某学校选课系统GIF验证码数据集 + Baseline模型 + 上下游相关工具

Overview

elective-dataset-2021spring

某学校2021春季选课系统GIF验证码数据集(29338张) + 准确率98.4%的Baseline模型 + 上下游相关工具。

数据集采用 知识共享署名-非商业性使用 4.0 国际许可协议 进行许可。

Baseline模型和上下游相关工具采用 MIT License 进行许可。

数据集

dataset/ 目录包含了收集到的所有带标签验证码数据,共29338张。

  • dataset/manual: 人工标注的带标签验证码GIF数据集,标签经过了elective验证因此都是正确的。共5471张。
  • dataset/auto-corrdataset/auto-fail-tagged: 模型自动标注的带标签验证码GIF数据集,其中 auto-corr 是识别正确(通过了elective验证)的部分,auto-fail-tagged 是识别错误然后手工重新标注的部分(此部分不保证正确性)。共22931(正确)+936(错误)张。

使用时请注意,由于 GitHub 的限制

  • auto-fail-tagged 在仓库中存储为7-zip压缩包;
  • manual 在仓库中存储为7个不超过48MB的7-zip分卷;
  • auto-corr 没有存储在仓库中,而是压缩为14个不超过95MB的7-zip分卷放在了 Release页面

Baseline 模型

baseline/ 目录包含一个简易的验证码识别模型。

此模型进行了提取关键帧、基于OpenCV的图像增强以及基于CNN的分类器等一系列工作以完成识别。

将训练集和测试集图片分别放入 set-trainset-test 后运行 train.py 进行训练,用一块TITAN RTX训练需要几分钟的时间。

用大约一万张图片训练好的 checkpoints/model_29.pth 能达到 98.4% 的整体精确度。

predict_bootstrap.py 在elective系统上测试当前模型,将检验正确的带标签图片放入 bootstrap_img_succ 目录,错误的图片放入 bootstrap_img_fail 目录。

上下游相关工具

  • crawl/: 验证码众包标注平台,可以从elective爬取验证码、辅助多名用户同时标注、检验正确性后将正确的数据放入 img_correct 目录。检验错误的验证码将被抛弃,这是初期的一个设计失误,这样将使得数据集的分布与真实分布有偏差。
  • retag/: 手工标注模型识别错误数据的工具。从 bootstrap_img_fail 读取标注错误图片,人工输入正确标注后移动到 bootstrap_img_fail_tagged
  • serve/: 提供在线验证码识别服务的 HTTP RPC 服务器。POST /fire 并传入base64编码的验证码GIF来进行识别。

数据处理过程

首先,我们设立了众包标注平台,多名志愿者累计标注了超过五千张验证码。

有了这些数据后,我们利用OpenCV进行了简单的图片增强、二值化、分字、裁切,然后随手糊了一个简单的CNN网络来识别。在随意调参之后,模型的整体(四个字)准确率接近95%。

然后,我们利用此模型来对数据集进行自举:爬取验证码后调用模型识别然后检验正确性,其中识别错误的部分手工标注。这样我们可以轻易地扩大数据集的规模,从而提升模型效果。

经过了更多的随意调参,模型的整体准确率可以达到98.4%。因为继续提升准确率意义不大,就没有继续优化。考虑到 PyTorch 安装比较麻烦,模型不易于部署到用户的设备上,我们实现了一个 HTTP API 可以用于云端识别。

相关工作

by Elector Quartet (按字典序的倒序 @xmcp, @SpiritedAwayCN, @Rabbit, @gzz)

You might also like...
Owner
xmcp
叶氏筛法第 NaN 代传人
xmcp
Second-order Attention Network for Single Image Super-resolution (CVPR-2019)

Second-order Attention Network for Single Image Super-resolution (CVPR-2019) "Second-order Attention Network for Single Image Super-resolution" is pub

516 Dec 28, 2022
Pre-trained Deep Learning models and demos (high quality and extremely fast)

OpenVINO™ Toolkit - Open Model Zoo repository This repository includes optimized deep learning models and a set of demos to expedite development of hi

OpenVINO Toolkit 3.4k Dec 31, 2022
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.

