# OCR text = pytesseract.image_to_string(img, config='--psm 8') return text.strip()
| Feature | Look for | |---------|-----------| | Dependencies | requests , Pillow , pytesseract only | | Models | Pre-downloaded weights (not 500 MB) | | No GPU | CPU-only inference | | Active | Recent commits, open issues | captcha solver python github portable
These projects rely on a small SDK to send challenges to a remote server. Because the heavy processing happens elsewhere, the local footprint is minimal. For instance, using the solvercaptcha-python library only requires a simple pip install within your portable environment and a valid API key. 2. Local Deep Learning Models (True Offline Portability) # OCR text = pytesseract
: The automation tool types the string into the input field or performs the required click/slide action. Ethical & Legal Considerations | High | Low to Medium | |
| Type | How It Works | Portability | Accuracy | |------|--------------|-------------|----------| | | Extracts text from simple image CAPTCHAs using Tesseract or EasyOCR. | High | Low to Medium | | Deep Learning | Uses a CNN (Convolutional Neural Network) trained on thousands of samples. | Medium (requires heavy models) | Medium to High | | Audio-based | Converts audio challenges to text via speech recognition. | High | Medium (for noisy audio) | | Solver Services | Sends CAPTCHA to a paid service (2Captcha, Anti-Captcha) via API. | Very High (just HTTP requests) | Very High |
Use solvecaptcha-python or capsolver-python . These libraries are minimal and handle reCAPTCHA, hCaptcha, and image CAPTCHAs by sending them to a remote server.
