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README.md
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'4': '4'
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'5': '5'
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'6': '6'
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'7': '7'
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'8': '8'
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'9': '9'
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splits:
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- name: train
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num_bytes: 8736255.716177294
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num_examples: 5000
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- name: validation
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num_bytes: 851528.6186232329
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num_examples: 500
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- name: test
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num_bytes: 1703057.2372464659
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num_examples: 1000
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download_size: 11788138
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dataset_size: 11290841.572046991
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: validation
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path: data/validation-*
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- split: test
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path: data/test-*
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---
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license: other
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tags:
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- svhn
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- street-view-house-numbers
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- image-classification
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- digit-recognition
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- subset
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- computer-vision
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source_datasets:
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- ufldl-stanford/svhn
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task_categories:
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- image-classification
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---
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# SVHN (Street View House Numbers) — Subset 🔢
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Stratified random subset of [SVHN](http://ufldl.stanford.edu/housenumbers/),
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sourced from [ufldl-stanford/svhn](https://huggingface.co/datasets/ufldl-stanford/svhn).
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## Splits
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| Split | Rows | Classes | Per class |
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|------------|-------|---------|-----------|
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| train | 5,000 | 10 | ~500 |
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| test | 1,000 | 10 | ~100 |
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| validation | 500 | 10 | ~50 |
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## About SVHN
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The Street View House Numbers (SVHN) dataset is a real-world digit recognition dataset
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obtained from Google Street View images.
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- **Full train set**: 73,257 images
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- **Full test set**: 26,032 images
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- **Extra set**: 531,131 images (not included in this subset)
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- **Image size**: 32 × 32 RGB (cropped_digits config)
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- **Classes**: 10 digits (0–9)
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- **Config used**: `cropped_digits` — MNIST-like single digit per image
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## Classes
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| ID | Digit | ID | Digit |
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|----|-------|----|-------|
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| 0 | 0 | 5 | 5 |
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| 1 | 1 | 6 | 6 |
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| 2 | 2 | 7 | 7 |
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| 3 | 3 | 8 | 8 |
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| 4 | 4 | 9 | 9 |
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## Usage
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```python
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from datasets import load_dataset
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ds = load_dataset("Chiranjeev007/SVHN-10_Subset")
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print(ds)
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# DatasetDict({
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# train: Dataset(num_rows: 5000),
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# validation: Dataset(num_rows: 500),
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# test: Dataset(num_rows: 1000)
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# })
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sample = ds["train"][0]
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sample["image"] # PIL Image 32×32 RGB
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sample["label"] # int 0–9
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```
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## Sampling Details
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- **Method**: Stratified random — proportional per class
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- **Seed**: 42
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- **Source config**: `cropped_digits`
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