Update app.py

app.py

@@ -2,17 +2,7 @@ import gradio as gr
 import numpy as np
 import tensorflow as tf
 import PIL
-import os
 
-'''
-def sepia(input_img):
-  sepia_filter = np.array([[.393, .769, .189],
-                           [.349, .686, .168],
-                           [.272, .534, .131]])
-  sepia_img = input_img.dot(sepia_filter.T)
-  sepia_img /= sepia_img.max()                          
-  return sepia_img
- '''
  
 def normalize_img(img):
     img = tf.cast(img, dtype=tf.float32)
@@ -29,15 +19,6 @@ def predict_and_save(img, generator_model):
 def run(image_path):
     model = tf.keras.models.load_model('pretrained')  
     print("Model loaded")
-    '''
-    img = tf.keras.preprocessing.image.load_img(
-        image_path, target_size=(256, 256)
-    )
-    
-    img_array = tf.keras.preprocessing.image.img_to_array(img)
-    img_array = tf.expand_dims(img_array, 0) 
-    '''
-    #predict_and_save(img_array, model)
     img_array = tf.expand_dims(image_path, 0)
     im = predict_and_save(img_array, model)
     print("Prediction Done")