Update app.py

app.py

@@ -30,23 +30,21 @@ def get_image(path):
         img = np.array(img.convert('RGB'))
     return img
     
+    
 def preprocess(img):
     '''
     Preprocessing required on the images for inference with mxnet gluon
-    The function takes path to an image and returns processed tensor
+    The function takes loaded 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 = mxnet.ndarray.array(img)
-    img = transform_fn(img)
-    img = img.expand_dims(axis=0) # batchify
+    img = np.array(Image.fromarray(img).resize((224, 224))).astype(np.float32)
+    img[:, :, 0] -= 123.68
+    img[:, :, 1] -= 116.779
+    img[:, :, 2] -= 103.939
+    img[:,:,[0,1,2]] = img[:,:,[2,1,0]]
+    img = img.transpose((2, 0, 1))
+    img = np.expand_dims(img, axis=0)
 
-    return img.asnumpy()
-    
+    return img
 
 def predict(path):
     img = get_image(path)