Update main.py

main.py

@@ -1,11 +1,11 @@
-import gradio as gd
+import gradio as gr
 import torch
-from torchvision import
+from torchvision import models, transforms
 
 # -- get torch and cuda version
 TORCH_VERSION = ".".join(torch.__version__.split(".")[:2])
 CUDA_VERSION = torch.__version__.split("+")[-1]
-
+'''
 # -- install pre-build detectron2
 !pip install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/{CUDA_VERSION}/{TORCH_VERSION}/index.html
 
@@ -36,7 +36,7 @@ outputs = predictor(im)
 
 print(outputs["instances"].pred_classes)
 print(outputs["instances"].pred_boxes)
-
+'''
 # -- load Mask R-CNN model for segmentation
 DesignModernityModel = torch.load("DesignModernityModel.pt")
 
@@ -45,12 +45,9 @@ DesignModernityModel = torch.load("DesignModernityModel.pt")
 
 DesignModernityModel.eval() # set state of the model to inference
 
-LABELS = ['2003-2006', 'VW Up!']
+LABELS = ['2000-2004', '2006-2008', '2009-2011', '2012-2015', '2016-2018']
 
-carTransforms = transforms.Compose([
-			transforms.RandomResizedCrop(224),
-			...
-])
+carTransforms = transforms.Compose([transforms.Resize(224)])
 
 def classifyCar(im):
   im = Image.fromarray(im.astype('uint8'), 'RGB')