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This project is a PyTorch implementation that uses deep CNN to recognize multi-digit numbers using the SVHN dataset derived from Google Street View house numbers, each picture contains a set of numbers from 0 to 9, the model is tested to have 89% accuracy.| 使用深度卷积神经网络从街景图像中识别多位数门牌号的PyTorch实现方案，使用的数据集为SVHN，来源于谷歌街景门牌号码，每张图片中包含一组0-9的阿拉伯数字，经测试精确度可达89%

Home Page: https://foruda.gitee.com/images/1681966695122858106/1448f9e8_10787834.png

License: MIT License

Python 100.00%
cnn-classification deep-learning pytorch svhn-dataset

svhn-recognition's Introduction

SVHN-Recognition

Python application license

Requirements

conda create -n svhn --yes --file conda.txt
conda activate svhn
pip install -r requirements.txt

Params

Steps GPU Batch Size Learning Rate Patience Decay Step Decay Rate Accuracy
122000 GTX 1080 Ti 512 0.01 100 625 0.9 89.21%

Usage

  1. Clone the source code
git clone [email protected]:MuGeminorum/SVHN-Recognition.git
cd SVHN-Recognition
  1. Run convert_to_lmdb.py
  2. Run train.py
  3. Run infer.py

Training curve

loss

Reference

[1] Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

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