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体验新版 GitCode,发现更多精彩内容 >>
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268ed03b
编写于
5月 11, 2020
作者:
L
LDOUBLEV
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差异文件
update detection doc and infer code
上级
af399022
变更
8
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Showing
8 changed file
with
76 addition
and
39 deletion
+76
-39
doc/detection.md
doc/detection.md
+13
-3
ppocr/data/det/db_process.py
ppocr/data/det/db_process.py
+0
-3
ppocr/data/reader_main.py
ppocr/data/reader_main.py
+0
-6
tools/eval_utils/eval_det_iou.py
tools/eval_utils/eval_det_iou.py
+4
-0
tools/eval_utils/eval_det_utils.py
tools/eval_utils/eval_det_utils.py
+8
-0
tools/infer/utility.py
tools/infer/utility.py
+0
-8
tools/infer_det.py
tools/infer_det.py
+51
-3
tools/program.py
tools/program.py
+0
-16
未找到文件。
doc/detection.md
浏览文件 @
268ed03b
...
@@ -32,8 +32,8 @@ json.dumps编码前的图像标注信息是包含多个字典的list,字典中
...
@@ -32,8 +32,8 @@ json.dumps编码前的图像标注信息是包含多个字典的list,字典中
## 3.2 快速启动训练
## 3.2 快速启动训练
首先下载pretrain model,
目前支持两种backbone,分别是MobileNetV3、ResNet50,您可以根据需求使用PaddleClas中的模型更换
首先下载pretrain model,
PaddleOCR的检测模型目前支持两种backbone,分别是MobileNetV3、ResNet50_vd,
backbone。
您可以根据需求使用
[
PaddleClas
](
https://github.com/PaddlePaddle/PaddleClas/tree/master/ppcls/modeling/architectures
)
中的模型更换
backbone。
```
```
# 下载MobileNetV3的预训练模型
# 下载MobileNetV3的预训练模型
wget -P /PaddleOCR/pretrained_model/ 模型链接
wget -P /PaddleOCR/pretrained_model/ 模型链接
...
@@ -63,7 +63,17 @@ PaddleOCR计算三个OCR检测相关的指标,分别是:Precision、Recall
...
@@ -63,7 +63,17 @@ PaddleOCR计算三个OCR检测相关的指标,分别是:Precision、Recall
运行如下代码,根据配置文件det_db_mv3.yml中save_res_path指定的测试集检测结果文件,计算评估指标。
运行如下代码,根据配置文件det_db_mv3.yml中save_res_path指定的测试集检测结果文件,计算评估指标。
```
```
python3 tools/eval.py -c configs/det/det_db_mv3.yml -o checkpoints
./output/best_accuracy
python3 tools/eval.py -c configs/det/det_db_mv3.yml -o checkpoints
="./output/best_accuracy"
```
```
## 3.4 测试检测效果
## 3.4 测试检测效果
测试单张图像的检测效果
```
python3 tools/infer_det.py -c config/det/det_db_mv3.yml -o TestReader.single_img_path="./demo.jpg"
```
测试文件夹下所有图像的检测效果
```
python3 tools/infer_det.py -c config/det/det_db_mv3.yml -o TestReader.single_img_path="./demo_img/"
```
ppocr/data/det/db_process.py
浏览文件 @
268ed03b
...
@@ -124,9 +124,6 @@ class DBProcessTest(object):
...
@@ -124,9 +124,6 @@ class DBProcessTest(object):
def
resize_image_type0
(
self
,
im
):
def
resize_image_type0
(
self
,
im
):
"""
"""
resize image to a size multiple of 32 which is required by the network
resize image to a size multiple of 32 which is required by the network
:param im: the resized image
:param max_side_len: limit of max image size to avoid out of memory in gpu
:return: the resized image and the resize ratio
"""
"""
max_side_len
=
self
.
max_side_len
max_side_len
=
self
.
max_side_len
h
,
w
,
_
=
im
.
shape
h
,
w
,
_
=
im
.
shape
...
...
ppocr/data/reader_main.py
浏览文件 @
268ed03b
...
@@ -73,9 +73,3 @@ def reader_main(config=None, mode=None):
...
@@ -73,9 +73,3 @@ def reader_main(config=None, mode=None):
return
paddle
.
reader
.
multiprocess_reader
(
readers
,
False
)
return
paddle
.
reader
.
multiprocess_reader
(
readers
,
False
)
else
:
else
:
return
function
(
mode
)
return
function
(
mode
)
def
test_reader
(
image_shape
,
img_path
):
img
=
cv2
.
imread
(
img_path
)
norm_img
=
process_image
(
img
,
image_shape
)
return
norm_img
tools/eval_utils/eval_det_iou.py
浏览文件 @
268ed03b
...
@@ -3,6 +3,10 @@
...
