Question 1

How to train cnn_captcha on my own CAPTCHA images?

Accepted Answer

First, organize your images in the sample/origin directory with naming like 'label_serial.jpg', then modify conf/sample_config.json for parameters like char_set and image dimensions. Run verify_and_split_data.py to validate and split data, followed by train_model.py for training, as detailed in the README sections 2.1 to 2.4.

Question 2

cnn_captcha vs Tesseract for CAPTCHA recognition

Accepted Answer

cnn_captcha uses CNNs specifically optimized for character-based CAPTCHAs, offering higher accuracy on distorted text without complex pre-processing, while Tesseract is a general OCR that struggles with noise and segmentation. However, cnn_captcha requires training and setup, whereas Tesseract can be used out-of-the-box but with lower reliability for CAPTCHAs.

Question 3

What hardware is needed to run cnn_captcha efficiently?

Accepted Answer

Training benefits from a GPU with at least 2GB VRAM, as noted in the README's performance stats using a GTX 950, and sufficient RAM to handle batch sizes. For inference, CPU can work but GPU speeds up recognition, with the API handling multiple requests via Flask deployment.

Question 4

How to improve accuracy if cnn_captcha is failing on some CAPTCHAs?

Accepted Answer

Increase your training dataset size with more varied samples, adjust configuration parameters like char_set or image dimensions, and use the batch testing tools to identify weaknesses. The README suggests adding correctly labeled negative samples to enhance model robustness.

Question 5

Can cnn_captcha handle Chinese or multi-language CAPTCHAs?

Accepted Answer

Yes, but it requires generating a labels.json file using the collect_labels.py script and setting use_labels_json_file to true in the configuration. The README explains this in section 2.2 for handling non-standard character sets.

Question 6

Is cnn_captcha still maintained and updated?

Accepted Answer

The project's last significant update was in 2019, with no recent commits, so it may have unpatched bugs or compatibility issues with newer libraries. Users should be prepared to troubleshoot based on the existing documentation and community issues.

cnn_captcha

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