Update app.py

app.py

@@ -66,11 +66,12 @@ carTransforms = transforms.Compose([transforms.Resize(224),
 
 def classifyCar(im):
   im = Image.fromarray(im.astype('uint8'), 'RGB')
-  im = carTransforms(im).unsqueeze(0)  # transform and add batch dimension
   with torch.no_grad():
     outputs = predictor(im)
     v = Visualizer(im[:, :, ::-1], MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), scale=1.2)
     out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
+  im = carTransforms(im).unsqueeze(0)  # transform and add batch dimension
+  with torch.no_grad():
     scores = torch.nn.functional.softmax(DesignModernityModel(im)[0])
   return Image.fromarray(np.uint8(out.get_image())).convert('RGB'), {LABELS[i]: float(scores[i]) for i in range(n_labels)}