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https://git.videolan.org/git/ffmpeg.git
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f73cc61bf5
more math unary operations will be added here
It can be tested with the model file generated with below python scripy:
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')
x1 = tf.subtract(x, 0.5)
x2 = tf.abs(x1)
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: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
39 lines
1.5 KiB
C
39 lines
1.5 KiB
C
/*
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* Copyright (c) 2019 Guo Yejun
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*
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* This file is part of FFmpeg.
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*
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* FFmpeg is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*
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* FFmpeg is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with FFmpeg; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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#include <string.h>
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#include "dnn_backend_native_layers.h"
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#include "dnn_backend_native_layer_pad.h"
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#include "dnn_backend_native_layer_conv2d.h"
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#include "dnn_backend_native_layer_depth2space.h"
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#include "dnn_backend_native_layer_maximum.h"
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#include "dnn_backend_native_layer_mathbinary.h"
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#include "dnn_backend_native_layer_mathunary.h"
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LayerFunc layer_funcs[DLT_COUNT] = {
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{NULL, NULL},
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{dnn_execute_layer_conv2d, dnn_load_layer_conv2d},
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{dnn_execute_layer_depth2space, dnn_load_layer_depth2space},
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{dnn_execute_layer_pad, dnn_load_layer_pad},
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{dnn_execute_layer_maximum, dnn_load_layer_maximum},
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{dnn_execute_layer_math_binary, dnn_load_layer_math_binary},
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{dnn_execute_layer_math_unary, dnn_load_layer_math_unary},
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};
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