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Unverified Commit aa1d40b1 authored by Double_V's avatar Double_V Committed by GitHub
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Merge branch 'dygraph' into bm_dyg

parents b796c916 2c2918f2
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MANIFEST.in
View file @ aa1d40b1
include LICENSE.txt include LICENSE
include README.md include README.md
recursive-include ppocr/utils *.txt utility.py logging.py recursive-include ppocr/utils *.txt utility.py logging.py network.py
recursive-include ppocr/data/ *.py recursive-include ppocr/data/ *.py
recursive-include ppocr/postprocess *.py recursive-include ppocr/postprocess *.py
recursive-include tools/infer *.py recursive-include tools/infer *.py
......
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MainActivity.java
View file @ aa1d40b1
...@@ -465,8 +465,12 @@ public class MainActivity extends AppCompatActivity { ...@@ -465,8 +465,12 @@ public class MainActivity extends AppCompatActivity {
} }
public void btn_load_model_click(View view) { public void btn_load_model_click(View view) {
tvStatus.setText("STATUS: load model ......"); if (predictor.isLoaded()){
loadModel(); tvStatus.setText("STATUS: model has been loaded");
}else{
tvStatus.setText("STATUS: load model ......");
loadModel();
}
} }
public void btn_run_model_click(View view) { public void btn_run_model_click(View view) {
......
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Predictor.java
View file @ aa1d40b1
...@@ -194,26 +194,25 @@ public class Predictor { ...@@ -194,26 +194,25 @@ public class Predictor {
"supported!"); "supported!");
return false; return false;
} }
int[] channelStride = new int[]{width * height, width * height * 2};
int p = scaleImage.getPixel(scaleImage.getWidth() - 1, scaleImage.getHeight() - 1);
for (int y = 0; y < height; y++) {
for (int x = 0; x < width; x++) {
int color = scaleImage.getPixel(x, y);
float[] rgb = new float[]{(float) red(color) / 255.0f, (float) green(color) / 255.0f,
(float) blue(color) / 255.0f};
inputData[y * width + x] = (rgb[channelIdx[0]] - inputMean[0]) / inputStd[0];
inputData[y * width + x + channelStride[0]] = (rgb[channelIdx[1]] - inputMean[1]) / inputStd[1];
inputData[y * width + x + channelStride[1]] = (rgb[channelIdx[2]] - inputMean[2]) / inputStd[2];
} int[] channelStride = new int[]{width * height, width * height * 2};
int[] pixels=new int[width*height];
scaleImage.getPixels(pixels,0,scaleImage.getWidth(),0,0,scaleImage.getWidth(),scaleImage.getHeight());
for (int i = 0; i < pixels.length; i++) {
int color = pixels[i];
float[] rgb = new float[]{(float) red(color) / 255.0f, (float) green(color) / 255.0f,
(float) blue(color) / 255.0f};
inputData[i] = (rgb[channelIdx[0]] - inputMean[0]) / inputStd[0];
inputData[i + channelStride[0]] = (rgb[channelIdx[1]] - inputMean[1]) / inputStd[1];
inputData[i+ channelStride[1]] = (rgb[channelIdx[2]] - inputMean[2]) / inputStd[2];
} }
} else if (channels == 1) { } else if (channels == 1) {
for (int y = 0; y < height; y++) { int[] pixels=new int[width*height];
for (int x = 0; x < width; x++) { scaleImage.getPixels(pixels,0,scaleImage.getWidth(),0,0,scaleImage.getWidth(),scaleImage.getHeight());
int color = inputImage.getPixel(x, y); for (int i = 0; i < pixels.length; i++) {
float gray = (float) (red(color) + green(color) + blue(color)) / 3.0f / 255.0f; int color = pixels[i];
inputData[y * width + x] = (gray - inputMean[0]) / inputStd[0]; float gray = (float) (red(color) + green(color) + blue(color)) / 3.0f / 255.0f;
} inputData[i] = (gray - inputMean[0]) / inputStd[0];
} }
} else { } else {
Log.i(TAG, "Unsupported channel size " + Integer.toString(channels) + ", only channel 1 and 3 is " + Log.i(TAG, "Unsupported channel size " + Integer.toString(channels) + ", only channel 1 and 3 is " +
......
