31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
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import cv2
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import numpy as np
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import tensorflow as tf
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cap=cv2.VideoCapture(0)
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np.set_printoptions(formatter={'float': '{:0.3f}'.format})
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with tf.Session() as s:
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saver=tf.train.import_meta_graph('./mon_vgg/modele.meta')
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saver.restore(s, tf.train.latest_checkpoint('./mon_vgg/'))
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graph=tf.get_default_graph()
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images=graph.get_tensor_by_name("images:0")
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sortie=graph.get_tensor_by_name("sortie:0")
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is_training=graph.get_tensor_by_name("is_training:0")
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while True:
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ret, frame=cap.read()
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test=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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test=cv2.resize(test, (28, 28))
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for x in range(28):
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for y in range(28):
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if test[y][x]<110:
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test[y][x]=1
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else:
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test[y][x]=0
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cv2.imshow('image', cv2.resize(test, (120, 120))*255)
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prediction=s.run(sortie, feed_dict={images: [test.reshape(28, 28, 1)], is_training: False})
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print(prediction, np.argmax(prediction))
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if cv2.waitKey(20)&0xFF==ord('q'):
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break
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cap.release()
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cv2.destroyAllWindows()
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