Training a new image recognition from scratch requires a lot of time and computational power. If we can take a prior-trained network and retrain it with our images, it may save us computational time. For this recipe, we will show how to use a pre-trained TensorFlow image recognition model and fine-tune it to work on a different set of images.
Retraining existing CNN models
Getting ready
The idea is to reuse the weights and structure of a prior model from the convolutional layers and retrain the fully connected layers at the top of the network.
TensorFlow has created a tutorial about training on top of existing CNN models (refer to the first bullet point in the next See also section). In this recipe, we will illustrate how...