doc/doc_ch/config.md
View file @ aa1d40b1
...@@ -111,9 +111,9 @@ ...@@ -111,9 +111,9 @@
| 字段 | 用途 | 默认值 | 备注 | | 字段 | 用途 | 默认值 | 备注 |
| :---------------------: | :---------------------: | :--------------: | :--------------------: | | :---------------------: | :---------------------: | :--------------: | :--------------------: |
| **dataset** | 每次迭代返回一个样本 | - | - | | **dataset** | 每次迭代返回一个样本 | - | - |
| name | dataset类名 | SimpleDataSet | 目前支持`SimpleDataSet`和`LMDBDateSet` | | name | dataset类名 | SimpleDataSet | 目前支持`SimpleDataSet`和`LMDBDataSet` |
| data_dir | 数据集图片存放路径 | ./train_data | \ | | data_dir | 数据集图片存放路径 | ./train_data | \ |
| label_file_list | 数据标签路径 | ["./train_data/train_list.txt"] | dataset为LMDBDateSet时不需要此参数 | | label_file_list | 数据标签路径 | ["./train_data/train_list.txt"] | dataset为LMDBDataSet时不需要此参数 |
| ratio_list | 数据集的比例 | [1.0] | 若label_file_list中有两个train_list，且ratio_list为[0.4,0.6]，则从train_list1中采样40%，从train_list2中采样60%组合整个dataset | | ratio_list | 数据集的比例 | [1.0] | 若label_file_list中有两个train_list，且ratio_list为[0.4,0.6]，则从train_list1中采样40%，从train_list2中采样60%组合整个dataset |
| transforms | 对图片和标签进行变换的方法列表 | [DecodeImage,CTCLabelEncode,RecResizeImg,KeepKeys] | 见[ppocr/data/imaug](../../ppocr/data/imaug) | | transforms | 对图片和标签进行变换的方法列表 | [DecodeImage,CTCLabelEncode,RecResizeImg,KeepKeys] | 见[ppocr/data/imaug](../../ppocr/data/imaug) |
| **loader** | dataloader相关 | - | | | **loader** | dataloader相关 | - | |
......
doc/doc_ch/recognition.md
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...@@ -243,7 +243,7 @@ Optimizer: ...@@ -243,7 +243,7 @@ Optimizer:
Train: Train:
dataset: dataset:
# 数据集格式，支持LMDBDateSet以及SimpleDataSet # 数据集格式，支持LMDBDataSet以及SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# 数据集路径 # 数据集路径
data_dir: ./train_data/ data_dir: ./train_data/
...@@ -263,7 +263,7 @@ Train: ...@@ -263,7 +263,7 @@ Train:
Eval: Eval:
dataset: dataset:
# 数据集格式，支持LMDBDateSet以及SimpleDataSet # 数据集格式，支持LMDBDataSet以及SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# 数据集路径 # 数据集路径
data_dir: ./train_data data_dir: ./train_data
...@@ -393,7 +393,7 @@ Global: ...@@ -393,7 +393,7 @@ Global:
Train: Train:
dataset: dataset:
# 数据集格式，支持LMDBDateSet以及SimpleDataSet # 数据集格式，支持LMDBDataSet以及SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# 数据集路径 # 数据集路径
data_dir: ./train_data/ data_dir: ./train_data/
...@@ -403,7 +403,7 @@ Train: ...@@ -403,7 +403,7 @@ Train:
Eval: Eval:
dataset: dataset:
# 数据集格式，支持LMDBDateSet以及SimpleDataSet # 数据集格式，支持LMDBDataSet以及SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# 数据集路径 # 数据集路径
data_dir: ./train_data data_dir: ./train_data
......
