v6
·
3 years ago
Plastic Sample Using contrast histogram Equalization 80-10-10
v5
·
3 years ago
Plastic Sample Using contrast Adaptive Equalization 80-10-10
v4
·
3 years ago
Plastic Sample Grayscale Preprocessing 80-10-10
v3
·
3 years ago
Plastic No Preprocessing 80-10-10
v2
·
3 years ago
Plastic No Preprocessing 70-20-10
v1
·
3 years ago
v32

Data Augment: Noise

Generated on Oct 16, 2021

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.
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Dataset Split

Train Set 86%
3144Images
Valid Set 9%
316Images
Test Set 6%
212Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 512x512
Tile: 2 rows x 2 columns

Augmentations

Outputs per training example: 2
Noise: Up to 5% of pixels

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