Update app.py

app.py

@@ -61,16 +61,17 @@ n_labels = len(LABELS)
 MEAN = [0.485, 0.456, 0.406]
 STD = [0.229, 0.224, 0.225]
 
-carTransforms = transforms.Compose([transforms.Resize(224),
-                                    transforms.ToTensor(),
-                                    transforms.Normalize(mean=MEAN, std=STD)])
+carTransforms = transforms.Compose([transforms.Resize(224)]
+                                    #transforms.ToTensor(),
+                                    #transforms.Normalize(mean=MEAN, std=STD)])
 
 def classifyCar(im):
   #im = Image.fromarray(im.astype('uint8'), 'RGB')
   try:
     im = cv2.imread(im)
+    im = carTransforms(im)
   except:
-    return im, {"error0": 0.5}
+    return im, {"error0": im.shape}
   try:
     with torch.no_grad():
       outputs = predictor(im)