doc/doc_en/config_en.md
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...@@ -110,9 +110,9 @@ In ppocr, the network is divided into four stages: Transform, Backbone, Neck and ...@@ -110,9 +110,9 @@ In ppocr, the network is divided into four stages: Transform, Backbone, Neck and
| Parameter | Use | Defaults | Note | | Parameter | Use | Defaults | Note |
| :---------------------: | :---------------------: | :--------------: | :--------------------: | | :---------------------: | :---------------------: | :--------------: | :--------------------: |
| **dataset** | Return one sample per iteration | - | - | | **dataset** | Return one sample per iteration | - | - |
| name | dataset class name | SimpleDataSet | Currently support`SimpleDataSet`,`LMDBDateSet` | | name | dataset class name | SimpleDataSet | Currently support`SimpleDataSet`,`LMDBDataSet` |
| data_dir | Image folder path | ./train_data | \ | | data_dir | Image folder path | ./train_data | \ |
| label_file_list | Groundtruth file path | ["./train_data/train_list.txt"] | This parameter is not required when dataset is LMDBDateSet | | label_file_list | Groundtruth file path | ["./train_data/train_list.txt"] | This parameter is not required when dataset is LMDBDataSet |
| ratio_list | Ratio of data set | [1.0] | If there are two train_lists in label_file_list and ratio_list is [0.4,0.6], 40% will be sampled from train_list1, and 60% will be sampled from train_list2 to combine the entire dataset | | ratio_list | Ratio of data set | [1.0] | If there are two train_lists in label_file_list and ratio_list is [0.4,0.6], 40% will be sampled from train_list1, and 60% will be sampled from train_list2 to combine the entire dataset |
| transforms | List of methods to transform images and labels | [DecodeImage,CTCLabelEncode,RecResizeImg,KeepKeys] | see[ppocr/data/imaug](../../ppocr/data/imaug) | | transforms | List of methods to transform images and labels | [DecodeImage,CTCLabelEncode,RecResizeImg,KeepKeys] | see[ppocr/data/imaug](../../ppocr/data/imaug) |
| **loader** | dataloader related | - | | | **loader** | dataloader related | - | |
......
doc/doc_en/recognition_en.md
View file @ aa1d40b1
...@@ -237,7 +237,7 @@ Optimizer: ...@@ -237,7 +237,7 @@ Optimizer:
Train: Train:
dataset: dataset:
# Type of dataset，we support LMDBDateSet and SimpleDataSet # Type of dataset，we support LMDBDataSet and SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# Path of dataset # Path of dataset
data_dir: ./train_data/ data_dir: ./train_data/
...@@ -257,7 +257,7 @@ Train: ...@@ -257,7 +257,7 @@ Train:
Eval: Eval:
dataset: dataset:
# Type of dataset，we support LMDBDateSet and SimpleDataSet # Type of dataset，we support LMDBDataSet and SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# Path of dataset # Path of dataset
data_dir: ./train_data data_dir: ./train_data
...@@ -394,7 +394,7 @@ Global: ...@@ -394,7 +394,7 @@ Global:
Train: Train:
dataset: dataset:
# Type of dataset，we support LMDBDateSet and SimpleDataSet # Type of dataset，we support LMDBDataSet and SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# Path of dataset # Path of dataset
data_dir: ./train_data/ data_dir: ./train_data/
...@@ -404,7 +404,7 @@ Train: ...@@ -404,7 +404,7 @@ Train:
Eval: Eval:
dataset: dataset:
# Type of dataset，we support LMDBDateSet and SimpleDataSet # Type of dataset，we support LMDBDataSet and SimpleDataSet
name: SimpleDataSet name: SimpleDataSet
# Path of dataset # Path of dataset
data_dir: ./train_data data_dir: ./train_data
......
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  • 2-up
  • Swipe
  • Onion skin
paddleocr.py
View file @ aa1d40b1
...@@ -19,17 +19,16 @@ __dir__ = os.path.dirname(__file__) ...@@ -19,17 +19,16 @@ __dir__ = os.path.dirname(__file__)
sys.path.append(os.path.join(__dir__, '')) sys.path.append(os.path.join(__dir__, ''))
import cv2 import cv2
import logging
import numpy as np import numpy as np
from pathlib import Path from pathlib import Path
import tarfile
import requests
from tqdm import tqdm
from tools.infer import predict_system from tools.infer import predict_system
from ppocr.utils.logging import get_logger from ppocr.utils.logging import get_logger
logger = get_logger() logger = get_logger()
from ppocr.utils.utility import check_and_read_gif, get_image_file_list from ppocr.utils.utility import check_and_read_gif, get_image_file_list
