Update app.py

app.py

@@ -106,30 +106,31 @@ def process(image):
     orig_image = Image.fromarray(image)
     w,h = orig_im_size = orig_image.size
     image = resize_image(orig_image)
-    im_np = np.array(image)
-    im_tensor = torch.tensor(im_np, dtype=torch.float32).permute(2,0,1)
-    im_tensor = torch.unsqueeze(im_tensor,0)
-    im_tensor = torch.divide(im_tensor,255.0)
-    im_tensor = normalize(im_tensor,[0.5,0.5,0.5],[1.0,1.0,1.0])
-    if torch.cuda.is_available():
-        im_tensor=im_tensor.cuda()
-
-    #inference
-    result=net(im_tensor)
-    # post process
-    result = torch.squeeze(F.interpolate(result[0][0], size=(h,w), mode='bilinear') ,0)
-    ma = torch.max(result)
-    mi = torch.min(result)
-    result = (result-mi)/(ma-mi)    
-    # image to pil
-    im_array = (result*255).cpu().data.numpy().astype(np.uint8)
-    pil_im = Image.fromarray(np.squeeze(im_array))
-    # paste the mask on the original image
-    new_im = Image.new("RGBA", pil_im.size, (0,0,0,0))
-    new_im.paste(orig_image, mask=pil_im)
-    # new_orig_image = orig_image.convert('RGBA')
-
-    return new_im
+    return image
+    # im_np = np.array(image)
+    # im_tensor = torch.tensor(im_np, dtype=torch.float32).permute(2,0,1)
+    # im_tensor = torch.unsqueeze(im_tensor,0)
+    # im_tensor = torch.divide(im_tensor,255.0)
+    # im_tensor = normalize(im_tensor,[0.5,0.5,0.5],[1.0,1.0,1.0])
+    # if torch.cuda.is_available():
+    #     im_tensor=im_tensor.cuda()
+
+    # #inference
+    # result=net(im_tensor)
+    # # post process
+    # result = torch.squeeze(F.interpolate(result[0][0], size=(h,w), mode='bilinear') ,0)
+    # ma = torch.max(result)
+    # mi = torch.min(result)
+    # result = (result-mi)/(ma-mi)    
+    # # image to pil
+    # im_array = (result*255).cpu().data.numpy().astype(np.uint8)
+    # pil_im = Image.fromarray(np.squeeze(im_array))
+    # # paste the mask on the original image
+    # new_im = Image.new("RGBA", pil_im.size, (0,0,0,0))
+    # new_im.paste(orig_image, mask=pil_im)
+    # # new_orig_image = orig_image.convert('RGBA')
+
+    # return new_im
 
 
 title = """<h1 style="text-align: center;">Product description generator</h1>"""