API_DeepLearning

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API_DeepLearning

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Usaremos Flask y Keras para montar un API que realiza clasificación de imágenes

API_DeepLearning 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# API_DeepLearning

Implementaremos una red neuronal usando keras-tensorflow y la ejecutaremos en un servicio web de flask

## 1. Preparación del entorno
    $ conda create -n APIDeep anaconda python=3.7.7
    $ conda activate APIDeep
    $ conda install ipykernel
    $ python -m ipykernel install --user --name APIDeep --display-name "APIDeep"
    $ conda install tensorflow-gpu==2.1.0 cudatoolkit=10.1
    $ pip install tensorflow==2.1.0
    $ pip install jupyter
    $ pip install keras==2.3.1
    $ pip install numpy scipy Pillow cython matplotlib scikit-image opencv-python h5py imgaug IPython[all]
    
 ## 2. Entrenar la red neuronal
 
    Descargar el repositorio
    Abrir terminal en la carpeta y correr jupyter notebook
    
    $ jupyter notebook
    
    Ejecutar BirdClass.ipynb
    
 ## 3. Probar la red neuronal
 
    $ python TestModel.py
    
## 4. Probar el API de Flask

$ python app.py

## Resultado

![API web Flask + Deep Learning](https://github.com/DavidReveloLuna/API_DeepLearning/blob/master/asssets/Resultado.jpg)

## Agradecimientos

Al trabajo de: 
[Krishnaik06](https://github.com/krishnaik06/Deployment-Deep-Learning-Model)

# **Canal de Youtube**
[Click aquì pare ver mi canal de YOUTUBE](https://www.youtube.com/channel/UCr_dJOULDvSXMHA1PSHy2rg)

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