from ppocr.utils.network import maybe_download, download_with_progressbar
from tools.infer.utility import draw_ocr, init_args, str2bool from tools.infer.utility import draw_ocr, init_args, str2bool
__all__ = ['PaddleOCR'] __all__ = ['PaddleOCR']
...@@ -37,84 +36,84 @@ __all__ = ['PaddleOCR'] ...@@ -37,84 +36,84 @@ __all__ = ['PaddleOCR']
model_urls = { model_urls = {
'det': { 'det': {
'ch': 'ch':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar',
'en': 'en':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar' 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar'
}, },
'rec': { 'rec': {
'ch': { 'ch': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt' 'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
}, },
'en': { 'en': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/en_dict.txt' 'dict_path': './ppocr/utils/en_dict.txt'
}, },
'french': { 'french': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/french_dict.txt' 'dict_path': './ppocr/utils/dict/french_dict.txt'
}, },
'german': { 'german': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/german_dict.txt' 'dict_path': './ppocr/utils/dict/german_dict.txt'
}, },
'korean': { 'korean': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/korean_dict.txt' 'dict_path': './ppocr/utils/dict/korean_dict.txt'
}, },
'japan': { 'japan': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/japan_dict.txt' 'dict_path': './ppocr/utils/dict/japan_dict.txt'
}, },
'chinese_cht': { 'chinese_cht': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt' 'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt'
}, },
'ta': { 'ta': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ta_dict.txt' 'dict_path': './ppocr/utils/dict/ta_dict.txt'
}, },
'te': { 'te': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/te_dict.txt' 'dict_path': './ppocr/utils/dict/te_dict.txt'
}, },
'ka': { 'ka': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/ka_dict.txt' 'dict_path': './ppocr/utils/dict/ka_dict.txt'
}, },
'latin': { 'latin': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/latin_dict.txt' 'dict_path': './ppocr/utils/dict/latin_dict.txt'
}, },
'arabic': { 'arabic': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/arabic_dict.txt' 'dict_path': './ppocr/utils/dict/arabic_dict.txt'
}, },
'cyrillic': { 'cyrillic': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/cyrillic_dict.txt' 'dict_path': './ppocr/utils/dict/cyrillic_dict.txt'
}, },
'devanagari': { 'devanagari': {
'url': 'url':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar', 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar',
'dict_path': './ppocr/utils/dict/devanagari_dict.txt' 'dict_path': './ppocr/utils/dict/devanagari_dict.txt'
} }
}, },
'cls': 'cls':
'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar' 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar'
} }
SUPPORT_DET_MODEL = ['DB'] SUPPORT_DET_MODEL = ['DB']
...@@ -123,50 +122,6 @@ SUPPORT_REC_MODEL = ['CRNN'] ...@@ -123,50 +122,6 @@ SUPPORT_REC_MODEL = ['CRNN']
BASE_DIR = os.path.expanduser("~/.paddleocr/") BASE_DIR = os.path.expanduser("~/.paddleocr/")
def download_with_progressbar(url, save_path):
response = requests.get(url, stream=True)
total_size_in_bytes = int(response.headers.get('content-length', 0))
block_size = 1024 # 1 Kibibyte
progress_bar = tqdm(total=total_size_in_bytes, unit='iB', unit_scale=True)
with open(save_path, 'wb') as file:
for data in response.iter_content(block_size):
progress_bar.update(len(data))
file.write(data)
progress_bar.close()
if total_size_in_bytes == 0 or progress_bar.n != total_size_in_bytes:
logger.error("Something went wrong while downloading models")
sys.exit(0)
def maybe_download(model_storage_directory, url):
# using custom model
tar_file_name_list = [
'inference.pdiparams', 'inference.pdiparams.info', 'inference.pdmodel'
]
if not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdiparams')
) or not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdmodel')):
tmp_path = os.path.join(model_storage_directory, url.split('/')[-1])
print('download {} to {}'.format(url, tmp_path))
os.makedirs(model_storage_directory, exist_ok=True)
download_with_progressbar(url, tmp_path)
with tarfile.open(tmp_path, 'r') as tarObj:
for member in tarObj.getmembers():
