Captcha: Solver Python Github
Stars: ~300 | Language: Python
Tesseract is a Python library that wraps Google's Tesseract-OCR engine. While not exclusively a "CAPTCHA solver," it is the most common tool for text-based CAPTCHAs.
Why it matters: For simple, old-school CAPTCHAs, pytesseract combined with PIL (Pillow) and OpenCV for preprocessing (greyscale, thresholding, erosion) can achieve 80-90% accuracy.
Key insight: The secret to using pytesseract isn't the library itself; it's the preprocessing. GitHub repos like user-none/Captcha-Solver demonstrate how to remove background noise and lines before feeding the image to Tesseract.
Searching for "captcha solver python github" opens a door to dozens of solutions, but no silver bullet exists. For hobbyist projects with simple CAPTCHAs, pytesseract paired with OpenCV is sufficient. For anything involving Google, Cloudflare, or hCaptcha, the 2captcha-python or capsolver-python API clients are your only reliable options.
The best approach is to hybridize: use a local solver from GitHub as a first-pass filter, then fall back to a paid API. This minimizes costs while maximizing success rates.
Final recommendation: Star 2captcha/2captcha-python and explore its examples. Then, for learning, clone a local solver like Captcha-Solver by xHak9x to understand the image preprocessing pipeline. Between these two, you will handle 99% of automation scenarios.
Have you built a CAPTCHA solver using a different GitHub repo? Share your experience and success rate in the discussion below.
When looking for a CAPTCHA solver in Python on , you will generally find two approaches: API-based services
that use human workers or AI to solve complex challenges, and open-source machine learning (ML) tools for solving simple text-based images 1. API-Based Solvers (Professional Services) These are the most reliable for modern CAPTCHAs like reCAPTCHA v2/v3 Cloudflare Turnstile . They require an API key and usually charge per solve. 2Captcha Python
: One of the most popular official SDKs. It supports almost every CAPTCHA type, including Amazon WAF and GeeTest. SolveCaptcha Python
: A modern, lightweight SDK with async support for reCAPTCHA, Cloudflare, and more. Anti-Captcha Official
: A long-standing service offering human-powered solving via a Python client.
: Focuses on AI-powered automatic solving with high speed for reCAPTCHA and hCaptcha. 2. Open-Source & ML Solvers (Local Solving) These tools use libraries like TensorFlow
to solve simple image-based CAPTCHAs locally without external APIs.
This report examines Python-based CAPTCHA solving solutions on GitHub, categorized by their technical approach: automated Optical Character Recognition (OCR) and API-based service wrappers. 1. API-Based Service Wrappers
Most reliable GitHub projects for solving complex CAPTCHAs (like reCAPTCHA or hCaptcha) act as Python wrappers for paid third-party human-solving services. These are preferred for high-accuracy production needs.
Solvecaptcha-python: A streamlined library used to integrate the SolverCaptcha API into Python applications. It allows developers to send CAPTCHA challenges to a remote server and receive the solved text or token back.
Metabypass-python: Another integration tool for the Metabypass service, supporting multiple CAPTCHA types through specialized API calls. captcha solver python github
2-Captcha-Solver: A popular repository providing a Python 3 program to automate the interaction with the 2Captcha service. 2. Local OCR & Image Processing Solutions
For simple, text-based image CAPTCHAs, developers often use local libraries to avoid API costs.
Pytesseract & Selenium: A common method involves using Selenium for web automation and pytesseract for OCR.
Process: Download the image, preprocess it with PIL (Pillow) to enhance contrast, and use OCR to extract text.
Simple Captcha Solver: This repository demonstrates a "masking" technique. It slides letter templates across a CAPTCHA image to find the highest pixel-match score for each character. 3. Comparative Implementation Overview Local OCR (Tesseract) API Wrappers (2Captcha, etc.) Complexity High (requires image processing) Low (straightforward API calls) Accuracy Low (struggles with noise/distortion) Very High (uses human or AI farms) Cost Pay-per-solve Best For Simple text-based images reCAPTCHA v2/v3, hCaptcha, FunCaptcha 4. Usage Considerations
Configuration: API-based libraries typically require an API_KEY and an instance creation (e.g., solver = Solvecaptcha('YOUR_API_KEY')).
