import gradio as gr 
import tensorflow as tf 
import keras 
import os 
import numpy as np
import matplotlib.pyplot as plt

#loading model 
cycleGen=tf.keras.models.load_model('cycle-gen-models/model')
cycleGen.load_weights('cycle-gen-models/weights')

def imageProcessing(img):
    #img=tf.io.read_file(img_path)
    img=tf.image.decode_jpeg(img,channels=3)
    img=tf.image.resize(img,[256,256])
    img=(img/127.5)-1
    img=tf.expand_dims(img,axis=0)
    
    return img

def image_change(inputs):
    img=imageProcessing(inputs)
    fake_monet,_,_,_=cycleGen((img,img),training=False)
    #prediction=(prediction * 127.5 + 127.5).astype(np.uint8)
    prediction=(fake_monet[0] * 127.5 + 127.5).numpy().astype(np.uint8)

    return prediction
    
Title="Monet Mimic image 🖌️🎨"

demo=gr.Interface(
    fn=image_change,
    inputs=gr.Image(type="filepath"),
    img=image_change(input),
    title=Title,
    outputs=gr.Image(img)
)

demo.launch()