filename = None
for tar_file_name in tar_file_name_list:
if tar_file_name in member.name:
filename = tar_file_name
if filename is None:
continue
file = tarObj.extractfile(member)
with open(
os.path.join(model_storage_directory, filename),
'wb') as f:
f.write(file.read())
os.remove(tmp_path)
def parse_args(mMain=True): def parse_args(mMain=True):
import argparse import argparse
parser = init_args() parser = init_args()
...@@ -194,10 +149,12 @@ class PaddleOCR(predict_system.TextSystem): ...@@ -194,10 +149,12 @@ class PaddleOCR(predict_system.TextSystem):
args: args:
**kwargs: other params show in paddleocr --help **kwargs: other params show in paddleocr --help
""" """
postprocess_params = parse_args(mMain=False) params = parse_args(mMain=False)
postprocess_params.__dict__.update(**kwargs) params.__dict__.update(**kwargs)
self.use_angle_cls = postprocess_params.use_angle_cls if params.show_log:
lang = postprocess_params.lang logger.setLevel(logging.DEBUG)
self.use_angle_cls = params.use_angle_cls
lang = params.lang
latin_lang = [ latin_lang = [
'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga', 'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga',
'hr', 'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms', 'hr', 'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms',
...@@ -223,46 +180,46 @@ class PaddleOCR(predict_system.TextSystem): ...@@ -223,46 +180,46 @@ class PaddleOCR(predict_system.TextSystem):
lang = "devanagari" lang = "devanagari"
assert lang in model_urls[ assert lang in model_urls[
'rec'], 'param lang must in {}, but got {}'.format( 'rec'], 'param lang must in {}, but got {}'.format(
model_urls['rec'].keys(), lang) model_urls['rec'].keys(), lang)
if lang == "ch": if lang == "ch":
det_lang = "ch" det_lang = "ch"
else: else:
det_lang = "en" det_lang = "en"
use_inner_dict = False use_inner_dict = False
if postprocess_params.rec_char_dict_path is None: if params.rec_char_dict_path is None:
use_inner_dict = True use_inner_dict = True
postprocess_params.rec_char_dict_path = model_urls['rec'][lang][ params.rec_char_dict_path = model_urls['rec'][lang][
'dict_path'] 'dict_path']
# init model dir # init model dir
if postprocess_params.det_model_dir is None: if params.det_model_dir is None:
postprocess_params.det_model_dir = os.path.join(BASE_DIR, VERSION, params.det_model_dir = os.path.join(BASE_DIR, VERSION,
'det', det_lang) 'det', det_lang)
if postprocess_params.rec_model_dir is None: if params.rec_model_dir is None:
postprocess_params.rec_model_dir = os.path.join(BASE_DIR, VERSION, params.rec_model_dir = os.path.join(BASE_DIR, VERSION,
'rec', lang) 'rec', lang)
if postprocess_params.cls_model_dir is None: if params.cls_model_dir is None:
postprocess_params.cls_model_dir = os.path.join(BASE_DIR, 'cls') params.cls_model_dir = os.path.join(BASE_DIR, 'cls')
print(postprocess_params)
# download model # download model
maybe_download(postprocess_params.det_model_dir, maybe_download(params.det_model_dir,
model_urls['det'][det_lang]) model_urls['det'][det_lang])
maybe_download(postprocess_params.rec_model_dir, maybe_download(params.rec_model_dir,
model_urls['rec'][lang]['url']) model_urls['rec'][lang]['url'])
maybe_download(postprocess_params.cls_model_dir, model_urls['cls']) maybe_download(params.cls_model_dir, model_urls['cls'])
if postprocess_params.det_algorithm not in SUPPORT_DET_MODEL: if params.det_algorithm not in SUPPORT_DET_MODEL:
logger.error('det_algorithm must in {}'.format(SUPPORT_DET_MODEL)) logger.error('det_algorithm must in {}'.format(SUPPORT_DET_MODEL))
sys.exit(0) sys.exit(0)
if postprocess_params.rec_algorithm not in SUPPORT_REC_MODEL: if params.rec_algorithm not in SUPPORT_REC_MODEL:
logger.error('rec_algorithm must in {}'.format(SUPPORT_REC_MODEL)) logger.error('rec_algorithm must in {}'.format(SUPPORT_REC_MODEL))
sys.exit(0) sys.exit(0)
if use_inner_dict: if use_inner_dict:
postprocess_params.rec_char_dict_path = str( params.rec_char_dict_path = str(
Path(__file__).parent / postprocess_params.rec_char_dict_path) Path(__file__).parent / params.rec_char_dict_path)
print(params)
# init det_model and rec_model # init det_model and rec_model
super().__init__(postprocess_params) super().__init__(params)
def ocr(self, img, det=True, rec=True, cls=True): def ocr(self, img, det=True, rec=True, cls=True):
""" """
......
