April 2017
Intermediate to advanced
320 pages
7h 46m
English
Content preview from Deep Learning with TensorFlow
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Source code
The second part of the implemented classifier is listed here:
from scipy import misc import numpy as np import matplotlib.cm as cm import tensorflow as tf from matplotlib import pyplot as plt import matplotlib.image as mpimg import EmotionDetectorUtils from EmotionDetectorUtils import testResult def rgb2gray(rgb): return np.dot(rgb[...,:3], [0.299, 0.587, 0.114]) img = mpimg.imread('author_image.jpg') gray = rgb2gray(img) plt.imshow(gray, cmap = plt.get_cmap('gray')) plt.show() sess = tf.InteractiveSession() new_saver = tf.train.import_meta_graph('logs/model.ckpt-1000.meta') new_saver.restore(sess, 'logs/model.ckpt-1000') tf.get_default_graph().as_graph_def() x = sess.graph.get_tensor_by_name("input:0") y_conv = sess.graph.get_tensor_by_name("output:0") ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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