@@ -3,6 +3,10 @@
from
collections
import
namedtuple
from
collections
import
namedtuple
import
numpy
as
np
import
numpy
as
np
from
shapely.geometry
import
Polygon
from
shapely.geometry
import
Polygon
"""
reference from :
https://github.com/MhLiao/DB/blob/3c32b808d4412680310d3d28eeb6a2d5bf1566c5/concern/icdar2015_eval/detection/iou.py#L8
"""
class
DetectionIoUEvaluator
(
object
):
class
DetectionIoUEvaluator
(
object
):
...
...
tools/eval_utils/eval_det_utils.py
浏览文件 @
268ed03b
...
@@ -98,6 +98,14 @@ def load_label_infor(label_file_path, do_ignore=False):
...
@@ -98,6 +98,14 @@ def load_label_infor(label_file_path, do_ignore=False):
def
cal_det_metrics
(
gt_label_path
,
save_res_path
):
def
cal_det_metrics
(
gt_label_path
,
save_res_path
):
"""
calculate the detection metrics
Args:
gt_label_path(string): The groundtruth detection label file path
save_res_path(string): The saved predicted detection label path
return:
claculated metrics including Hmean、precision and recall
"""
evaluator
=
DetectionIoUEvaluator
()
evaluator
=
DetectionIoUEvaluator
()
gt_label_infor
=
load_label_infor
(
gt_label_path
,
do_ignore
=
True
)
gt_label_infor
=
load_label_infor
(
gt_label_path
,
do_ignore
=
True
)
dt_label_infor
=
load_label_infor
(
save_res_path
)
dt_label_infor
=
load_label_infor
(
save_res_path
)
...
...
tools/infer/utility.py
浏览文件 @
268ed03b
...
@@ -99,15 +99,7 @@ def create_predictor(args, mode):
...
@@ -99,15 +99,7 @@ def create_predictor(args, mode):
config
.
disable_gpu
()
config
.
disable_gpu
()
config
.
disable_glog_info
()
config
.
disable_glog_info
()
# config.switch_ir_optim(args.ir_optim)
# if args.use_tensorrt:
# config.enable_tensorrt_engine(
# precision_mode=AnalysisConfig.Precision.Half
# if args.use_fp16 else AnalysisConfig.Precision.Float32,
# max_batch_size=args.batch_size)
# config.enable_memory_optim()
# use zero copy
# use zero copy
config
.
switch_use_feed_fetch_ops
(
False
)
config
.
switch_use_feed_fetch_ops
(
False
)
predictor
=
create_paddle_predictor
(
config
)
predictor
=
create_paddle_predictor
(
config
)
...
...
tools/infer_det.py
浏览文件 @
268ed03b
...
@@ -44,6 +44,7 @@ from ppocr.utils.utility import create_module
...
@@ -44,6 +44,7 @@ from ppocr.utils.utility import create_module
import
program
import
program
from
ppocr.utils.save_load
import
init_model
from
ppocr.utils.save_load
import
init_model
from
ppocr.data.reader_main
import
reader_main
from
ppocr.data.reader_main
import
reader_main
import
cv2
from
ppocr.utils.utility
import
initial_logger
from
ppocr.utils.utility
import
initial_logger
logger
=
initial_logger
()
logger
=
initial_logger
()
...
@@ -67,6 +68,50 @@ def draw_det_res(dt_boxes, config, img_name, ino):
...
@@ -67,6 +68,50 @@ def draw_det_res(dt_boxes, config, img_name, ino):
logger
.
info
(
"The detected Image saved in {}"
.
format
(
save_path
))
logger
.
info
(
"The detected Image saved in {}"
.
format
(
save_path
))
def
simple_reader
(
img_file
,
config
):
imgs_lists
=
[]
if
img_file
is
None
or
not
os
.
path
.
exists
(
img_file
):
raise
Exception
(
"not found any img file in {}"
.
format
(
img_file
))
img_end
=
[
'jpg'
,
'png'
,
'jpeg'
,
'JPEG'
,
'JPG'
,
'bmp'
]
if
os
.
path
.
isfile
(
img_file
)
and
img_file
.
split
(
'.'
)[
-
1
]
in
img_end
:
imgs_lists
.
append
(
img_file
)
elif
os
.
path
.
isdir
(
img_file
):
for
single_file
in
os
.
listdir
(
img_file
):
if
single_file
.
split
(
'.'
)[
-
1
]
in
img_end
:
imgs_lists
.
append
(
os
.
path
.
join
(
img_file
,
single_file
))
if
len
(
imgs_lists
)
==
0
:
raise
Exception
(
"not found any img file in {}"
.
format
(
img_file
))
batch_size
=
config
[
'Global'
][
'test_batch_size_per_card'
]
global_params
=
config
[
'Global'
]
params
=
deepcopy
(
config
[
'TestReader'
])
params
.
update
(
global_params
)
reader_function
=
params
[
'process_function'
]
process_function
=
create_module
(
reader_function
)(
params
)
def
batch_iter_reader
():
batch_outs
=
[]
for
img_path
in
imgs_lists
:
img
=
cv2
.
imread
(
img_path
)
if
img
.
shape
[
-
1
]
==
1
or
len
(
list
(
img
.
shape
))
==
2
:
img
=
cv2
.
cvtColor
(
img
,
cv2
.