Ethics & Policies: Automated CAPTCHA solving must comply with the Target's Terms of Service. Many platforms, including GitHub, use CAPTCHAs specifically to prevent unauthorized bot activity.
Python has become the primary language for automating CAPTCHA solving due to its rich ecosystem of AI libraries and integration with GitHub-hosted tools. Whether you are handling legacy image puzzles or modern invisible challenges like reCAPTCHA v3 and Cloudflare Turnstile, GitHub provides both ready-to-use SDKs for commercial services and open-source OCR (Optical Character Recognition) frameworks. Top Python CAPTCHA Solvers on GitHub (2026)
The following repositories are currently leading the market in terms of performance, maintenance, and community support:
CapSolver Python SDK: Widely regarded as a top choice for speed and reliability, particularly for Cloudflare challenges and Amazon WAF.
SolveCaptcha SDK: A modern, lightweight library supporting async/await, designed for seamless integration with browser automation tools like Selenium and Playwright.
Anti-Captcha Official: A veteran service with a highly stable API that uses a hybrid of AI and human workers for 99.9% uptime.
Simple-CAPTCHA-Solver: An open-source project ideal for lightweight image-based CAPTCHAs, using PIL (Pillow) and basic pixel comparison for local processing.
Puzzle-Captcha-Solver: Specializes in solving slide-based puzzle CAPTCHAs for platforms like TikTok and Binance using OpenCV for image detection. How to Implement a CAPTCHA Solver in Python
Implementing these tools typically follows one of two paths: using a professional API service or building a local OCR pipeline.
1. Using an API-Based Solver (Recommended for reCAPTCHA/Cloudflare)
API services are the most reliable for modern challenges because they handle rotating browser fingerprints and behavioral scoring. Stars: ~300 | Language: Python Tesseract is a
# Example using solvecaptcha-python SDK from solvecaptcha import Solvecaptcha # Initialize the solver with your API key solver = Solvecaptcha('YOUR_API_KEY') # Solve a reCAPTCHA v2 result = solver.recaptcha_v2( site_key='SITE_KEY_HERE', page_url='https://example.com' ) print(f"Solved Token: result['code']") Use code with caution. Installation: pip install solvecaptcha-python. 2. Local OCR Solver (For Simple Text/Images)
If you are dealing with basic, non-distorted images, you can use local libraries to avoid API costs.
Finding a reliable Python CAPTCHA solver on GitHub typically involves choosing between two main strategies: using OCR-based libraries for simple text images or integrating third-party API services for complex challenges like reCAPTCHA. Popular GitHub Repositories and Libraries
Solvecaptcha-Python: A client library designed to integrate with CAPTCHA solving services via an API key.
Simple CAPTCHA Solver: An educational project that demonstrates how to solve basic image-based CAPTCHAs by comparing pixel differences.
Captcha-Text-Extraction: A repository focused on using OpenCV and contours to isolate characters for machine learning prediction. Common Approaches
OCR and Image Processing: For basic text-based CAPTCHAs, developers often combine Pytesseract (an OCR tool) with OpenCV to clean and threshold images before extraction.
API Integration: For advanced challenges (v2/v3, hCaptcha), tools like the 2Captcha Python library are preferred. They outsource the solving process to a service that returns a token for submission.
Browser Automation: Tools like Selenium are frequently used to handle the web interaction while these libraries process the underlying challenge. Implementation Example (OCR Approach) For a simple text-based CAPTCHA, a basic workflow involves: Read the image using OpenCV. Apply thresholding to convert it to black and white. Find contours to identify individual characters. Extract text using a library like Tesseract.
