Update app.py

app.py

@@ -18,7 +18,7 @@ import numpy as np
 #import requests
 #import tarfile
 
-MODEL_PATH='Nst_model'
+#MODEL_PATH='Nst_model'
 
 # Disable scientific notation for clarity
 np.set_printoptions(suppress=True)
@@ -39,7 +39,7 @@ def tensor_to_image(tensor):
 
 
 
-"""## Grayscaling image for testing purpose to check if we could get better results."""
+"""## Grayscaling image for testing purpose to check if we could get better results.
 def gray_scaled(inp_img):
   gray = cv2.cvtColor(inp_img, cv2.COLOR_BGR2GRAY)
   gray_img = np.zeros_like(inp_img)
@@ -47,13 +47,14 @@ def gray_scaled(inp_img):
   gray_img[:,:,1] = gray
   gray_img[:,:,2] = gray
   return gray_img
+ """
 
 ##Transformation 
-def transform_mymodel(content_image,style_image):
+def transform_my_model(content_image,style_image):
   # Convert to float32 numpy array, add batch dimension, and normalize to range [0, 1]
   #content_image=gray_scaled(content_image)
-  content_image = content_image.astype(np.float32)[np.newaxis, ...] / 255.0
-  style_image = style_image.astype(np.float32)[np.newaxis, ...] / 255.0
+  content_image = content_image.astype(np.float32)[np.newaxis, ...] / 255.
+  style_image = style_image.astype(np.float32)[np.newaxis, ...] / 255.
  
   #Resizing image
   #style_image = tf.image.resize(style_image, (256, 256))
@@ -66,17 +67,11 @@ def transform_mymodel(content_image,style_image):
   stylized_image =tensor_to_image(stylized_image)
   return stylized_image
 
-def gradio_intrface(mymodel):
-# Initializing the input component 
-  image1 = gr.inputs.Image(label="Content Image") #CONTENT IMAGE
-  image2 = gr.inputs.Image(label="Style Image") #STYLE IMAGE
-  stylizedimg=gr.outputs.Image(label="Result") 
-  gr.Interface(fn=mymodel, inputs= [image1,image2] , outputs= stylizedimg,title='Style Transfer',theme='seafoam',examples=[['Content_Images/contnt12.jpg','VG516.jpg']],article="References-\n\nExploring the structure of a real-time, arbitrary neural artistic stylization network. Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin.").launch()
 
-"""The function will be launched both  Inline and Outline  where u need to add a content and style image."""
-
-
-gradio_intrface(transform_mymodel)
+image1 = gr.inputs.Image(label="Content Image") #CONTENT IMAGE
+image2 = gr.inputs.Image(label="Style Image") #STYLE IMAGE
+stylizedimg=gr.outputs.Image(label="Result") 
+gr.Interface(fn=transform_my_model, inputs= [image1,image2] , outputs= stylizedimg,title='Style Transfer',theme='seafoam',examples=[['Content_Images/contnt12.jpg','VG516.jpg']],article="References-\n\nExploring the structure of a real-time, arbitrary neural artistic stylization network. Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin.").launch()