File size: 1,598 Bytes
6b68a58 9f98039 6b68a58 9f98039 a0ab119 9f98039 a0ab119 0d37db6 9f98039 a0ab119 9f98039 13968df 9f98039 a0ab119 0d37db6 9f98039 a0ab119 13968df 9f98039 a0ab119 13968df 9f98039 a0ab119 77974d3 9f98039 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 |
---
license: mit
datasets:
- svhn
language:
- en
- zh
metrics:
- accuracy
pipeline_tag: object-detection
tags:
- legal
---
# Intro
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.
## Demo
<https://huggingface.co/spaces/Genius-Society/svhn>
## Usage
```python
from modelscope import snapshot_download
model_dir = snapshot_download("Genius-Society/svhn")
```
## Dataset
<https://huggingface.co/datasets/Genius-Society/svhn>
## Training curve
## Mirror
<https://www.modelscope.cn/models/Genius-Society/svhn>
## References
[1] <https://github.com/Genius-Society/svhn_recognition><br>
[2] [Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks](http://arxiv.org/pdf/1312.6082.pdf) |