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yolov5
Commits
80473a65
Unverified
提交
80473a65
authored
1月 13, 2022
作者:
Glenn Jocher
提交者:
GitHub
1月 13, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Update `export.py` with Detect, Validate usages (#6280)
上级
f3085acc
隐藏空白字符变更
内嵌
并排
正在显示
1 个修改的文件
包含
30 行增加
和
23 行删除
+30
-23
export.py
export.py
+30
-23
没有找到文件。
export.py
浏览文件 @
80473a65
...
@@ -82,6 +82,7 @@ def export_torchscript(model, im, file, optimize, prefix=colorstr('TorchScript:'
...
@@ -82,6 +82,7 @@ def export_torchscript(model, im, file, optimize, prefix=colorstr('TorchScript:'
ts
.
save
(
str
(
f
),
_extra_files
=
extra_files
)
ts
.
save
(
str
(
f
),
_extra_files
=
extra_files
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'{prefix} export failure: {e}'
)
...
@@ -125,7 +126,7 @@ def export_onnx(model, im, file, opset, train, dynamic, simplify, prefix=colorst
...
@@ -125,7 +126,7 @@ def export_onnx(model, im, file, opset, train, dynamic, simplify, prefix=colorst
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'{prefix} simplifier failure: {e}'
)
LOGGER
.
info
(
f
'{prefix} simplifier failure: {e}'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
"{prefix} run --dynamic ONNX model inference with: 'python detect.py --weights {f}'"
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'{prefix} export failure: {e}'
)
...
@@ -143,13 +144,13 @@ def export_openvino(model, im, file, prefix=colorstr('OpenVINO:')):
...
@@ -143,13 +144,13 @@ def export_openvino(model, im, file, prefix=colorstr('OpenVINO:')):
subprocess
.
check_output
(
cmd
,
shell
=
True
)
subprocess
.
check_output
(
cmd
,
shell
=
True
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
def
export_coreml
(
model
,
im
,
file
,
prefix
=
colorstr
(
'CoreML:'
)):
def
export_coreml
(
model
,
im
,
file
,
prefix
=
colorstr
(
'CoreML:'
)):
# YOLOv5 CoreML export
# YOLOv5 CoreML export
ct_model
=
None
try
:
try
:
check_requirements
((
'coremltools'
,))
check_requirements
((
'coremltools'
,))
import
coremltools
as
ct
import
coremltools
as
ct
...
@@ -162,10 +163,10 @@ def export_coreml(model, im, file, prefix=colorstr('CoreML:')):
...
@@ -162,10 +163,10 @@ def export_coreml(model, im, file, prefix=colorstr('CoreML:')):
ct_model
.
save
(
f
)
ct_model
.
save
(
f
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
ct_model
,
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
return
None
,
None
return
ct_model
def
export_engine
(
model
,
im
,
file
,
train
,
half
,
simplify
,
workspace
=
4
,
verbose
=
False
,
prefix
=
colorstr
(
'TensorRT:'
)):
def
export_engine
(
model
,
im
,
file
,
train
,
half
,
simplify
,
workspace
=
4
,
verbose
=
False
,
prefix
=
colorstr
(
'TensorRT:'
)):
...
@@ -216,7 +217,7 @@ def export_engine(model, im, file, train, half, simplify, workspace=4, verbose=F
...
@@ -216,7 +217,7 @@ def export_engine(model, im, file, train, half, simplify, workspace=4, verbose=F
with
builder
.
build_engine
(
network
,
config
)
as
engine
,
open
(
f
,
'wb'
)
as
t
:
with
builder
.
build_engine
(
network
,
config
)
as
engine
,
open
(
f
,
'wb'
)
as
t
:
t
.
write
(
engine
.
serialize
())
t
.
write
(
engine
.
serialize
())
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
...
@@ -225,7 +226,6 @@ def export_saved_model(model, im, file, dynamic,
...
@@ -225,7 +226,6 @@ def export_saved_model(model, im, file, dynamic,
tf_nms
=
False
,
agnostic_nms
=
False
,
topk_per_class
=
100
,
topk_all
=
100
,
iou_thres
=
0.45
,
tf_nms
=
False
,
agnostic_nms
=
False
,
topk_per_class
=
100
,
topk_all
=
100
,
iou_thres
=
0.45
,
conf_thres
=
0.25
,
prefix
=
colorstr
(
'TensorFlow SavedModel:'
)):
conf_thres
=
0.25
,
prefix
=
colorstr
(
'TensorFlow SavedModel:'
)):
# YOLOv5 TensorFlow SavedModel export
# YOLOv5 TensorFlow SavedModel export
keras_model
=
None
try
:
try
:
import
tensorflow
as
tf
import
tensorflow
as
tf
from
tensorflow
import
keras
from
tensorflow
import
keras
...
