Dataset Versions

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Versions
2023-09-05 6:18pm
v21
·
a year ago
2023-09-05 6:14pm
v20
·
a year ago
2023-08-31 12:33am
v18
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a year ago
2023-06-08 8:32pm
v12
·
a year ago
2023-06-08 2:14am
v11
·
a year ago
2023-06-07 1:20am
v10
·
a year ago
2023-05-31 2:07am
v9
·
2 years ago
2023-05-30 10:36pm
v8
·
2 years ago
2023-05-30 2:32am
v7
·
2 years ago
2023-05-10 2:25am
v5
·
2 years ago
2023-04-03 4:18pm
v1
·
2 years ago
v20

2023-09-05 6:14pm

Generated on Sep 5, 2023
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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
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4259 Total Images

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Dataset Split

Train Set 99%
4221Images
Valid Set 1%
38Images
Test Set %
0Images

Preprocessing

Auto-Orient: Applied
Resize: Fit within 480x640
Auto-Adjust Contrast: Using Contrast Stretching

Augmentations

Outputs per training example: 3
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -29° and +29°
Shear: ±10° Horizontal, ±10° Vertical
Hue: Between -30° and +30°
Saturation: Between -50% and +50%
Brightness: Between -51% and +51%
Exposure: Between -45% and +45%
Bounding Box: Crop: 0% Minimum Zoom, 30% Maximum Zoom
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Brightness: Between -20% and +20%
Bounding Box: Exposure: Between -40% and +40%
Bounding Box: Blur: Up to 3.25px
Bounding Box: Noise: Up to 5% of pixels

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