Metadata-Version: 2.1
Name: CaptchaCracker
Version: 0.0.4
Summary: CaptchaCracker is an open source Python library that provides functions to create and apply deep learning models for Captcha Image recognition.
Home-page: https://github.com/WooilJeong/CaptchaCracker
Author: Wooil Jeong
Author-email: wooil@kakao.com
License: MIT
Description: # CaptchaCracker
        
        ![](https://img.shields.io/badge/TensorFlow-2.5.0-red.svg)
        ![](https://img.shields.io/badge/NumPy-1.19.5-blue.svg)
        [![Linkedin Badge](https://img.shields.io/badge/-WooilJeong-blue?style=plastic&logo=Linkedin&logoColor=white&link=https://www.linkedin.com/in/wooil/)](https://www.linkedin.com/in/wooil/) 
        
        [한국어 문서](https://github.com/WooilJeong/CaptchaCracker/blob/main/README-ko.md)
        
        ## Introduction
        
        CaptchaCracker is an open source Python library that provides functions to create and apply deep learning models for Captcha Image recognition. You can create a deep learning model that recognizes numbers in the Captcha Image as shown below and outputs a string of numbers, or you can try the model yourself.
        
        
        ### Input
        
        ![png](https://github.com/WooilJeong/CaptchaCracker/raw/main/assets/example01.png)
        
        
        ### Output
        
        ```
        023062
        ```
        
        
        ## Installation
        
        ```bash
        pip install CaptchaCracker
        ```
        
        ## Dependency
        
        ```
        pip install numpy==1.19.5 tensorflow==2.5.0
        ```
        
        ## Examples
        
        ### Train and save the model
        
        Before executing model training, training data image files in which the actual value of the Captcha image is indicated in the file name should be prepared as shown below.
        
        - [Download Sample Dataset](https://github.com/WooilJeong/CaptchaCracker/raw/main/sample.zip)
        
        ![png](https://github.com/WooilJeong/CaptchaCracker/raw/main/assets/example02.png)
        
        
        ```python
        import glob
        from CaptchaCracker import CreateModel
        
        train_img_path_list = glob.glob("../data/train_numbers_only/*.png")
        
        CM = CreateModel(train_img_path_list)
        model = CM.train_model(epochs=100)
        model.save_weights("../model/weights.h5")
        
        ```
        
        ### Load a saved model to make predictions
        
        ```python
        from CaptchaCracker import ApplyModel
        
        weights_path = "../model/weights.h5"
        AM = ApplyModel(weights_path)
        
        target_img_path = "../data/target.png"
        pred = AM.predict(target_img_path)
        print(pred)
        ```
        
        
        ## References
        
        - https://keras.io/examples/vision/captcha_ocr/
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
