Metadata-Version: 2.1
Name: py-agender
Version: 0.0.5
Summary: Simple opencv & tensorflow based solution to estimate Faces, Age and Gender on pictures
Home-page: https://github.com/aristofun/py-agender
Author: Michael Butlitsky
Author-email: aristofun@yandex.ru
License: UNKNOWN
Description: # Face Age & Gender detection tool
        Simple opencv & tensorflow solution to estimate Age and Gender in your 
        next project. Command line or Python DIY style. 
        
        Based on and forked from: https://github.com/yu4u/age-gender-estimation
        
        Good enough for pet-projects and prototypes, but not ready for production 
        real-life applications
        
        ## How
        
        ```commandline
        pip3 install py-agender
        ```
        
        R equired dry-run for weights download:
        
        ```commandline
        py-agender  
        ```
        
        Warning — ~190MB download (pretrained network is heavy).
        
        CLI: 
        
        ```commandline
        py-agender PATH_TO_IMAGE
        ```
        
        Python:
        
        ```python
        from pyagender import PyAgender
        
        agender = PyAgender() 
        # see available options in __init__() src
        
        faces = agender.detect_genders_ages(cv2.imread(MY_IMAGE))
        # [
        #   {left: 34, top: 11, right: 122, bottom: 232, width:(r-l), height: (b-t), gender: 0.67, age: 23.5},
        #   ...
        # ]
        
        # Additional options & methods in PyAgender source
        ``` 
        
        Don't forget to download pretrained weights if using source code DIY style.
        
        ## TODO: 
        - add options (like STDIN input, output formatters etc.) for useful commandline 
        applications 
        - add help output
        - train better network with higher image resolution
        
        ## Tests
        
        ```commandline
        python3 -m unittest 
        ```
        
        ## Dependencies
        - Python 3.5, 3.6
        - numpy ~> 1.15
        - Keras ~> 2.2
        - TensorFlow ~> 1.9
        - opencv-python ~> 3.4.2+contrib
        
        Tested on:
        - MacOS 10.13 high Sierra without GPU (you're welcome to update & contribute!)
        
        
        # Model
        
        These weigts are from https://github.com/yu4u/age-gender-estimation
        on first console version run they are cached in **./pyagender.pretrained_models** folder:
        
        https://github.com/yu4u/age-gender-estimation/releases/download/v0.5/weights.28-3.73.hdf5
        
        # License
        
        This project is released under the MIT license.
        
        However, [the IMDB-Wiki dataset](https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/) used for pretrained network above is originally provided under the following conditions:
        
        > Please notice that this dataset is made available for academic research purpose only. All the images are collected from the Internet, and the copyright belongs to the original owners. If any of the images belongs to you and you would like it removed, please kindly inform us, we will remove it from our dataset immediately.
        
        Refer to fresh IMDB-Wiki dataset License and act accordingly.
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Environment :: Console
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
