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--- |
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license: mit |
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datasets: |
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- svhn |
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language: |
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- en |
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- zh |
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metrics: |
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- accuracy |
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pipeline_tag: object-detection |
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tags: |
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- legal |
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--- |
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# Intro |
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This is a model for recognizing multi-digit house numbers, employing a deep convolutional neural network based on the PyTorch framework, designed to identify multi-digit house numbers from street view images with high efficiency and accuracy. The training data for the model comes from the Google Street View House Numbers dataset (SVHN), which includes a series of Arabic numerals from 0 to 9 in each image. The model has achieved significant results in precision, with an accuracy rate of 89% after rigorous testing. The deep convolutional neural network structure allows the model to effectively capture the characteristics of the numbers in the house number images, thus enabling accurate recognition of multi-digit house numbers. It offers dependable technical support for street view applications in the realm of digital recognition. |
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## Demo |
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<https://huggingface.co/spaces/Genius-Society/svhn> |
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## Usage |
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```python |
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from huggingface_hub import snapshot_download |
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model_dir = snapshot_download("Genius-Society/svhn") |
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``` |
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## Maintenance |
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```bash |
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GIT_LFS_SKIP_SMUDGE=1 git clone [email protected]:Genius-Society/svhn |
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cd svhn |
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``` |
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## Dataset |
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<https://huggingface.co/datasets/Genius-Society/svhn> |
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## Training curve |
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## Mirror |
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<https://www.modelscope.cn/models/Genius-Society/svhn> |
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## References |
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[1] <https://github.com/Genius-Society/svhn_recognition><br> |
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[2] [Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks](http://arxiv.org/pdf/1312.6082.pdf) |