ppocr/data/imaug/operators.py
View file @ aa1d40b1
...@@ -81,7 +81,7 @@ class NormalizeImage(object): ...@@ -81,7 +81,7 @@ class NormalizeImage(object):
assert isinstance(img, assert isinstance(img,
np.ndarray), "invalid input 'img' in NormalizeImage" np.ndarray), "invalid input 'img' in NormalizeImage"
data['image'] = ( data['image'] = (
img.astype('float32') * self.scale - self.mean) / self.std img.astype('float32') * self.scale - self.mean) / self.std
return data return data
...@@ -163,7 +163,7 @@ class DetResizeForTest(object): ...@@ -163,7 +163,7 @@ class DetResizeForTest(object):
img, (ratio_h, ratio_w) img, (ratio_h, ratio_w)
""" """
limit_side_len = self.limit_side_len limit_side_len = self.limit_side_len
h, w, _ = img.shape h, w, c = img.shape
# limit the max side # limit the max side
if self.limit_type == 'max': if self.limit_type == 'max':
...@@ -174,7 +174,7 @@ class DetResizeForTest(object): ...@@ -174,7 +174,7 @@ class DetResizeForTest(object):
ratio = float(limit_side_len) / w ratio = float(limit_side_len) / w
else: else:
ratio = 1. ratio = 1.
else: elif self.limit_type == 'min':
if min(h, w) < limit_side_len: if min(h, w) < limit_side_len:
if h < w: if h < w:
ratio = float(limit_side_len) / h ratio = float(limit_side_len) / h
...@@ -182,6 +182,10 @@ class DetResizeForTest(object): ...@@ -182,6 +182,10 @@ class DetResizeForTest(object):
ratio = float(limit_side_len) / w ratio = float(limit_side_len) / w
else: else:
ratio = 1. ratio = 1.
elif self.limit_type == 'resize_long':
ratio = float(limit_side_len) / max(h,w)
else:
raise Exception('not support limit type, image ')
resize_h = int(h * ratio) resize_h = int(h * ratio)
resize_w = int(w * ratio) resize_w = int(w * ratio)
......
ppocr/postprocess/rec_postprocess.py
View file @ aa1d40b1
...@@ -44,16 +44,16 @@ class BaseRecLabelDecode(object): ...@@ -44,16 +44,16 @@ class BaseRecLabelDecode(object):
self.character_str = string.printable[:-6] self.character_str = string.printable[:-6]
dict_character = list(self.character_str) dict_character = list(self.character_str)
elif character_type in support_character_type: elif character_type in support_character_type:
self.character_str = "" self.character_str = []
assert character_dict_path is not None, "character_dict_path should not be None when character_type is {}".format( assert character_dict_path is not None, "character_dict_path should not be None when character_type is {}".format(
character_type) character_type)
with open(character_dict_path, "rb") as fin: with open(character_dict_path, "rb") as fin:
lines = fin.readlines() lines = fin.readlines()
for line in lines: for line in lines:
line = line.decode('utf-8').strip("\n").strip("\r\n") line = line.decode('utf-8').strip("\n").strip("\r\n")
self.character_str += line self.character_str.append(line)
if use_space_char: if use_space_char:
self.character_str += " " self.character_str.append(" ")
dict_character = list(self.character_str) dict_character = list(self.character_str)
else: else:
...@@ -288,3 +288,156 @@ class SRNLabelDecode(BaseRecLabelDecode): ...@@ -288,3 +288,156 @@ class SRNLabelDecode(BaseRecLabelDecode):
assert False, "unsupport type %s in get_beg_end_flag_idx" \ assert False, "unsupport type %s in get_beg_end_flag_idx" \
% beg_or_end % beg_or_end
return idx return idx
class TableLabelDecode(object):
""" """
def __init__(self,
max_text_length,
max_elem_length,
max_cell_num,
character_dict_path,
**kwargs):
self.max_text_length = max_text_length
self.max_elem_length = max_elem_length
self.max_cell_num = max_cell_num
list_character, list_elem = self.load_char_elem_dict(character_dict_path)
list_character = self.add_special_char(list_character)
list_elem = self.add_special_char(list_elem)
self.dict_character = {}
self.dict_idx_character = {}
for i, char in enumerate(list_character):
self.dict_idx_character[i] = char
self.dict_character[char] = i
self.dict_elem = {}
self.dict_idx_elem = {}
for i, elem in enumerate(list_elem):
self.dict_idx_elem[i] = elem
self.dict_elem[elem] = i
def load_char_elem_dict(self, character_dict_path):
list_character = []
list_elem = []
with open(character_dict_path, "rb") as fin:
lines = fin.readlines()
substr = lines[0].decode('utf-8').strip("\n").split("\t")
