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体验新版 GitCode,发现更多精彩内容 >>
提交
a5694968
编写于
8月 03, 2021
作者:
W
WenmuZhou
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix bug when inference with network img
上级
b2debedb
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
84 addition
and
20 deletion
+84
-20
__init__.py
__init__.py
+1
-1
doc/doc_ch/whl.md
doc/doc_ch/whl.md
+78
-16
doc/doc_en/whl_en.md
doc/doc_en/whl_en.md
+4
-2
paddleocr.py
paddleocr.py
+1
-1
未找到文件。
__init__.py
浏览文件 @
a5694968
...
...
@@ -15,4 +15,4 @@ import paddleocr
from
.paddleocr
import
*
__version__
=
paddleocr
.
VERSION
__all__
=
[
'PaddleOCR'
,
'PPStructure'
,
'draw_ocr'
,
'draw_structure_result'
,
'save_structure_res'
]
__all__
=
[
'PaddleOCR'
,
'PPStructure'
,
'draw_ocr'
,
'draw_structure_result'
,
'save_structure_res'
,
'download_with_progressbar'
]
doc/doc_ch/whl.md
浏览文件 @
a5694968
...
...
@@ -5,26 +5,32 @@
### 1.1 安装whl包
pip安装
```
bash
pip
install
"paddleocr>=2.0.1"
# 推荐使用2.0.1+版本
```
本地构建并安装
```
bash
python3 setup.py bdist_wheel
pip3
install
dist/paddleocr-x.x.x-py3-none-any.whl
# x.x.x是paddleocr的版本号
```
## 2 使用
### 2.1 代码使用
paddleocr whl包会自动下载ppocr轻量级模型作为默认模型,可以根据第3节
**自定义模型**
进行自定义更换。
*
检测+方向分类器+识别全流程
```
python
from
paddleocr
import
PaddleOCR
,
draw_ocr
# Paddleocr目前支持中英文、英文、法语、德语、韩语、日语,可以通过修改lang参数进行切换
# 参数依次为`ch`, `en`, `french`, `german`, `korean`, `japan`。
ocr
=
PaddleOCR
(
use_angle_cls
=
True
,
lang
=
"ch"
)
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
(
use_angle_cls
=
True
,
lang
=
"ch"
)
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs/11.jpg'
result
=
ocr
.
ocr
(
img_path
,
cls
=
True
)
for
line
in
result
:
...
...
@@ -32,6 +38,7 @@ for line in result:
# 显示结果
from
PIL
import
Image
image
=
Image
.
open
(
img_path
).
convert
(
'RGB'
)
boxes
=
[
line
[
0
]
for
line
in
result
]
txts
=
[
line
[
1
][
0
]
for
line
in
result
]
...
...
@@ -40,31 +47,36 @@ im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc
im_show
=
Image
.
fromarray
(
im_show
)
im_show
.
save
(
'result.jpg'
)
```
结果是一个list,每个item包含了文本框,文字和识别置信度
```
bash
[[[
24.0, 36.0],
[
304.0, 34.0],
[
304.0, 72.0],
[
24.0, 74.0]],
[
'纯臻营养护发素'
, 0.964739]]
[[[
24.0, 80.0],
[
172.0, 80.0],
[
172.0, 104.0],
[
24.0, 104.0]],
[
'产品信息/参数'
, 0.98069626]]
[[[
24.0, 109.0],
[
333.0, 109.0],
[
333.0, 136.0],
[
24.0, 136.0]],
[
'(45元/每公斤,100公斤起订)'
, 0.9676722]]
......
```
结果可视化
<div
align=
"center"
>
<img
src=
"../imgs_results/whl/11_det_rec.jpg"
width=
"800"
>
</div>
*
检测+识别
```
python
from
paddleocr
import
PaddleOCR
,
draw_ocr
ocr
=
PaddleOCR
()
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
()
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs/11.jpg'
result
=
ocr
.
ocr
(
img_path
,
cls
=
False
)
result
=
ocr
.
ocr
(
img_path
,
cls
=
False
)
for
line
in
result
:
print
(
line
)
# 显示结果
from
PIL
import
Image
image
=
Image
.
open
(
img_path
).
convert
(
'RGB'
)
boxes
=
[
line
[
0
]
for
line
in
result
]
txts
=
[
line
[
1
][
0
]
for
line
in
result
]
...
...
