Metadata-Version: 2.1
Name: CaptchaCracker
Version: 0.0.2
Summary: CaptchaCracker
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
        
        - Before execution, training data image files in which the actual value of the Captcha image is indicated in the following file names should be prepared.
        
        ![png](https://github.com/WooilJeong/CaptchaCracker/raw/main/assets/example02.png)
        
        
        ### Train and save the model
        
        ```python
        import glob
        from CaptchaCracker import CreateModel
        
        train_img_path = glob.glob("../data/train_numbers_only/*.png")
        
        CM = CreateModel(train_img_path)
        model = CM.train_model(epochs=100)
        model.save_weights("../model/weights.h5")
        
        ```
        
        ### Load a saved model to make predictions
        
        ```python
        from CaptchaCracker import ApplyModel
        
        target_img_path = "../data/target.png"
        
        AM = ApplyModel(target_img_path)
        AM.load_saved_weights("../model/weights.h5")
        
        pred = AM.predict()
        
        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
