dnn_backend_native_layer_mathunary: add tan support

It can be tested with the model 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, 0.78)
x2 = tf.tan(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>

diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c
index fa8710a3ed3b7aa4e2457eccbf305d4d97efe060..e6e45a6b9f7e01938e8601f9791e1e0c7121fab9 100644 (file)
--- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c
+++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c
@@ -84,6 +84,10 @@ int dnn_execute_layer_math_unary(DnnOperand *operands, const int32_t *input_oper
         for (int i = 0; i < dims_count; ++i)
             dst[i] = cos(src[i]);
         return 0;
+    case DMUO_TAN:
+        for (int i = 0; i < dims_count; ++i)
+            dst[i] = tan(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 f70aea846bc75cb3da2c1a7e0916576c184f7e46..0467717a8bf0bbf240d55ac55a48f46faeac01e9 100644 (file)
--- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.h
+++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h
@@ -33,6 +33,7 @@ typedef enum {
     DMUO_ABS = 0,
     DMUO_SIN = 1,
     DMUO_COS = 2,
+    DMUO_TAN = 3,
     DMUO_COUNT
 } DNNMathUnaryOperation;
 

diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py
index 9e99fccdabe280b5fe9857c91602706cf732f0d3..9da6a43612d8542e70ffd683d75034edb987267f 100644 (file)
--- 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, 'Sin':1, 'Cos':2}
+        self.mathun2code  = {'Abs':0, 'Sin':1, 'Cos':2, 'Tan':3}
         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 ba6d18126e28f10e9b73ed5c5c52e0258891079c..b7fb0f797ae71a4a561a722581cb30475e5a2ea0 100644 (file)
--- 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 = 8
+minor = 9