@@ -73,38 +85,46 @@ im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc
im_show
=
Image
.
fromarray
(
im_show
)
im_show
.
save
(
'result.jpg'
)
```
结果是一个list,每个item包含了文本框,文字和识别置信度
```
bash
[[[
24.0, 36.0],
[
304.0, 34.0],
[
304.0, 72.0],
[
24.0, 74.0]],
[
'纯臻营养护发素'
, 0.964739]]
[[[
24.0, 80.0],
[
172.0, 80.0],
[
172.0, 104.0],
[
24.0, 104.0]],
[
'产品信息/参数'
, 0.98069626]]
[[[
24.0, 109.0],
[
333.0, 109.0],
[
333.0, 136.0],
[
24.0, 136.0]],
[
'(45元/每公斤,100公斤起订)'
, 0.9676722]]
......
```
结果可视化
<div
align=
"center"
>
<img
src=
"../imgs_results/whl/11_det_rec.jpg"
width=
"800"
>
</div>
*
方向分类器+识别
```
python
from
paddleocr
import
PaddleOCR
ocr
=
PaddleOCR
(
use_angle_cls
=
True
)
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
(
use_angle_cls
=
True
)
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs_words/ch/word_1.jpg'
result
=
ocr
.
ocr
(
img_path
,
det
=
False
,
cls
=
True
)
for
line
in
result
:
print
(
line
)
```
结果是一个list,每个item只包含识别结果和识别置信度
```
bash
[
'韩国小馆'
, 0.9907421]
```
*
单独执行检测
```
python
from
paddleocr
import
PaddleOCR
,
draw_ocr
ocr
=
PaddleOCR
()
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
()
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs/11.jpg'
result
=
ocr
.
ocr
(
img_path
,
rec
=
False
)
for
line
in
result
:
...
...
@@ -118,13 +138,16 @@ im_show = draw_ocr(image, result, txts=None, scores=None, font_path='/path/to/Pa
im_show
=
Image
.
fromarray
(
im_show
)
im_show
.
save
(
'result.jpg'
)
```
结果是一个list,每个item只包含文本框
```
bash
[[
26.0, 457.0],
[
137.0, 457.0],
[
137.0, 477.0],
[
26.0, 477.0]]
[[
25.0, 425.0],
[
372.0, 425.0],
[
372.0, 448.0],
[
25.0, 448.0]]
[[
128.0, 397.0],
[
273.0, 397.0],
[
273.0, 414.0],
[
128.0, 414.0]]
......
```
结果可视化
...
...
@@ -133,29 +156,37 @@ im_show.save('result.jpg')
</div>
*
单独执行识别
```
python
from
paddleocr
import
PaddleOCR
ocr
=
PaddleOCR
()
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
()
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs_words/ch/word_1.jpg'
result
=
ocr
.
ocr
(
img_path
,
det
=
False
)
for
line
in
result
:
print
(
line
)
```
结果是一个list,每个item只包含识别结果和识别置信度
```
bash
[
'韩国小馆'
, 0.9907421]
```
*
单独执行方向分类器
```
python
from
paddleocr
import
PaddleOCR
ocr
=
PaddleOCR
(
use_angle_cls
=
True
)
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
(
use_angle_cls
=
True
)
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs_words/ch/word_1.jpg'
result
=
ocr
.
ocr
(
img_path
,
det
=
False
,
rec
=
False
,
cls
=
True
)
for
line
in
result
:
print
(
line
)
```
结果是一个list,每个item只包含分类结果和分类置信度
```
bash
[
'0'
, 0.9999924]
```
...
...
@@ -163,15 +194,19 @@ for line in result:
### 2.2 通过命令行使用
查看帮助信息
```
bash
paddleocr
-h
```
*
检测+方向分类器+识别全流程
```
bash
paddleocr
--image_dir
PaddleOCR/doc/imgs/11.jpg
--use_angle_cls
true
```
结果是一个list,每个item包含了文本框,文字和识别置信度
```
bash
[[[
24.0, 36.0],
[
304.0, 34.0],
[
304.0, 72.0],
[
24.0, 74.0]],
[
'纯臻营养护发素'
, 0.964739]]
[[[
24.0, 80.0],
[
172.0, 80.0],
[
172.0, 104.0],
[
24.0, 104.0]],
[
'产品信息/参数'
, 0.98069626]]
...
...
