Merge branch 'PaddlePaddle:dygraph' into dygraph

PPOCRLabel/README.md

@@ -34,10 +34,10 @@ PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field, w
 pip3 install --upgrade pip
 
 # If you have cuda9 or cuda10 installed on your machine, please run the following command to install
-python3 -m pip install paddlepaddle-gpu==2.0.0 -i https://mirror.baidu.com/pypi/simple
+python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
 
 # If you only have cpu on your machine, please run the following command to install
-python3 -m pip install paddlepaddle==2.0.0 -i https://mirror.baidu.com/pypi/simple
+python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
 ```
 
 For more software version requirements, please refer to the instructions in [Installation Document](https://www.paddlepaddle.org.cn/install/quick) for operation.

PPOCRLabel/README_ch.md

@@ -37,11 +37,11 @@ PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具，内置P
 pip3 install --upgrade pip
 
 如果您的机器安装的是CUDA9或CUDA10，请运行以下命令安装
-python3 -m pip install paddlepaddle-gpu==2.0.0 -i https://mirror.baidu.com/pypi/simple
+python3 -m pip install paddlepaddle-gpu -i https://mirror.baidu.com/pypi/simple
 
 如果您的机器是CPU，请运行以下命令安装
 
-python3 -m pip install paddlepaddle==2.0.0 -i https://mirror.baidu.com/pypi/simple
+python3 -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
 ```
 
 更多的版本需求，请参照[安装文档](https://www.paddlepaddle.org.cn/install/quick)中的说明进行操作。

PTDN/common_func.sh

+#!/bin/bash
+
+function func_parser_key(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[0]}
+    echo ${tmp}
+}
+
+function func_parser_value(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[1]}
+    echo ${tmp}
+}
+
+function func_set_params(){
+    key=$1
+    value=$2
+    if [ ${key}x = "null"x ];then
+        echo " "
+    elif [[ ${value} = "null" ]] || [[ ${value} = " " ]] || [ ${#value} -le 0 ];then
+        echo " "
+    else 
+        echo "${key}=${value}"
+    fi
+}
+
+function func_parser_params(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    key=${array[0]}
+    tmp=${array[1]}
+    IFS="|"
+    res=""
+    for _params in ${tmp[*]}; do
+        IFS="="
+        array=(${_params})
+        mode=${array[0]}
+        value=${array[1]}
+        if [[ ${mode} = ${MODE} ]]; then
+            IFS="|"
+            #echo $(func_set_params "${mode}" "${value}")
+            echo $value
+            break
+        fi
+        IFS="|"
+    done
+    echo ${res}
+}
+
+function status_check(){
+    last_status=$1   # the exit code
+    run_command=$2
+    run_log=$3
+    if [ $last_status -eq 0 ]; then
+        echo -e "\033[33m Run successfully with command - ${run_command}!  \033[0m" | tee -a ${run_log}
+    else
+        echo -e "\033[33m Run failed with command - ${run_command}!  \033[0m" | tee -a ${run_log}
+    fi
+}
+

PTDN/compare_results.py

+import numpy as np
+import os
+import subprocess
+import json
+import argparse
+import glob
+
+
+def init_args():
+    parser = argparse.ArgumentParser()
+    # params for testing assert allclose
+    parser.add_argument("--atol", type=float, default=1e-3)
+    parser.add_argument("--rtol", type=float, default=1e-3)
+    parser.add_argument("--gt_file", type=str, default="")
+    parser.add_argument("--log_file", type=str, default="")
+    parser.add_argument("--precision", type=str, default="fp32")
+    return parser
+
+
+def parse_args():
+    parser = init_args()
+    return parser.parse_args()
+
+
+def run_shell_command(cmd):
+    p = subprocess.Popen(
+        cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
+    out, err = p.communicate()
+
+    if p.returncode == 0:
+        return out.decode('utf-8')
+    else:
+        return None
+
+def parser_results_from_log_by_name(log_path, names_list):
+    if not os.path.exists(log_path):
+        raise ValueError("The log file {} does not exists!".format(log_path))
+
+    if names_list is None or len(names_list) < 1:
+        return []
+
+    parser_results = {}
+    for name in names_list:
+        cmd = "grep {} {}".format(name, log_path)
+        outs = run_shell_command(cmd)
+        outs = outs.split("\n")[0]
+        result = outs.split("{}".format(name))[-1]
+        try:
+            result = json.loads(result)
+        except:
+            result = np.array([int(r) for r in result.split()]).reshape(-1, 4)
+        parser_results[name] = result
+    return parser_results
+
+def load_gt_from_file(gt_file):
+    if not os.path.exists(gt_file):
+        raise ValueError("The log file {} does not exists!".format(gt_file))
+    with open(gt_file, 'r') as f:
+        data = f.readlines()
+        f.close()
+    parser_gt = {}
+    for line in data:
+        image_name, result = line.strip("\n").split("\t")
+        image_name = image_name.split('/')[-1]
+        try:
+            result = json.loads(result)
+        except:
+            result = np.array([int(r) for r in result.split()]).reshape(-1, 4)
+        parser_gt[image_name] = result
+    return parser_gt
+
+
+def load_gt_from_txts(gt_file):
+    gt_list = glob.glob(gt_file)
+    gt_collection = {}
+    for gt_f in gt_list:
+        gt_dict = load_gt_from_file(gt_f)
+        basename = os.path.basename(gt_f)
+        if "fp32" in basename:
+            gt_collection["fp32"] = [gt_dict, gt_f]
+        elif "fp16" in basename:
+            gt_collection["fp16"] = [gt_dict, gt_f]
+        elif "int8" in basename:
+            gt_collection["int8"] = [gt_dict, gt_f]
+        else:
+            continue
+    return gt_collection
+
+
+def collect_predict_from_logs(log_path, key_list):
+    log_list = glob.glob(log_path)
+    pred_collection = {}
+    for log_f in log_list:
+        pred_dict = parser_results_from_log_by_name(log_f, key_list)
+        key = os.path.basename(log_f)
+        pred_collection[key] = pred_dict
+
+    return pred_collection
+
+
+def testing_assert_allclose(dict_x, dict_y, atol=1e-7, rtol=1e-7):
+    for k in dict_x:
+        np.testing.assert_allclose(
+            np.array(dict_x[k]), np.array(dict_y[k]), atol=atol, rtol=rtol)
+
+
+if __name__ == "__main__":
+    # Usage:
+    # python3.7 tests/compare_results.py --gt_file=./tests/results/*.txt  --log_file=./tests/output/infer_*.log
+
+    args = parse_args()
+
+    gt_collection = load_gt_from_txts(args.gt_file)
+    key_list = gt_collection["fp32"][0].keys()
+
+    pred_collection = collect_predict_from_logs(args.log_file, key_list)
+    for filename in pred_collection.keys():
+        if "fp32" in filename:
+            gt_dict, gt_filename = gt_collection["fp32"]
+        elif "fp16" in filename:
+            gt_dict, gt_filename = gt_collection["fp16"]
+        elif "int8" in filename:
+            gt_dict, gt_filename = gt_collection["int8"]
+        else:
+            continue
+        pred_dict = pred_collection[filename]
+
+        try:
+            testing_assert_allclose(
+                gt_dict, pred_dict, atol=args.atol, rtol=args.rtol)
+            print(
+                "Assert allclose passed! The results of {} and {} are consistent!".
+                format(filename, gt_filename))
+        except Exception as E:
+            print(E)
+            raise ValueError(
+                "The results of {} and the results of {} are inconsistent!".
+                format(filename, gt_filename))