Note on Ethics: While using a CAPTCHA solver is not inherently illegal, using it to scrape data from sites that explicitly forbid it in their Terms of Service may lead to IP bans or legal issues. simple CAPTCHA solver in python - GitHub
Searching for "captcha solver python github" reveals two main ways to handle CAPTCHAs in your code: using specialized API libraries (fast and reliable) or building a custom OCR solver (no cost, but high maintenance). 1. Popular GitHub Libraries (API-Based)
These are the most reliable for modern CAPTCHAs (reCAPTCHA, hCaptcha) because they send the challenge to a solving service.
2captcha-python: The official Python SDK for the 2Captcha service. It supports virtually every challenge type, including canvas and rotating images.
solvercaptcha-python: A streamlined library for integrating SolverCaptcha into automation scripts.
metabypass-python: Provides a quick setup for the MetaBypass API, often used in Selenium or Playwright workflows. Basic Implementation Example:
from twocaptcha import TwoCaptcha solver = TwoCaptcha('YOUR_API_KEY') result = solver.normal('path/to/captcha.jpg') print(result['code']) Use code with caution. Copied to clipboard 2. Custom OCR Solvers (Self-Hosted)
If you are dealing with simple, old-school text CAPTCHAs (distorted text on a plain background), you can use Python's image processing tools directly. Have you built a CAPTCHA solver using a
Tesseract OCR (pytesseract): The gold standard for text recognition. You’ll often need to use OpenCV first to remove "noise" (lines or dots) from the image.
Simple Captcha Solver: A lightweight GitHub project that demonstrates how to solve basic CAPTCHAs by comparing pixel differences between letters. 3. Automation Tools for Capturing Challenges
Before you can solve a CAPTCHA, you have to extract it from the web page.
Selenium: Used to find the CAPTCHA element and take a screenshot of it or grab its src URL.
Undetected Chromedriver: A modified Selenium driver that helps prevent CAPTCHAs from appearing in the first place by mimicking a real human browser more effectively. Quick Comparison Table Approach Reliability API SDKs Paid (per solve) reCAPTCHA v2/v3, hCaptcha, FunCaptcha Tesseract/OCR Low-Medium Simple numeric/text CAPTCHAs Machine Learning Time-Intensive High-volume, specific fixed patterns If you'd like to proceed, let me know:
What type of CAPTCHA are you trying to solve? (Text, reCAPTCHA checkboxes, image puzzles?)
Are you using a browser automation tool like Selenium or just making Requests?
Do you prefer a paid API (easier) or a free local script (harder)? I can provide a specific code snippet based on your choice.
Python libraries and GitHub repositories for solving CAPTCHAs generally fall into two categories: API wrappers for paid services (like 2Captcha or Anti-Captcha) and OCR/AI-based local solvers 1. Official API Wrappers (Paid Services)
These libraries connect your Python script to external services that solve CAPTCHAs using human workers or advanced AI. 2captcha-python : The official Python SDK for
. It supports nearly all types, including reCAPTCHA (v2/v3), hCaptcha, and FunCaptcha. anticaptcha-python : The official library for Anti-Captcha
. It provides a unified API to handle various challenges like Cloudflare Turnstile and Amazon WAF. solvecaptcha-python : A newer client for integrating with the SolverCaptcha 2. Local & Lightweight OCR Solvers
These tools attempt to solve specific text-based or image-based CAPTCHAs locally on your machine without external API costs. amazoncaptcha
: A highly specialized, lightweight library designed specifically to solve Amazon's image CAPTCHAs with high accuracy. simple-CAPTCHA-solver : A classic example of a Python solver using the PIL (Pillow)
library to segment letters and match them against a known alphabet. MathCaptchaSolver
: A tool specifically designed to solve math-based CAPTCHAs (e.g., "5 + 2 = ?") by extracting and calculating the expression. : A bypass tool that leverages the Google Cloud Vision API to recognize and extract text from images for automation. 3. AI & Deep Learning Approaches
For more complex, distorted text, researchers use machine learning models like TensorFlow or PyTorch.
print(f"Captcha Text: solve_local_captcha('captcha.png')")
Before diving into the code, it is important to distinguish between the two main approaches found on GitHub: