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dnn_backend_native_layer_mathunary: add atan support

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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')
x1 = tf.atan(x)
x2 = tf.divide(x1, 3.1416/4) # pi/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: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>
This commit is contained in:
Ting Fu 2020-06-18 17:15:35 +08:00 committed by Guo, Yejun
parent 130c600144
commit 13f5613e68
4 changed files with 7 additions and 2 deletions
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4
libavfilter/dnn/dnn_backend_native_layer_mathunary.c
View File

@ -100,6 +100,10 @@ int dnn_execute_layer_math_unary(DnnOperand *operands, const int32_t *input_oper
for (int i = 0; i < dims_count; ++i) for (int i = 0; i < dims_count; ++i)
dst[i] = acos(src[i]); dst[i] = acos(src[i]);
return 0; return 0;
case DMUO_ATAN:
for (int i = 0; i < dims_count; ++i)
dst[i] = atan(src[i]);
return 0;
default: default:
return -1; return -1;
} }

1
libavfilter/dnn/dnn_backend_native_layer_mathunary.h
View File

@ -36,6 +36,7 @@ typedef enum {
DMUO_TAN = 3, DMUO_TAN = 3,
DMUO_ASIN = 4, DMUO_ASIN = 4,
DMUO_ACOS = 5, DMUO_ACOS = 5,
DMUO_ATAN = 6,
DMUO_COUNT DMUO_COUNT
} DNNMathUnaryOperation; } DNNMathUnaryOperation;

2
tools/python/convert_from_tensorflow.py
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@ -72,7 +72,7 @@ class TFConverter:
self.conv2d_scopename_inputname_dict = {} self.conv2d_scopename_inputname_dict = {}
self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4, 'MathBinary':5, 'MathUnary':6} self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4, 'MathBinary':5, 'MathUnary':6}
self.mathbin2code = {'Sub':0, 'Add':1, 'Mul':2, 'RealDiv':3, 'Minimum':4} self.mathbin2code = {'Sub':0, 'Add':1, 'Mul':2, 'RealDiv':3, 'Minimum':4}
self.mathun2code = {'Abs':0, 'Sin':1, 'Cos':2, 'Tan':3, 'Asin':4, 'Acos':5} self.mathun2code = {'Abs':0, 'Sin':1, 'Cos':2, 'Tan':3, 'Asin':4, 'Acos':5, 'Atan':6}
self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2} self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2}
self.name_operand_dict = {} self.name_operand_dict = {}

2
tools/python/convert_header.py
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@ -23,4 +23,4 @@ str = 'FFMPEGDNNNATIVE'
major = 1 major = 1
# increase minor when we don't have to re-convert the model file # increase minor when we don't have to re-convert the model file
minor = 11 minor = 12