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authorTing Fu <ting.fu@intel.com>2020-06-06 20:12:46 +0800
committerGuo Yejun <yejun.guo@intel.com>2020-06-11 11:10:51 +0800
commit0b6d3f0d838f1f28f30ccc25a08f539a53e58665 (patch)
tree48205aea2bf894dc7d1c42eb959ab32bded3b795
parentc33e56c7a6a8bef7d95e1d36eb2f35748d475695 (diff)
downloadffmpeg-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.c6
-rw-r--r--libavfilter/dnn/dnn_backend_native_layer_mathunary.h1
-rw-r--r--tools/python/convert_from_tensorflow.py2
-rw-r--r--tools/python/convert_header.py2
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