Visual Inspection Code-Along

What you learned: To load and preprocess data

• Load data using an image datastore
• TheimageDatastorefunction automatically labels the images based on folder names
• You can augment your dataset by adding images of different scale and rotation
• Image-based apps can significantly speed up common preprocessing tasks like cropping, labeling, and registering images

What you learned: To import a deep learning model and modify it for transfer learning

• Use a variety of pretrained models as a starting point for transfer learning
• Use Deep Network Designer app to interactively alter the model for a new task
• Import models and architectures from TensorFlow™-Keras, TensorFlow 2, Caffe, and the ONNX™ (Open Neural Network Exchange) model format

What you learned: To modify a model for learning

• Choose from a variety of training options, which change the training results
• Models can take a long time to train depending on hardware and dataset size
• Perform deep learning without needing to learn how to create a model from scratch

What you learned: To test the model on new data

• Classify the test data (set aside in step 1) and calculate the classification accuracy
• Visualize the test data with corresponding labels to ensure model accuracy on new data
• Use Explainable AI techniques like GradCAM to visualize where in the image the model detected a defect.