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.asin(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...@intel.com> --- libavfilter/dnn/dnn_backend_native_layer_mathunary.c | 4 ++++ libavfilter/dnn/dnn_backend_native_layer_mathunary.h | 1 + tools/python/convert_from_tensorflow.py | 2 +- 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 90fac6aa67..3a147c2b3c 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c @@ -92,6 +92,10 @@ int dnn_execute_layer_math_unary(DnnOperand *operands, const int32_t *input_oper for (int i = 0; i < dims_count; ++i) dst[i] = tan(src[i]); return 0; + case DMUO_ASIN: + for (int i = 0; i < dims_count; ++i) + dst[i] = asin(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 40a9bb5fb8..1c25db5a42 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.h +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h @@ -34,6 +34,7 @@ typedef enum { DMUO_SIN = 1, DMUO_COS = 2, DMUO_TAN = 3, + DMUO_ASIN = 4, DMUO_COUNT } DNNMathUnaryOperation; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index 9da6a43612..5e526e31ce 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} + self.mathun2code = {'Abs':0, 'Sin':1, 'Cos':2, 'Tan':3, 'Asin':4} 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 b7fb0f797a..2b6afe8d13 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 = 9 +minor = 10 -- 2.17.1 _______________________________________________ ffmpeg-devel mailing list ffmpeg-devel@ffmpeg.org https://ffmpeg.org/mailman/listinfo/ffmpeg-devel To unsubscribe, visit link above, or email ffmpeg-devel-requ...@ffmpeg.org with subject "unsubscribe".