@@ -180,10 +215,13 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --use_angle_cls true
```
*
检测+识别
```
bash
paddleocr
--image_dir
PaddleOCR/doc/imgs/11.jpg
```
结果是一个list,每个item包含了文本框,文字和识别置信度
```
bash
[[[
24.0, 36.0],
[
304.0, 34.0],
[
304.0, 72.0],
[
24.0, 74.0]],
[
'纯臻营养护发素'
, 0.964739]]
[[[
24.0, 80.0],
[
172.0, 80.0],
[
172.0, 104.0],
[
24.0, 104.0]],
[
'产品信息/参数'
, 0.98069626]]
...
...
@@ -192,20 +230,25 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg
```
*
方向分类器+识别
```
bash
paddleocr
--image_dir
PaddleOCR/doc/imgs_words/ch/word_1.jpg
--use_angle_cls
true
--det
false
```
结果是一个list,每个item只包含识别结果和识别置信度
```
bash
[
'韩国小馆'
, 0.9907421]
```
*
单独执行检测
```
bash
paddleocr
--image_dir
PaddleOCR/doc/imgs/11.jpg
--rec
false
```
结果是一个list,每个item只包含文本框
```
bash
[[
26.0, 457.0],
[
137.0, 457.0],
[
137.0, 477.0],
[
26.0, 477.0]]
[[
25.0, 425.0],
[
372.0, 425.0],
[
372.0, 448.0],
[
25.0, 448.0]]
...
...
@@ -214,34 +257,42 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --rec false
```
*
单独执行识别
```
bash
paddleocr
--image_dir
PaddleOCR/doc/imgs_words/ch/word_1.jpg
--det
false
```
结果是一个list,每个item只包含识别结果和识别置信度
```
bash
[
'韩国小馆'
, 0.9907421]
```
*
单独执行方向分类器
```
bash
paddleocr
--image_dir
PaddleOCR/doc/imgs_words/ch/word_1.jpg
--use_angle_cls
true
--det
false
--rec
false
```
结果是一个list,每个item只包含分类结果和分类置信度
```
bash
[
'0'
, 0.9999924]
```
## 3 自定义模型
当内置模型无法满足需求时,需要使用到自己训练的模型。
首先,参照
[
inference.md
](
./inference.md
)
第一节转换将检测、分类和识别模型转换为inference模型,然后按照如下方式使用
当内置模型无法满足需求时,需要使用到自己训练的模型。
首先,参照
[
inference.md
](
./inference.md
)
第一节转换将检测、分类和识别模型转换为inference模型,然后按照如下方式使用
### 3.1 代码使用
```
python
from
paddleocr
import
PaddleOCR
,
draw_ocr
# 模型路径下必须含有model和params文件
ocr
=
PaddleOCR
(
det_model_dir
=
'{your_det_model_dir}'
,
rec_model_dir
=
'{your_rec_model_dir}'
,
rec_char_dict_path
=
'{your_rec_char_dict_path}'
,
cls_model_dir
=
'{your_cls_model_dir}'
,
use_angle_cls
=
True
)
ocr
=
PaddleOCR
(
det_model_dir
=
'{your_det_model_dir}'
,
rec_model_dir
=
'{your_rec_model_dir}'
,
rec_char_dict_path
=
'{your_rec_char_dict_path}'
,
cls_model_dir
=
'{your_cls_model_dir}'
,
use_angle_cls
=
True
)
img_path
=
'PaddleOCR/doc/imgs/11.jpg'
result
=
ocr
.
ocr
(
img_path
,
cls
=
True
)
for
line
in
result
:
...
...
@@ -249,6 +300,7 @@ for line in result:
# 显示结果
from
PIL
import
Image
image
=
Image
.
open
(
img_path
).
convert
(
'RGB'
)
boxes
=
[
line
[
0
]
for
line
in
result
]
txts
=
[
line
[
1
][
0
]
for
line
in
result
]
...
...
@@ -269,11 +321,13 @@ paddleocr --image_dir PaddleOCR/doc/imgs/11.jpg --det_model_dir {your_det_model_
### 4.1 网络图片
-
代码使用
```
python
from
paddleocr
import
PaddleOCR
,
draw_ocr
from
paddleocr
import
PaddleOCR
,
draw_ocr
,
download_with_progressbar
# Paddleocr目前支持中英文、英文、法语、德语、韩语、日语,可以通过修改lang参数进行切换
# 参数依次为`ch`, `en`, `french`, `german`, `korean`, `japan`。
ocr
=
PaddleOCR
(
use_angle_cls
=
True
,
lang
=
"ch"
)
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
(
use_angle_cls
=
True
,
lang
=
"ch"
)
# need to run only once to download and load model into memory
img_path
=
'http://n.sinaimg.cn/ent/transform/w630h933/20171222/o111-fypvuqf1838418.jpg'
result
=
ocr
.
ocr
(
img_path
,
cls
=
True
)
for
line
in
result
:
...
