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It can be tested with the model generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
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')
please uncomment the part you want to test
x_sinh_1 = tf.sinh(x)
x_out = tf.divide(x_sinh_1, 1.176) # sinh(1.0)
x_cosh_1 = tf.cosh(x)
x_out = tf.divide(x_cosh_1, 1.55) # cosh(1.0)
x_tanh_1 = tf.tanh(x)
x__out = tf.divide(x_tanh_1, 0.77) # tanh(1.0)
x_asinh_1 = tf.asinh(x)
x_out = tf.divide(x_asinh_1, 0.89) # asinh(1.0/1.1)
x_acosh_1 = tf.add(x, 1.1)
x_acosh_2 = tf.acosh(x_acosh_1) # accept (1, inf)
x_out = tf.divide(x_acosh_2, 1.4) # acosh(2.1)
x_atanh_1 = tf.divide(x, 1.1)
x_atanh_2 = tf.atanh(x_atanh_1) # accept (-1, 1)
x_out = tf.divide(x_atanh_2, 1.55) # atanhh(1.0/1.1)
y = tf.identity(x_out, name='dnn_out') #please only preserve the x_out you want to test
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: Ting Fu <ting.fu@intel.com>
FFmpeg README
FFmpeg is a collection of libraries and tools to process multimedia content such as audio, video, subtitles and related metadata.
Libraries
libavcodecprovides implementation of a wider range of codecs.libavformatimplements streaming protocols, container formats and basic I/O access.libavutilincludes hashers, decompressors and miscellaneous utility functions.libavfilterprovides a mean to alter decoded Audio and Video through chain of filters.libavdeviceprovides an abstraction to access capture and playback devices.libswresampleimplements audio mixing and resampling routines.libswscaleimplements color conversion and scaling routines.
Tools
- ffmpeg is a command line toolbox to manipulate, convert and stream multimedia content.
- ffplay is a minimalistic multimedia player.
- ffprobe is a simple analysis tool to inspect multimedia content.
- Additional small tools such as
aviocat,ismindexandqt-faststart.
Documentation
The offline documentation is available in the doc/ directory.
The online documentation is available in the main website and in the wiki.
Examples
Coding examples are available in the doc/examples directory.
License
FFmpeg codebase is mainly LGPL-licensed with optional components licensed under GPL. Please refer to the LICENSE file for detailed information.
Contributing
Patches should be submitted to the ffmpeg-devel mailing list using
git format-patch or git send-email. Github pull requests should be
avoided because they are not part of our review process and will be ignored.