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Exercise

Using a real world model

Okay, so Ivy's picture is ready to be used by ResNet50. It is stored in img_ready and now looks like this:

ResNet50 is a model trained on the Imagenet dataset that is able to distinguish between 1000 different labeled objects. ResNet50 is a deep model with 50 layers, you can check it in 3D here.

ResNet50 and decode_predictions have both been imported from tensorflow.keras.applications.resnet50 for you.

It's time to use this trained model to find out Ivy's breed!

Instructions

100 XP
  • Instantiate a ResNet50 model, setting the weights parameter to be 'imagenet'.
  • Use the model to predict on your processed image.
  • Decode the first 3 predictions with decode_predictions().