Dataset Versions

Versions
2023-05-13 11:52pm
v26
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2 years ago
2023-05-13 11:51pm
v25
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2 years ago
2023-05-10 8:57pm
v24
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2 years ago
2023-05-10 8:55pm
v23
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2 years ago
2023-05-10 8:54pm
v22
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2 years ago
2023-05-10 6:36pm
v21
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2 years ago
2023-05-10 6:35pm
v20
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2 years ago
2023-05-05 10:09am
v19
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2 years ago
2023-05-05 10:06am
v18
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2 years ago
2023-05-04 1:59pm
v17
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2 years ago
2023-05-04 12:26pm
v16
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2 years ago
2023-05-01 10:06pm
v15
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2 years ago
2023-05-01 10:05pm
v14
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2 years ago
2023-04-04 1:56am
v13
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2 years ago
2023-04-04 1:53am
v12
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2 years ago
2023-04-04 1:52am
v11
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2 years ago
2023-04-03 11:03pm
v10
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2 years ago
2023-04-03 11:03pm
v9
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2 years ago
2023-04-02 6:35pm
v8
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2 years ago
2023-04-02 6:34pm
v7
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2 years ago
2023-04-02 2:36pm
v6
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2 years ago
2023-04-02 2:36pm
v5
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2 years ago
2023-03-31 8:25pm
v4
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2 years ago
2023-03-31 2:30pm
v3
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2 years ago
2023-03-31 2:30pm
v2
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2 years ago
2023-03-31 2:30pm
v1
·
2 years ago
v10

2023-04-03 11:03pm

Generated on Apr 3, 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.
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256 Total Images

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Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image Dataset Image

Dataset Split

Train Set 69%
176Images
Valid Set 29%
73Images
Test Set 3%
7Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 1
Grayscale: Apply to 50% of images
Exposure: Between -30% and +30%
Blur: Up to 3.5px
Noise: Up to 5% of pixels

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