From 71e28c5422e321640b69ee512eef3e899c746e1e Mon Sep 17 00:00:00 2001 From: "Guo, Yejun" Date: Sun, 26 Apr 2020 15:46:38 +0800 Subject: [PATCH] dnn/native: add native support for minimum it can be tested with model file generated with below python script: import tensorflow as tf import numpy as np import imageio in_img = imageio.imread('input.jpg') 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.minimum(0.7, x) x2 = tf.maximum(x1, 0.4) 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: Guo, Yejun --- .../dnn/dnn_backend_native_layer_mathbinary.c | 13 +++++++++++++ .../dnn/dnn_backend_native_layer_mathbinary.h | 1 + tools/python/convert_from_tensorflow.py | 11 +++-------- tools/python/convert_header.py | 2 +- 4 files changed, 18 insertions(+), 9 deletions(-) diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c index c32a042788..edc389d3ba 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c +++ b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c @@ -150,6 +150,19 @@ int dnn_execute_layer_math_binary(DnnOperand *operands, const int32_t *input_ope } } return 0; + case DMBO_MINIMUM: + if (params->input0_broadcast || params->input1_broadcast) { + for (int i = 0; i < dims_count; ++i) { + dst[i] = FFMIN(params->v, src[i]); + } + } else { + const DnnOperand *input1 = &operands[input_operand_indexes[1]]; + const float *src1 = input1->data; + for (int i = 0; i < dims_count; ++i) { + dst[i] = FFMIN(src[i], src1[i]); + } + } + return 0; default: return -1; } diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h index 2ffbb66eeb..f3dbbeb8c3 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h +++ b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h @@ -35,6 +35,7 @@ typedef enum { DMBO_ADD = 1, DMBO_MUL = 2, DMBO_REALDIV = 3, + DMBO_MINIMUM = 4, DMBO_COUNT } DNNMathBinaryOperation; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index a0fdad25b7..1c20891fcc 100644 --- a/tools/python/convert_from_tensorflow.py +++ b/tools/python/convert_from_tensorflow.py @@ -71,7 +71,7 @@ class TFConverter: self.conv2d_scope_names = set() self.conv2d_scopename_inputname_dict = {} self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4, 'MathBinary':5} - self.mathbin2code = {'Sub':0, 'Add':1, 'Mul':2, 'RealDiv':3} + self.mathbin2code = {'Sub':0, 'Add':1, 'Mul':2, 'RealDiv':3, 'Minimum':4} self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2} self.name_operand_dict = {} @@ -305,15 +305,10 @@ class TFConverter: self.dump_mirrorpad_to_file(node, f) elif node.op == 'Maximum': self.dump_maximum_to_file(node, f) - elif node.op == 'Sub': - self.dump_mathbinary_to_file(node, f) - elif node.op == 'Add': - self.dump_mathbinary_to_file(node, f) - elif node.op == 'Mul': - self.dump_mathbinary_to_file(node, f) - elif node.op == 'RealDiv': + elif node.op in self.mathbin2code: self.dump_mathbinary_to_file(node, f) + def dump_operands_to_file(self, f): operands = sorted(self.name_operand_dict.values()) for operand in operands: diff --git a/tools/python/convert_header.py b/tools/python/convert_header.py index 75d1ce803c..e692a5e217 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 = 4 +minor = 5