virtualenv/FFmpeg
1
0
Fork 0
mirror of https://github.com/FFmpeg/FFmpeg.git synced 2025-06-14 22:15:12 +02:00
Code Issues Releases Activity

libavfilter/dnn: add layer maximum for native mode.

Browse Source 
The reason to add this layer is that it is used by srcnn in vf_sr.
This layer is currently ignored in native mode. After this patch,
we can add multiple outputs support for native mode.

Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
This commit is contained in:
Guo, Yejun
2019-09-20 11:55:48 +08:00
committed by Pedro Arthur
parent ea673a0edb
commit b2683c66b2
8 changed files with 198 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
tools/python/convert_from_tensorflow.py
View File

@ -70,7 +70,7 @@ class TFConverter:
self.converted_nodes = set()
self.conv2d_scope_names = set()
self.conv2d_scopename_inputname_dict = {}
self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3}
self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4}
self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2}
self.name_operand_dict = {}
@ -200,6 +200,19 @@ class TFConverter:
np.array([input_operand_index, output_operand_index], dtype=np.uint32).tofile(f)
def dump_maximum_to_file(self, node, f):
assert(node.op == 'Maximum')
self.layer_number = self.layer_number + 1
ynode = self.name_node_dict[node.input[1]]
y = ynode.attr['value'].tensor.float_val[0]
np.array([self.op2code[node.op]], dtype=np.uint32).tofile(f)
np.array([y], dtype=np.float32).tofile(f)
self.converted_nodes.add(node.name)
input_operand_index = self.add_operand(node.input[0], Operand.IOTYPE_INPUT)
output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
np.array([input_operand_index, output_operand_index], dtype=np.uint32).tofile(f)
def dump_layers_to_file(self, f):
for node in self.nodes:
if node.name in self.converted_nodes:
@ -216,6 +229,8 @@ class TFConverter:
self.dump_depth2space_to_file(node, f)
elif node.op == 'MirrorPad':
self.dump_mirrorpad_to_file(node, f)
elif node.op == 'Maximum':
self.dump_maximum_to_file(node, f)
def dump_operands_to_file(self, f):