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author | Ting Fu <ting.fu@intel.com> | 2020-06-18 17:15:33 +0800 |
---|---|---|
committer | Guo, Yejun <yejun.guo@intel.com> | 2020-06-25 08:41:50 +0800 |
commit | 461485feac561c66a6e84bf6c7ff73e3eacd3f37 (patch) | |
tree | 2b9d2dfc610ddf15900fcfc5bdd8b77d938752f7 | |
parent | 057f6ee7f43c91033d37bb10548714ede01fcfc5 (diff) | |
download | ffmpeg-461485feac561c66a6e84bf6c7ff73e3eacd3f37.tar.gz |
dnn_backend_native_layer_mathunary: add acos support
It can be tested with the model generated with below python script:
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.acos(x)
x2 = tf.divide(x1, 3.1416/2) # pi/2
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 | 4 | ||||
-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, 7 insertions, 2 deletions
diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c index 3a147c2b3c..d130058546 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c @@ -96,6 +96,10 @@ int dnn_execute_layer_math_unary(DnnOperand *operands, const int32_t *input_oper for (int i = 0; i < dims_count; ++i) dst[i] = asin(src[i]); return 0; + case DMUO_ACOS: + for (int i = 0; i < dims_count; ++i) + dst[i] = acos(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 1c25db5a42..f146248567 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.h +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h @@ -35,6 +35,7 @@ typedef enum { DMUO_COS = 2, DMUO_TAN = 3, DMUO_ASIN = 4, + DMUO_ACOS = 5, DMUO_COUNT } DNNMathUnaryOperation; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index 5e526e31ce..78297e48a9 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, 'Sin':1, 'Cos':2, 'Tan':3, 'Asin':4} + self.mathun2code = {'Abs':0, 'Sin':1, 'Cos':2, 'Tan':3, 'Asin':4, 'Acos':5} 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 2b6afe8d13..4a8e44b4aa 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 = 10 +minor = 11 |