COLOR_GRAY2BGR
)
if
img
is
None
:
logger
.
info
(
"load image error:"
+
img_path
)
continue
outs
=
process_function
(
img
)
outs
.
append
(
os
.
path
.
basename
(
img_path
))
print
(
outs
[
0
].
shape
,
outs
[
2
])
batch_outs
.
append
(
outs
)
if
len
(
batch_outs
)
==
batch_size
:
yield
batch_outs
batch_outs
=
[]
if
len
(
batch_outs
)
!=
0
:
yield
batch_outs
return
batch_iter_reader
def
main
():
def
main
():
config
=
program
.
load_config
(
FLAGS
.
config
)
config
=
program
.
load_config
(
FLAGS
.
config
)
program
.
merge_config
(
FLAGS
.
opt
)
program
.
merge_config
(
FLAGS
.
opt
)
...
@@ -103,7 +148,9 @@ def main():
...
@@ -103,7 +148,9 @@ def main():
save_res_path
=
config
[
'Global'
][
'save_res_path'
]
save_res_path
=
config
[
'Global'
][
'save_res_path'
]
with
open
(
save_res_path
,
"wb"
)
as
fout
:
with
open
(
save_res_path
,
"wb"
)
as
fout
:
test_reader
=
reader_main
(
config
=
config
,
mode
=
'test'
)
# test_reader = reader_main(config=config, mode='test')
single_img_path
=
config
[
'TestReader'
][
'single_img_path'
]
test_reader
=
simple_reader
(
img_file
=
single_img_path
,
config
=
config
)
tackling_num
=
0
tackling_num
=
0
for
data
in
test_reader
():
for
data
in
test_reader
():
img_num
=
len
(
data
)
img_num
=
len
(
data
)
...
@@ -116,6 +163,7 @@ def main():
...
@@ -116,6 +163,7 @@ def main():
img_list
.
append
(
data
[
ino
][
0
])
img_list
.
append
(
data
[
ino
][
0
])
ratio_list
.
append
(
data
[
ino
][
1
])
ratio_list
.
append
(
data
[
ino
][
1
])
img_name_list
.
append
(
data
[
ino
][
2
])
img_name_list
.
append
(
data
[
ino
][
2
])
img_list
=
np
.
concatenate
(
img_list
,
axis
=
0
)
img_list
=
np
.
concatenate
(
img_list
,
axis
=
0
)
outs
=
exe
.
run
(
eval_prog
,
\
outs
=
exe
.
run
(
eval_prog
,
\
feed
=
{
'image'
:
img_list
},
\
feed
=
{
'image'
:
img_list
},
\
...
@@ -126,7 +174,7 @@ def main():
...
@@ -126,7 +174,7 @@ def main():
postprocess_params
.
update
(
global_params
)
postprocess_params
.
update
(
global_params
)
postprocess
=
create_module
(
postprocess_params
[
'function'
])
\
postprocess
=
create_module
(
postprocess_params
[
'function'
])
\
(
params
=
postprocess_params
)
(
params
=
postprocess_params
)
dt_boxes_list
=
postprocess
(
outs
,
ratio_list
)
dt_boxes_list
=
postprocess
(
{
"maps"
:
outs
[
0
]}
,
ratio_list
)
for
ino
in
range
(
img_num
):
for
ino
in
range
(
img_num
):
dt_boxes
=
dt_boxes_list
[
ino
]
dt_boxes
=
dt_boxes_list
[
ino
]
img_name
=
img_name_list
[
ino
]
img_name
=
img_name_list
[
ino
]
...
...
tools/program.py
浏览文件 @
268ed03b
...
@@ -185,22 +185,6 @@ def build(config, main_prog, startup_prog, mode):
...
@@ -185,22 +185,6 @@ def build(config, main_prog, startup_prog, mode):
def
build_export
(
config
,
main_prog
,
startup_prog
):
def
build_export
(
config
,
main_prog
,
startup_prog
):
"""
"""
Build a program using a model and an optimizer
1. create feeds
2. create a dataloader
3. create a model
4. create fetchs
5. create an optimizer
Args:
config(dict): config
main_prog(): main program
startup_prog(): startup program
is_train(bool): train or valid
Returns:
dataloader(): a bridge between the model and the data
fetchs(dict): dict of model outputs(included loss and measures)
"""
"""
with
fluid
.
program_guard
(
main_prog
,
startup_prog
):
with
fluid
.
program_guard
(
main_prog
,
startup_prog
):
with
fluid
.
unique_name
.
guard
():
with
fluid
.
unique_name
.
guard
():
...
...
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