From f73cc61bf5aa383048979f4de2023877c522f6be Mon Sep 17 00:00:00 2001 From: Ting Fu Date: Mon, 25 May 2020 22:46:26 +0800 Subject: 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 Signed-off-by: Guo, Yejun --- libavfilter/dnn/dnn_backend_native_layers.c | 2 ++ 1 file changed, 2 insertions(+) (limited to 'libavfilter/dnn/dnn_backend_native_layers.c') 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}, }; -- cgit v1.2.3