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author | Ting Fu <ting.fu@intel.com> | 2020-06-06 20:12:46 +0800 |
---|---|---|
committer | Guo Yejun <yejun.guo@intel.com> | 2020-06-11 11:10:51 +0800 |
commit | 0b6d3f0d838f1f28f30ccc25a08f539a53e58665 (patch) | |
tree | 48205aea2bf894dc7d1c42eb959ab32bded3b795 | |
parent | c33e56c7a6a8bef7d95e1d36eb2f35748d475695 (diff) | |
download | ffmpeg-0b6d3f0d838f1f28f30ccc25a08f539a53e58665.tar.gz |
dnn_backend_native_layer_mathunary: add sin support
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.multiply(x, 3.14)
x2 = tf.sin(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>
-rw-r--r-- | libavfilter/dnn/dnn_backend_native_layer_mathunary.c | 6 | ||||
-rw-r--r-- | libavfilter/dnn/dnn_backend_native_layer_mathunary.h | 1 | ||||
-rw-r--r-- | tools/python/convert_from_tensorflow.py | 2 | ||||
-rw-r--r-- | tools/python/convert_header.py | 2 |
4 files changed, 9 insertions, 2 deletions
diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c index d65af151cd..5324d15bc3 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c @@ -23,6 +23,8 @@ * DNN native backend implementation. */ +#include <math.h> + #include "dnn_backend_native.h" #include "libavutil/avassert.h" #include "dnn_backend_native_layer_mathunary.h" @@ -74,6 +76,10 @@ int dnn_execute_layer_math_unary(DnnOperand *operands, const int32_t *input_oper for (int i = 0; i < dims_count; ++i) dst[i] = FFABS(src[i]); return 0; + case DMUO_SIN: + for (int i = 0; i < dims_count; ++i) + dst[i] = sin(src[i]); + return 0; default: return -1; } diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathunary.h b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h index 4e44003b66..31a1ea8fb6 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.h +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h @@ -31,6 +31,7 @@ typedef enum { DMUO_ABS = 0, + DMUO_SIN = 1, DMUO_COUNT } DNNMathUnaryOperation; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index 8c0a9be7be..b17facdda8 100644 --- a/tools/python/convert_from_tensorflow.py +++ b/tools/python/convert_from_tensorflow.py @@ -72,7 +72,7 @@ class TFConverter: self.conv2d_scopename_inputname_dict = {} 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.mathun2code = {'Abs':0} + self.mathun2code = {'Abs':0, 'Sin':1} self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2} self.name_operand_dict = {} diff --git a/tools/python/convert_header.py b/tools/python/convert_header.py index ad4491729a..c79fef4be8 100644 --- a/tools/python/convert_header.py +++ b/tools/python/convert_header.py @@ -23,4 +23,4 @@ str = 'FFMPEGDNNNATIVE' major = 1 # increase minor when we don't have to re-convert the model file -minor = 6 +minor = 7 |