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authorGuo, Yejun <yejun.guo@intel.com>2020-04-26 15:46:38 +0800
committerGuo, Yejun <yejun.guo@intel.com>2020-05-08 15:22:27 +0800
commit71e28c5422e321640b69ee512eef3e899c746e1e (patch)
tree8a2d673b6224e4492d5e045d42aecb18a93188f3
parent607b85f07e6596a4f1e56bbd5717522b41737547 (diff)
downloadffmpeg-71e28c5422e321640b69ee512eef3e899c746e1e.tar.gz
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 <yejun.guo@intel.com>
-rw-r--r--libavfilter/dnn/dnn_backend_native_layer_mathbinary.c13
-rw-r--r--libavfilter/dnn/dnn_backend_native_layer_mathbinary.h1
-rw-r--r--tools/python/convert_from_tensorflow.py11
-rw-r--r--tools/python/convert_header.py2
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