A proof of concept ai-powered Recaptcha v2 solver

Overview

Recaptcha Fullauto

I've decided to open source my old Recaptcha v2 solver. My latest version will be opened sourced this summer. I am hoping this project will serve as inspiration for others to build a solver from, as plugging in an existing model is not too difficult to do.

This project uses the AWS Rekognition API, which is a decent solution but isn't the best. If you are looking to build off this project, I would take a look at this repo for inspiration on building and training your own model. I would also reccomend using this repo as a base for your dataset or scraping images from Google Images using this project.

Twitter.vid.mp4

Requirements

  • Python 3
  • Firefox
  • Geckodriver (make sure it is installed in your PATH)
  • AWS credentials (create a new IAM user with the AmazonRekognitionFullAccess role)

Installation

Download The Project

git clone https://github.com/natewong1313/recaptcha-fullauto.git
cd recaptcha-fullauto

Configuration

Add your proxies in the proxies.txt file and add your AWS credentials in the .env file
If you don't want to use proxies, modify the src/main.py file as such

rcs = RecaptchaSolver("https://www.google.com/recaptcha/api2/demo", use_proxies = False)

Using Docker

docker build -t recaptcha-fullauto .
docker run recaptcha-fullauto

From Source

pip install -r requirements.txt
python src/main.py
Owner
Nate
17
Nate
ICRA 2021 "Towards Precise and Efficient Image Guided Depth Completion"

PENet: Precise and Efficient Depth Completion This repo is the PyTorch implementation of our paper to appear in ICRA2021 on "Towards Precise and Effic

232 Dec 25, 2022
Self-Supervised Methods for Noise-Removal

SSMNR | Self-Supervised Methods for Noise Removal Image denoising is the task of removing noise from an image, which can be formulated as the task of

1 Jan 16, 2022
DiffQ performs differentiable quantization using pseudo quantization noise. It can automatically tune the number of bits used per weight or group of weights, in order to achieve a given trade-off between model size and accuracy.

Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto

Facebook Research 145 Dec 30, 2022
SegNet-Basic with Keras

SegNet-Basic: What is Segnet? Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-wise Image Segmentation Segnet = (Encoder + Decoder)

Yad Konrad 81 Jun 30, 2022
The official repository for Deep Image Matting with Flexible Guidance Input

FGI-Matting The official repository for Deep Image Matting with Flexible Guidance Input. Paper: https://arxiv.org/abs/2110.10898 Requirements easydict

Hang Cheng 51 Nov 10, 2022
Exploiting Robust Unsupervised Video Person Re-identification

Exploiting Robust Unsupervised Video Person Re-identification Implementation of the proposed uPMnet. For the preprint, please refer to [Arxiv]. Gettin

1 Apr 09, 2022
Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)

Unsupervised Attributed Multiplex Network Embedding (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However

Chanyoung Park 114 Dec 06, 2022
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding (AAAI 2020) - PyTorch Implementation

Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding PyTorch implementation for the Scalable Attentive Sentence-Pair Modeling vi

Microsoft 25 Dec 02, 2022
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework

(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework Background: Outlier detection (OD) is a key data mining task for identify

Yue Zhao 127 Jan 05, 2023
Code for Learning to Segment The Tail (LST)

Learning to Segment the Tail [arXiv] In this repository, we release code for Learning to Segment The Tail (LST). The code is directly modified from th

47 Nov 07, 2022
https://sites.google.com/cornell.edu/recsys2021tutorial

Counterfactual Learning and Evaluation for Recommender Systems (RecSys'21 Tutorial) Materials for "Counterfactual Learning and Evaluation for Recommen

yuta-saito 45 Nov 10, 2022
the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet]

BGNet This repository contains the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet] Environment Python 3.6.* C

3DCV developer 87 Nov 29, 2022
Model Quantization Benchmark

Introduction MQBench is an open-source model quantization toolkit based on PyTorch fx. The envision of MQBench is to provide: SOTA Algorithms. With MQ

500 Jan 06, 2023
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation (ICCV2021)

Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic Segmentation (ICCV2021) This is the implementation of PSD (ICCV 2021),

12 Dec 12, 2022
GT China coal model

GT China coal model The full version of a China coal transport model with a very high spatial reslution. What it does The code works in a few steps: T

0 Dec 13, 2021
Pytorch Lightning Implementation of SC-Depth Methods.

SC_Depth_pl: This is a pytorch lightning implementation of SC-Depth (V1, V2) for self-supervised learning of monocular depth from video. In the V1 (IJ

JiaWang Bian 216 Dec 30, 2022
Generalized Proximal Policy Optimization with Sample Reuse (GePPO)

Generalized Proximal Policy Optimization with Sample Reuse This repository is the official implementation of the reinforcement learning algorithm Gene

Jimmy Queeney 9 Nov 28, 2022
This is an official implementation for the WTW Dataset in "Parsing Table Structures in the Wild " on table detection and table structure recognition.

WTW-Dataset This is an official implementation for the WTW Dataset in "Parsing Table Structures in the Wild " on ICCV 2021. Here, you can download the

109 Dec 29, 2022
ParaGen is a PyTorch deep learning framework for parallel sequence generation

ParaGen is a PyTorch deep learning framework for parallel sequence generation. Apart from sequence generation, ParaGen also enhances various NLP tasks, including sequence-level classification, extrac

Bytedance Inc. 169 Dec 22, 2022
The 3rd place solution for competition

The 3rd place solution for competition "Lyft Motion Prediction for Autonomous Vehicles" at Kaggle Team behind this solution: Artsiom Sanakoyeu [Homepa

Artsiom 104 Nov 22, 2022