Captcha Solver Python Github -

What are you trying to solve? (Text, reCAPTCHA checkboxes, image puzzles?)

This script loads a CAPTCHA image, preprocesses it to improve clarity, and then uses Tesseract to extract the text.

def build_cnn(input_shape=(28,28,1), n_classes=36): m = models.Sequential([ layers.Conv2D(32,3,activation='relu',input_shape=input_shape), layers.MaxPool2D(), layers.Conv2D(64,3,activation='relu'), layers.MaxPool2D(), layers.Flatten(), layers.Dense(128,activation='relu'), layers.Dense(n_classes,activation='softmax') ]) m.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) return m captcha solver python github

For enterprise-grade defenses like reCAPTCHA v3 or Cloudflare Turnstile, local OCR will fail. The industry standard is to use a CAPTCHA solving API (like 2Captcha, Anti-Captcha, or CapSolver) via their official or community-maintained Python SDKs on GitHub.

Method B: Machine Learning & Computer Vision (Best for Sliders & Objects) What are you trying to solve

Struggles with complex backgrounds, overlapping lines, or behavioral CAPTCHAs.

A core challenge for Python developers is that many of these modern CAPTCHAs are designed to be executed within a real web browser environment. Therefore, most Python solutions rely heavily on browser automation tools like and Playwright to interact with the CAPTCHA widgets naturally. The industry standard is to use a CAPTCHA

One of the oldest and most reliable client libraries for interacting with the Anti-Captcha API.

Many public repositories demonstrate how to click the "Audio Challenge" button on ReCAPTCHA or hCaptcha, download the .mp3 payload, and pass it to Python's SpeechRecognition library (using the PocketSphinx or Google Speech API) to get the text response.

# Apply OCR text = pytesseract.image_to_string(img)

Implement randomized delay intervals ( time.sleep() ) between web requests to break predictable traffic signatures.