...
@@ -281,7 +335,9 @@ for line in result:
# 显示结果
from
PIL
import
Image
image
=
Image
.
open
(
img_path
).
convert
(
'RGB'
)
download_with_progressbar
(
img_path
,
'tmp.jpg'
)
image
=
Image
.
open
(
'tmp.jpg'
).
convert
(
'RGB'
)
boxes
=
[
line
[
0
]
for
line
in
result
]
txts
=
[
line
[
1
][
0
]
for
line
in
result
]
scores
=
[
line
[
1
][
1
]
for
line
in
result
]
...
...
@@ -289,19 +345,24 @@ im_show = draw_ocr(image, boxes, txts, scores, font_path='/path/to/PaddleOCR/doc
im_show
=
Image
.
fromarray
(
im_show
)
im_show
.
save
(
'result.jpg'
)
```
-
命令行模式
```
bash
paddleocr
--image_dir
http://n.sinaimg.cn/ent/transform/w630h933/20171222/o111-fypvuqf1838418.jpg
--use_angle_cls
=
true
```
### 4.2 numpy数组
仅通过代码使用时支持numpy数组作为输入
```
python
import
cv2
from
paddleocr
import
PaddleOCR
,
draw_ocr
# Paddleocr目前支持中英文、英文、法语、德语、韩语、日语,可以通过修改lang参数进行切换
# 参数依次为`ch`, `en`, `french`, `german`, `korean`, `japan`。
ocr
=
PaddleOCR
(
use_angle_cls
=
True
,
lang
=
"ch"
)
# need to run only once to download and load model into memory
ocr
=
PaddleOCR
(
use_angle_cls
=
True
,
lang
=
"ch"
)
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs/11.jpg'
img
=
cv2
.
imread
(
img_path
)
# img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY), 如果你自己训练的模型支持灰度图,可以将这句话的注释取消
...
...
@@ -311,6 +372,7 @@ for line in result:
# 显示结果
from
PIL
import
Image
image
=
Image
.
open
(
img_path
).
convert
(
'RGB'
)
boxes
=
[
line
[
0
]
for
line
in
result
]
txts
=
[
line
[
1
][
0
]
for
line
in
result
]
...
...
doc/doc_en/whl_en.md
浏览文件 @
a5694968
...
...
@@ -306,7 +306,7 @@ Support numpy array as input only when used by code
```
python
import
cv2
from
paddleocr
import
PaddleOCR
,
draw_ocr
from
paddleocr
import
PaddleOCR
,
draw_ocr
,
download_with_progressbar
ocr
=
PaddleOCR
(
use_angle_cls
=
True
,
lang
=
"ch"
)
# need to run only once to download and load model into memory
img_path
=
'PaddleOCR/doc/imgs/11.jpg'
img
=
cv2
.
imread
(
img_path
)
...
...
@@ -317,7 +317,9 @@ for line in result:
# show result
from
PIL
import
Image
image
=
Image
.
open
(
img_path
).
convert
(
'RGB'
)
download_with_progressbar
(
img_path
,
'tmp.jpg'
)
image
=
Image
.
open
(
'tmp.jpg'
).
convert
(
'RGB'
)
boxes
=
[
line
[
0
]
for
line
in
result
]
txts
=
[
line
[
1
][
0
]
for
line
in
result
]
scores
=
[
line
[
1
][
1
]
for
line
in
result
]
...
...
paddleocr.py
浏览文件 @
a5694968
...
...
@@ -33,7 +33,7 @@ from tools.infer.utility import draw_ocr, str2bool
from
ppstructure.utility
import
init_args
,
draw_structure_result
from
ppstructure.predict_system
import
OCRSystem
,
save_structure_res
__all__
=
[
'PaddleOCR'
,
'PPStructure'
,
'draw_ocr'
,
'draw_structure_result'
,
'save_structure_res'
]
__all__
=
[
'PaddleOCR'
,
'PPStructure'
,
'draw_ocr'
,
'draw_structure_result'
,
'save_structure_res'
,
'download_with_progressbar'
]
model_urls
=
{
'det'
:
{
...
...
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