dnn_backend_native_layer_mathunary: add abs support

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>

1 files changed, 2 insertions, 0 deletions

diff --git a/libavfilter/dnn/dnn_backend_native_layers.c b/libavfilter/dnn/dnn_backend_native_layers.c
index af18552eb4..70f9a5f958 100644
--- a/libavfilter/dnn/dnn_backend_native_layers.c
+++ b/libavfilter/dnn/dnn_backend_native_layers.c
@@ -25,6 +25,7 @@
 #include "dnn_backend_native_layer_depth2space.h"
 #include "dnn_backend_native_layer_maximum.h"
 #include "dnn_backend_native_layer_mathbinary.h"
+#include "dnn_backend_native_layer_mathunary.h"
 
 LayerFunc layer_funcs[DLT_COUNT] = {
     {NULL, NULL},
@@ -33,4 +34,5 @@ LayerFunc layer_funcs[DLT_COUNT] = {
     {dnn_execute_layer_pad,         dnn_load_layer_pad},
     {dnn_execute_layer_maximum,     dnn_load_layer_maximum},
     {dnn_execute_layer_math_binary, dnn_load_layer_math_binary},
+    {dnn_execute_layer_math_unary,  dnn_load_layer_math_unary},
 };