Classical OCR DCNN reproduction based on PaddlePaddle framework.

Overview

Paddle-SVHN

Classical OCR DCNN reproduction based on PaddlePaddle framework.

This project reproduces Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks based on the paddlepaddle framework and participates in the Baidu paper reproduction competition. The AIStudio link is provided as follow:

link

Results_Compared

SVHN Dataset

Methods Model Download Batch Size Learning Rate Patience Decay Step Decay Rate Training Speed (FPS) Accuracy
Pytorch_SVHN torch_model 512 0.16 100 625 0.9 ~1700 95.65%
PaddlePaddle_SVHN paddle_model 1024 0.01 100 625 0.9 ~1700 95.65%

Introduction

The main idea of this exercise is to study the evolvement of the state of the art and main work along topic of visual attention model. There are two datasets that are studied: augmented MNIST and SVHN. The former dataset focused on canonical problem  —  handwritten digits recognition, but with cluttering and translation, the latter focus on real world problem  —  street view house number (SVHN) transcription. In this exercise, the following papers are studied in the way of developing a good intuition to choose a proper model to tackle each of the above challenges.

For more detail, please refer to this blog

Recommended environment

Python 3.6+
paddlepaddle-gpu 2.0.2
nccl 2.0+
editdistance
visdom
h5py
protobuf
lmdb

Install

Install env

Install paddle following the official tutorial.

pip install visdom
pip install h5py
pip install protobuf
pip install lmdb

Dataset

  1. Download SVHN Dataset format 1

  2. Extract to data folder, now your folder structure should be like below:

    SVHNClassifier
        - data
            - extra
                - 1.png 
                - 2.png
                - ...
                - digitStruct.mat
            - test
                - 1.png 
                - 2.png
                - ...
                - digitStruct.mat
            - train
                - 1.png 
                - 2.png
                - ...
                - digitStruct.mat
    

Usage

  1. (Optional) Take a glance at original images with bounding boxes

    Open `draw_bbox.ipynb` in Jupyter
    
  2. Convert to LMDB format

    $ python convert_to_lmdb.py --data_dir ./data
    
  3. (Optional) Test for reading LMDBs

    Open `read_lmdb_sample.ipynb` in Jupyter
    
  4. Train

    $ python train.py --data_dir ./data --logdir ./logs
    
  5. Retrain if you need

    $ python train.py --data_dir ./data --logdir ./logs_retrain --restore_checkpoint ./logs/model-100.pth
    
  6. Evaluate

    $ python eval.py --data_dir ./data ./logs/model-100.pth
    
  7. Visualize

    $ python -m visdom.server
    $ python visualize.py --logdir ./logs
    
  8. Infer

    $ python infer.py --checkpoint=./logs/model-100.pth ./images/test1.png
    
  9. Clean

    $ rm -rf ./logs
    or
    $ rm -rf ./logs_retrain
    
Owner
Dreams Are Messages From The Deep🪐
QICK: Quantum Instrumentation Control Kit

QICK: Quantum Instrumentation Control Kit The QICK is a kit of firmware and software to use the Xilinx RFSoC to control quantum systems. It consists o

81 Dec 15, 2022
This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing described in paper Discontinuous Grammar as a Foreign Language.

Discontinuous Grammar as a Foreign Language This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing

Daniel Fernández-González 2 Apr 07, 2022
TLoL (Python Module) - League of Legends Deep Learning AI (Research and Development)

TLoL-py - League of Legends Deep Learning Library TLoL-py is the Python component of the TLoL League of Legends deep learning library. It provides a s

7 Nov 29, 2022
Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021]

Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021] This repository is the official implementation of Moiré Attack (MA): A New Pot

Dantong Niu 22 Dec 24, 2022
Price-Prediction-For-a-Dream-Home - A machine learning based linear regression trained model for house price prediction.

Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p

DIKSHA DESWAL 1 Dec 29, 2021
Image-to-image translation with conditional adversarial nets

pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat

Phillip Isola 9.3k Jan 08, 2023
Breast Cancer Classification Model is applied on a different dataset

Breast Cancer Classification Model is applied on a different dataset

1 Feb 04, 2022
Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Diffusion Probabilistic Models This repository provides a reference implementation of the method described in the paper: Deep Unsupervised Learning us

Jascha Sohl-Dickstein 238 Jan 02, 2023
Voila - Voilà turns Jupyter notebooks into standalone web applications

Rendering of live Jupyter notebooks with interactive widgets. Introduction Voilà turns Jupyter notebooks into standalone web applications. Unlike the

Voilà Dashboards 4.5k Jan 03, 2023
Source codes for "Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs"

Structure-Aware-BART This repo contains codes for the following paper: Jiaao Chen, Diyi Yang:Structure-Aware Abstractive Conversation Summarization vi

GT-SALT 56 Dec 08, 2022
A python module for scientific analysis of 3D objects based on VTK and Numpy

A lightweight and powerful python module for scientific analysis and visualization of 3d objects.

Marco Musy 1.5k Jan 06, 2023
Picasso: a methods for embedding points in 2D in a way that respects distances while fitting a user-specified shape.

Picasso Code to generate Picasso embeddings of any input matrix. Picasso maps the points of an input matrix to user-defined, n-dimensional shape coord

Pachter Lab 45 Dec 23, 2022
Bridging Composite and Real: Towards End-to-end Deep Image Matting

Bridging Composite and Real: Towards End-to-end Deep Image Matting Please note that the official repository of the paper Bridging Composite and Real:

Jizhizi_Li 30 Oct 31, 2022
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning

Learning to Reweight Examples for Robust Deep Learning Unofficial PyTorch implementation of Learning to Reweight Examples for Robust Deep Learning. Th

Daniel Stanley Tan 325 Dec 28, 2022
Repository for MeshTalk supplemental material and code once the (already approved) 16 GHS captures our lab will make publicly available are released.

meshtalk This repository contains code to run MeshTalk for face animation from audio. If you use MeshTalk, please cite @inproceedings{richard2021mesht

Meta Research 221 Jan 06, 2023
Codes for "Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier"

Deep-RTC [project page] This repository contains the source code accompanying our ECCV 2020 paper. Solving Long-tailed Recognition with Deep Realistic

Gina Wu 16 May 26, 2022
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
ICCV2021 Oral SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

Sign-Agnostic Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page This repository contains the implementation

64 Jan 05, 2023
Research code for the paper "Variational Gibbs inference for statistical estimation from incomplete data".

Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer

Vaidotas Šimkus 1 Apr 08, 2022
Implementation of a Transformer that Ponders, using the scheme from the PonderNet paper

Ponder(ing) Transformer Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of

Phil Wang 65 Oct 04, 2022