character_num = int(substr[0])
elem_num = int(substr[1])
for cno in range(1, 1 + character_num):
character = lines[cno].decode('utf-8').strip("\n")
list_character.append(character)
for eno in range(1 + character_num, 1 + character_num + elem_num):
elem = lines[eno].decode('utf-8').strip("\n")
list_elem.append(elem)
return list_character, list_elem
def add_special_char(self, list_character):
self.beg_str = "sos"
self.end_str = "eos"
list_character = [self.beg_str] + list_character + [self.end_str]
return list_character
def get_sp_tokens(self):
char_beg_idx = self.get_beg_end_flag_idx('beg', 'char')
char_end_idx = self.get_beg_end_flag_idx('end', 'char')
elem_beg_idx = self.get_beg_end_flag_idx('beg', 'elem')
elem_end_idx = self.get_beg_end_flag_idx('end', 'elem')
elem_char_idx1 = self.dict_elem['<td>']
elem_char_idx2 = self.dict_elem['<td']
sp_tokens = np.array([char_beg_idx, char_end_idx, elem_beg_idx,
elem_end_idx, elem_char_idx1, elem_char_idx2, self.max_text_length,
self.max_elem_length, self.max_cell_num])
return sp_tokens
def __call__(self, preds):
structure_probs = preds['structure_probs']
loc_preds = preds['loc_preds']
if isinstance(structure_probs,paddle.Tensor):
structure_probs = structure_probs.numpy()
if isinstance(loc_preds,paddle.Tensor):
loc_preds = loc_preds.numpy()
structure_idx = structure_probs.argmax(axis=2)
structure_probs = structure_probs.max(axis=2)
structure_str, structure_pos, result_score_list, result_elem_idx_list = self.decode(structure_idx,
structure_probs, 'elem')
res_html_code_list = []
res_loc_list = []
batch_num = len(structure_str)
for bno in range(batch_num):
res_loc = []
for sno in range(len(structure_str[bno])):
text = structure_str[bno][sno]
if text in ['<td>', '<td']:
pos = structure_pos[bno][sno]
res_loc.append(loc_preds[bno, pos])
res_html_code = ''.join(structure_str[bno])
res_loc = np.array(res_loc)
res_html_code_list.append(res_html_code)
res_loc_list.append(res_loc)
return {'res_html_code': res_html_code_list, 'res_loc': res_loc_list, 'res_score_list': result_score_list,
'res_elem_idx_list': result_elem_idx_list,'structure_str_list':structure_str}
def decode(self, text_index, structure_probs, char_or_elem):
"""convert text-label into text-index.
"""
if char_or_elem == "char":
current_dict = self.dict_idx_character
else:
current_dict = self.dict_idx_elem
ignored_tokens = self.get_ignored_tokens('elem')
beg_idx, end_idx = ignored_tokens
result_list = []
result_pos_list = []
result_score_list = []
result_elem_idx_list = []
batch_size = len(text_index)
for batch_idx in range(batch_size):
char_list = []
elem_pos_list = []
elem_idx_list = []
score_list = []
for idx in range(len(text_index[batch_idx])):
tmp_elem_idx = int(text_index[batch_idx][idx])
if idx > 0 and tmp_elem_idx == end_idx:
break
if tmp_elem_idx in ignored_tokens:
continue
char_list.append(current_dict[tmp_elem_idx])
elem_pos_list.append(idx)
score_list.append(structure_probs[batch_idx, idx])
elem_idx_list.append(tmp_elem_idx)
result_list.append(char_list)
result_pos_list.append(elem_pos_list)
result_score_list.append(score_list)
result_elem_idx_list.append(elem_idx_list)
return result_list, result_pos_list, result_score_list, result_elem_idx_list
def get_ignored_tokens(self, char_or_elem):
beg_idx = self.get_beg_end_flag_idx("beg", char_or_elem)
end_idx = self.get_beg_end_flag_idx("end", char_or_elem)
return [beg_idx, end_idx]
def get_beg_end_flag_idx(self, beg_or_end, char_or_elem):
if char_or_elem == "char":
if beg_or_end == "beg":
idx = self.dict_character[self.beg_str]
elif beg_or_end == "end":
idx = self.dict_character[self.end_str]
else:
assert False, "Unsupport type %s in get_beg_end_flag_idx of char" \
% beg_or_end
elif char_or_elem == "elem":
if beg_or_end == "beg":
idx = self.dict_elem[self.beg_str]
elif beg_or_end == "end":
idx = self.dict_elem[self.end_str]
else:
assert False, "Unsupport type %s in get_beg_end_flag_idx of elem" \
% beg_or_end
else:
assert False, "Unsupport type %s in char_or_elem" \
% char_or_elem
return idx
ppocr/utils/dict/table_dict.txt 0 → 100644
View file @ aa1d40b1
←
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}
ν
ppocr/utils/dict/table_structure_dict.txt 0 → 100644
View file @ aa1d40b1
This diff is collapsed.
