OpenCV 3 Computer Vision with Python Cookbook

How to do it...

You need to complete the following steps:

1. Import the modules:

import cv2import numpy as np

2. Load a model from Caffe and print the information about the types of layers used in the model:

net = cv2.dnn.readNetFromCaffe('../data/bvlc_googlenet.prototxt',                                '../data/bvlc_googlenet.caffemodel')if not net.empty():    print('Net loaded successfully\n')    print('Net contains:')for t in net.getLayerTypes():    print('\t%d layers of type %s' % (net.getLayersCount(t), t))

3. Get the tensor shapes for the loaded model and specified input shape. Then print all of the information:

layers_ids, in_shapes, out_shapes = net.getLayersShapes([1, 3, 224, 224])layers_names = net.getLayerNames()print('Net layers shapes:')for l in range(len(layers_names)): ...