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Exercise

Running semantic segmentation

Good job designing the U-Net! You will find an already pre-trained model very similar to the one you have just built available to you. This model has been trained on a large set of images and contains a few small additions to the architecture, such as the batch norm layers.

You can instantiate the model as UNet(), which will provide the model with the pre-trained weights. You task is to use it to produce segmentation masks for the following image of a car.

car image

Image from PIL has already been imported for you.

Instructions

100 XP
  • Instantiate UNet() in a variable called model.
  • Load the image at car.jpg to a variable called image.
  • Produce segmentation masks by passing the image to the model and squeeze(0)-ing the output.