@@ -247,10 +247,10 @@ def export_saved_model(model, im, file, dynamic,
...
@@ -247,10 +247,10 @@ def export_saved_model(model, im, file, dynamic,
keras_model
.
save
(
f
,
save_format
=
'tf'
)
keras_model
.
save
(
f
,
save_format
=
'tf'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
keras_model
,
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
return
None
,
None
return
keras_model
def
export_pb
(
keras_model
,
im
,
file
,
prefix
=
colorstr
(
'TensorFlow GraphDef:'
)):
def
export_pb
(
keras_model
,
im
,
file
,
prefix
=
colorstr
(
'TensorFlow GraphDef:'
)):
...
@@ -269,6 +269,7 @@ def export_pb(keras_model, im, file, prefix=colorstr('TensorFlow GraphDef:')):
...
@@ -269,6 +269,7 @@ def export_pb(keras_model, im, file, prefix=colorstr('TensorFlow GraphDef:')):
tf
.
io
.
write_graph
(
graph_or_graph_def
=
frozen_func
.
graph
,
logdir
=
str
(
f
.
parent
),
name
=
f
.
name
,
as_text
=
False
)
tf
.
io
.
write_graph
(
graph_or_graph_def
=
frozen_func
.
graph
,
logdir
=
str
(
f
.
parent
),
name
=
f
.
name
,
as_text
=
False
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
...
@@ -300,7 +301,7 @@ def export_tflite(keras_model, im, file, int8, data, ncalib, prefix=colorstr('Te
...
@@ -300,7 +301,7 @@ def export_tflite(keras_model, im, file, int8, data, ncalib, prefix=colorstr('Te
tflite_model
=
converter
.
convert
()
tflite_model
=
converter
.
convert
()
open
(
f
,
"wb"
)
.
write
(
tflite_model
)
open
(
f
,
"wb"
)
.
write
(
tflite_model
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
...
@@ -328,6 +329,7 @@ def export_edgetpu(keras_model, im, file, prefix=colorstr('Edge TPU:')):
...
@@ -328,6 +329,7 @@ def export_edgetpu(keras_model, im, file, prefix=colorstr('Edge TPU:')):
subprocess
.
run
(
cmd
,
shell
=
True
,
check
=
True
)
subprocess
.
run
(
cmd
,
shell
=
True
,
check
=
True
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
...
@@ -364,6 +366,7 @@ def export_tfjs(keras_model, im, file, prefix=colorstr('TensorFlow.js:')):
...
@@ -364,6 +366,7 @@ def export_tfjs(keras_model, im, file, prefix=colorstr('TensorFlow.js:')):
j
.
write
(
subst
)
j
.
write
(
subst
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
LOGGER
.
info
(
f
'{prefix} export success, saved as {f} ({file_size(f):.1f} MB)'
)
return
f
except
Exception
as
e
:
except
Exception
as
e
:
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
LOGGER
.
info
(
f
'
\n
{prefix} export failure: {e}'
)
...
@@ -431,15 +434,15 @@ def run(data=ROOT / 'data/coco128.yaml', # 'dataset.yaml path'
...
@@ -431,15 +434,15 @@ def run(data=ROOT / 'data/coco128.yaml', # 'dataset.yaml path'
# Exports
# Exports
if
'torchscript'
in
include
:
if
'torchscript'
in
include
:
export_torchscript
(
model
,
im
,
file
,
optimize
)
f
=
export_torchscript
(
model
,
im
,
file
,
optimize
)
if
'engine'
in
include
:
# TensorRT required before ONNX
if
'engine'
in
include
:
# TensorRT required before ONNX
export_engine
(
model
,
im
,
file
,
train
,
half
,
simplify
,
workspace
,
verbose
)
f
=
export_engine
(
model
,
im
,
file
,
train
,
half
,
simplify
,
workspace
,
verbose
)
if
(
'onnx'
in
include
)
or
(
'openvino'
in
include
):
# OpenVINO requires ONNX
if
(
'onnx'
in
include
)
or
(
'openvino'
in
include
):
# OpenVINO requires ONNX
export_onnx
(
model
,
im
,
file
,
opset
,
train
,
dynamic
,
simplify
)
f
=
export_onnx
(
model
,
im
,
file
,
opset
,
train
,
dynamic
,
simplify
)
if
'openvino'
in
include
:
if
'openvino'
in
include
:
export_openvino
(
model
,
im
,
file
)
f
=
export_openvino
(
model
,
im
,
file
)
if
'coreml'
in
include
:
if
'coreml'
in
include
:
export_coreml
(
model
,
im
,
file
)
_
,
f
=
export_coreml
(
model
,
im
,
file
)
# TensorFlow Exports
# TensorFlow Exports
if
any
(
tf_exports
):
if
any
(
tf_exports
):
...