ppocr/utils/network.py 0 → 100644
View file @ aa1d40b1
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
import tarfile
import requests
from tqdm import tqdm
from ppocr.utils.logging import get_logger
def download_with_progressbar(url, save_path):
logger = get_logger()
response = requests.get(url, stream=True)
total_size_in_bytes = int(response.headers.get('content-length', 0))
block_size = 1024 # 1 Kibibyte
progress_bar = tqdm(total=total_size_in_bytes, unit='iB', unit_scale=True)
with open(save_path, 'wb') as file:
for data in response.iter_content(block_size):
progress_bar.update(len(data))
file.write(data)
progress_bar.close()
if total_size_in_bytes == 0 or progress_bar.n != total_size_in_bytes:
logger.error("Something went wrong while downloading models")
sys.exit(0)
def maybe_download(model_storage_directory, url):
# using custom model
tar_file_name_list = [
'inference.pdiparams', 'inference.pdiparams.info', 'inference.pdmodel'
]
if not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdiparams')
) or not os.path.exists(
os.path.join(model_storage_directory, 'inference.pdmodel')):
assert url.endswith('.tar'), 'Only supports tar compressed package'
tmp_path = os.path.join(model_storage_directory, url.split('/')[-1])
print('download {} to {}'.format(url, tmp_path))
os.makedirs(model_storage_directory, exist_ok=True)
download_with_progressbar(url, tmp_path)
with tarfile.open(tmp_path, 'r') as tarObj:
for member in tarObj.getmembers():
filename = None
for tar_file_name in tar_file_name_list:
if tar_file_name in member.name:
filename = tar_file_name
if filename is None:
continue
file = tarObj.extractfile(member)
with open(
os.path.join(model_storage_directory, filename),
'wb') as f:
f.write(file.read())
os.remove(tmp_path)
def is_link(s):
return s is not None and s.startswith('http')
def confirm_model_dir_url(model_dir, default_model_dir, default_url):
url = default_url
if model_dir is None or is_link(model_dir):
if is_link(model_dir):
url = model_dir
file_name = url.split('/')[-1][:-4]
model_dir = default_model_dir
model_dir = os.path.join(model_dir, file_name)
return model_dir, url
ppstructure/MANIFEST.in 0 → 100644
View file @ aa1d40b1
include LICENSE
include README.md
recursive-include ppocr/utils *.txt utility.py logging.py network.py
recursive-include ppocr/data/ *.py
recursive-include ppocr/postprocess *.py
recursive-include tools/infer *.py
recursive-include ppstructure *.py
ppstructure/README_ch.md
View file @ aa1d40b1
# TableStructurer
1. 代码使用
```python
import cv2
from paddlestructure import PaddleStructure,draw_result
table_engine = PaddleStructure(
output='./output/table',
show_log=True)
img_path = '../doc/table/1.png'
img = cv2.imread(img_path)
result = table_engine(img)
for line in result:
print(line)
from PIL import Image
font_path = 'path/tp/PaddleOCR/doc/fonts/simfang.ttf'
image = Image.open(img_path).convert('RGB')
im_show = draw_result(image, result,font_path=font_path)
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
```
2. 命令行使用
```bash
paddlestructure --image_dir=../doc/table/1.png
```
ppstructure/__init__.py 0 → 100644
View file @ aa1d40b1
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .paddlestructure import PaddleStructure, draw_result, to_excel
__all__ = ['PaddleStructure', 'draw_result', 'to_excel']
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