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import numpy as np
import cv2, os
from PIL import Image
import tensorflow as tf
from keras.preprocessing import image
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.image import img_to_array, save_img, array_to_img
def generate_new_image(image_path, model_path, imageID = 0):
# Processing Image
img = cv2.imread(image_path)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
original_height, original_width = img.shape[:2]
img_arr = (img_to_array(img) - 127.5) / 127.5
resized = cv2.resize(img_arr, (256, 256), interpolation=cv2.INTER_AREA)
ready_img = np.expand_dims(resized, axis=0)
# Loading Model
model = load_model(model_path)
# Prdicting Image
pred = model.predict(ready_img)
pred = (cv2.medianBlur(pred[0], 1) + 1) / 2
pred = cv2.resize(pred, (original_width, original_height))
pred = array_to_img(pred)
final_image_path = f"captures/new_image_{imageID}.png"
save_img(final_image_path, pred)
return final_image_path
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