Python Image Processing Cookbook

How to do it...

Run the following steps to implement fine-tuning (with transfer learning) using keras.

1. Define the train and test directories along with the size that the input images will get resized to before training:

train_dir = 'images/flower_photos/train'test_dir = 'images/flower_photos/test'image_size = 224

2. Load the pretrained VGG16 network, but without the top FC layers:

vgg_conv = VGG16(weights='imagenet', include_top=False, input_shape=(image_size, image_size, 3))

3. Freeze all the convolutional layers except the last two convolutional layers, along with the FC layers, to reuse the pretrained weights for those layers (without retraining them):

for layer in vgg_conv.layers[:-2]:     layer.trainable = False 

4. Now let's verify the status ...