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N
ffmpeg-0.6.3
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v0.5
v0.5.1
v0.5.2
v0.5.3
v0.6
v0.6.1
${ noResults }
Guo, Yejun
71e28c5422
it can be tested with model file generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.minimum(0.7, x)
x2 = tf.maximum(x1, 0.4)
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
|
5 years ago | |
|---|---|---|
| .. | ||
| convert.py | convert_from_tensorflow.py: add option to dump graph for visualization in tensorboard | 5 years ago |
| convert_from_tensorflow.py | dnn/native: add native support for minimum | 5 years ago |
| convert_header.py | dnn/native: add native support for minimum | 5 years ago |