Update app.py

app.py

@@ -28,17 +28,21 @@ def get_image(path):
     return img
     
 def preprocess(img):
-    img = img / 255.
-    img = cv2.resize(img, (256, 256))
-    h, w = img.shape[0], img.shape[1]
-    y0 = (h - 224) // 2
-    x0 = (w - 224) // 2
-    img = img[y0 : y0+224, x0 : x0+224, :]
-    img = (img - [0.485, 0.456, 0.406]) / [0.229, 0.224, 0.225]
-    img = np.transpose(img, axes=[2, 0, 1])
-    img = img.astype(np.float32)
-    img = np.expand_dims(img, axis=0)
+    '''
+    Preprocessing required on the images for inference with mxnet gluon
+    The function takes path to an image and returns processed tensor
+    '''
+    transform_fn = transforms.Compose([
+    transforms.Resize(224),
+    transforms.CenterCrop(224),
+    transforms.ToTensor(),
+    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+    ])
+    img = transform_fn(img)
+    img = img.expand_dims(axis=0) # batchify
+
     return img
+    
 
 def predict(path):
     img = get_image(path)