OpenCDA OpenCDA is a SIMULATION tool integrated with a prototype cooperative driving automation (CDA; see SAE J3216) pipeline as well as regular autom

UCLA Mobility Lab 726 Dec 29, 2022
Official implementation of particle-based models (GNS and DPI-Net) on the Physion dataset.

Physion: Evaluating Physical Prediction from Vision in Humans and Machines [paper] Daniel M. Bear, Elias Wang, Damian Mrowca, Felix J. Binder, Hsiao-Y

Hsiao-Yu Fish Tung 18 Dec 19, 2022
Mmrotate - OpenMMLab Rotated Object Detection Benchmark

OpenMMLab website HOT OpenMMLab platform TRY IT OUT 📘 Documentation | 🛠️ Insta

OpenMMLab 1.2k Jan 04, 2023
Principled Detection of Out-of-Distribution Examples in Neural Networks

ODIN: Out-of-Distribution Detector for Neural Networks This is a PyTorch implementation for detecting out-of-distribution examples in neural networks.

189 Nov 29, 2022
Various operations like path tracking, counting, etc by using yolov5

Object-tracing-with-YOLOv5 Various operations like path tracking, counting, etc by using yolov5

Pawan Valluri 5 Nov 28, 2022
PyTorch implementation of MoCo: Momentum Contrast for Unsupervised Visual Representation Learning

MoCo: Momentum Contrast for Unsupervised Visual Representation Learning This is a PyTorch implementation of the MoCo paper: @Article{he2019moco, aut

Meta Research 3.7k Jan 02, 2023
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

AlphaZero-Gomoku This is an implementation of the AlphaZero algorithm for playing the simple board game Gomoku (also called Gobang or Five in a Row) f

Junxiao Song 2.8k Dec 26, 2022
This Deep Learning Model Predicts that from which disease you are suffering.

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

Jai Viral Doshi 0 Jan 20, 2022
[ACM MM 2021] Joint Implicit Image Function for Guided Depth Super-Resolution

Joint Implicit Image Function for Guided Depth Super-Resolution This repository contains the code for: Joint Implicit Image Function for Guided Depth

hawkey 78 Dec 27, 2022
rliable is an open-source Python library for reliable evaluation, even with a handful of runs, on reinforcement learning and machine learnings benchmarks.

Open-source library for reliable evaluation on reinforcement learning and machine learning benchmarks. See NeurIPS 2021 oral for details.

Google Research 529 Jan 01, 2023
TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset

AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin

Matteo Dunnhofer 161 Nov 25, 2022
An official source code for "Augmentation-Free Self-Supervised Learning on Graphs"

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

Namkyeong Lee 59 Dec 01, 2022
Baseline inference Algorithm for the STOIC2021 challenge.

STOIC2021 Baseline Algorithm This codebase contains an example submission for the STOIC2021 COVID-19 AI Challenge. As a baseline algorithm, it impleme

Luuk Boulogne 10 Aug 08, 2022
Churn-Prediction-Project - In this project, a churn prediction model is developed for a private bank as a term project for Data Mining class.

Churn-Prediction-Project In this project, a churn prediction model is developed for a private bank as a term project for Data Mining class. Project in

1 Jan 03, 2022
🏃‍♀️ A curated list about human motion capture, analysis and synthesis.

Awesome Human Motion 🏃‍♀️ A curated list about human motion capture, analysis and synthesis. Contents Introduction Human Models Datasets Data Process

Dennis Wittchen 274 Dec 14, 2022
Official PyTorch implementation of the paper Image-Based CLIP-Guided Essence Transfer.

TargetCLIP- official pytorch implementation of the paper Image-Based CLIP-Guided Essence Transfer This repository finds a global direction in StyleGAN

Hila Chefer 221 Dec 13, 2022
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.

Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut

Bin Xiao 175 Jan 08, 2023
Semi-supervised Stance Detection of Tweets Via Distant Network Supervision

SANDS This is an annonymous repository containing code and data necessary to reproduce the results published in "Semi-supervised Stance Detection of T

2 Sep 22, 2022