@@ -447,22 +450,26 @@ def run(data=ROOT / 'data/coco128.yaml', # 'dataset.yaml path'
...
@@ -447,22 +450,26 @@ def run(data=ROOT / 'data/coco128.yaml', # 'dataset.yaml path'
if
int8
or
edgetpu
:
# TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
if
int8
or
edgetpu
:
# TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
check_requirements
((
'flatbuffers==1.12'
,))
# required before `import tensorflow`
check_requirements
((
'flatbuffers==1.12'
,))
# required before `import tensorflow`
assert
not
(
tflite
and
tfjs
),
'TFLite and TF.js models must be exported separately, please pass only one type.'
assert
not
(
tflite
and
tfjs
),
'TFLite and TF.js models must be exported separately, please pass only one type.'
model
=
export_saved_model
(
model
,
im
,
file
,
dynamic
,
tf_nms
=
nms
or
agnostic_nms
or
tfjs
,
model
,
f
=
export_saved_model
(
model
,
im
,
file
,
dynamic
,
tf_nms
=
nms
or
agnostic_nms
or
tfjs
,
agnostic_nms
=
agnostic_nms
or
tfjs
,
topk_per_class
=
topk_per_class
,
topk_all
=
topk_all
,
agnostic_nms
=
agnostic_nms
or
tfjs
,
topk_per_class
=
topk_per_class
,
conf_thres
=
conf_thres
,
iou_thres
=
iou_thres
)
# keras model
topk_all
=
topk_all
,
conf_thres
=
conf_thres
,
iou_thres
=
iou_thres
)
# keras model
if
pb
or
tfjs
:
# pb prerequisite to tfjs
if
pb
or
tfjs
:
# pb prerequisite to tfjs
export_pb
(
model
,
im
,
file
)
f
=
export_pb
(
model
,
im
,
file
)
if
tflite
or
edgetpu
:
if
tflite
or
edgetpu
:
export_tflite
(
model
,
im
,
file
,
int8
=
int8
or
edgetpu
,
data
=
data
,
ncalib
=
100
)
f
=
export_tflite
(
model
,
im
,
file
,
int8
=
int8
or
edgetpu
,
data
=
data
,
ncalib
=
100
)
if
edgetpu
:
if
edgetpu
:
export_edgetpu
(
model
,
im
,
file
)
f
=
export_edgetpu
(
model
,
im
,
file
)
if
tfjs
:
if
tfjs
:
export_tfjs
(
model
,
im
,
file
)
f
=
export_tfjs
(
model
,
im
,
file
)
# Finish
# Finish
LOGGER
.
info
(
f
'
\n
Export complete ({time.time() - t:.2f}s)'
LOGGER
.
info
(
f
'
\n
Export complete ({time.time() - t:.2f}s)'
f
"
\n
Results saved to {colorstr('bold', file.parent.resolve())}"
f
"
\n
Results saved to {colorstr('bold', file.parent.resolve())}"
f
'
\n
Visualize with https://netron.app'
)
f
"
\n
Visualize with https://netron.app"
f
"
\n
Detect with `python detect.py --weights {f}`"
f
" or `model = torch.hub.load('ultralytics/yolov5', 'custom', '{f}')"
f
"
\n
Validate with `python val.py --weights {f}`"
)
def
parse_opt
():
def
parse_opt
():
...
@@ -490,7 +497,7 @@ def parse_opt():
...
@@ -490,7 +497,7 @@ def parse_opt():
parser
.
add_argument
(
'--conf-thres'
,
type
=
float
,
default
=
0.25
,
help
=
'TF.js NMS: confidence threshold'
)
parser
.
add_argument
(
'--conf-thres'
,
type
=
float
,
default
=
0.25
,
help
=
'TF.js NMS: confidence threshold'
)
parser
.
add_argument
(
'--include'
,
nargs
=
'+'
,
parser
.
add_argument
(
'--include'
,
nargs
=
'+'
,
default
=
[
'torchscript'
,
'onnx'
],
default
=
[
'torchscript'
,
'onnx'
],
help
=
'
available formats are (torchscript, onnx, engine, coreml, saved_model, pb, tflite, tfjs)
'
)
help
=
'
torchscript, onnx, openvino, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs
'
)
opt
=
parser
.
parse_args
()
opt
=
parser
.
parse_args
()
print_args
(
FILE
.
stem
,
opt
)
print_args
(
FILE
.
stem
,
opt
)
return
opt
return
opt
...
...
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