PTDN/configs/det_mv3_db.yml

+Global:
+  use_gpu: false
+  epoch_num: 5
+  log_smooth_window: 20
+  print_batch_step: 1
+  save_model_dir: ./output/db_mv3/
+  save_epoch_step: 1200
+  # evaluation is run every 2000 iterations
+  eval_batch_step: [0, 400]
+  cal_metric_during_train: False
+  pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained
+  checkpoints:
+  save_inference_dir:
+  use_visualdl: False
+  infer_img: doc/imgs_en/img_10.jpg
+  save_res_path: ./output/det_db/predicts_db.txt
+
+Architecture:
+  model_type: det
+  algorithm: DB
+  Transform:
+  Backbone:
+    name: MobileNetV3
+    scale: 0.5
+    model_name: large
+    disable_se: False
+  Neck:
+    name: DBFPN
+    out_channels: 256
+  Head:
+    name: DBHead
+    k: 50
+
+Loss:
+  name: DBLoss
+  balance_loss: true
+  main_loss_type: DiceLoss
+  alpha: 5 
+  beta: 10 
+  ohem_ratio: 3
+
+Optimizer:
+  name: Adam #Momentum
+  #momentum: 0.9
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    learning_rate: 0.001
+  regularizer:
+    name: 'L2'
+    factor: 0
+
+PostProcess:
+  name: DBPostProcess
+  thresh: 0.3
+  box_thresh: 0.6
+  max_candidates: 1000
+  unclip_ratio: 1.5
+
+Metric:
+  name: DetMetric
+  main_indicator: hmean
+
+Train:
+  dataset:
+    name: SimpleDataSet
+    data_dir: ./train_data/icdar2015/text_localization/
+    label_file_list:
+      - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt
+    ratio_list: [1.0]
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - DetLabelEncode: # Class handling label
+      - Resize:
+          size: [640, 640]
+      - MakeBorderMap:
+          shrink_ratio: 0.4
+          thresh_min: 0.3
+          thresh_max: 0.7
+      - MakeShrinkMap:
+          shrink_ratio: 0.4
+          min_text_size: 8
+      - NormalizeImage:
+          scale: 1./255.
+          mean: [0.485, 0.456, 0.406]
+          std: [0.229, 0.224, 0.225]
+          order: 'hwc'
+      - ToCHWImage:
+      - KeepKeys:
+          keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list
+  loader:
+    shuffle: False
+    drop_last: False
+    batch_size_per_card: 1
+    num_workers: 0
+    use_shared_memory: False
+
+Eval:
+  dataset:
+    name: SimpleDataSet
+    data_dir: ./train_data/icdar2015/text_localization/
+    label_file_list:
+      - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - DetLabelEncode: # Class handling label
+      - DetResizeForTest:
+          image_shape: [736, 1280]
+      - NormalizeImage:
+          scale: 1./255.
+          mean: [0.485, 0.456, 0.406]
+          std: [0.229, 0.224, 0.225]
+          order: 'hwc'
+      - ToCHWImage:
+      - KeepKeys:
+          keep_keys: ['image', 'shape', 'polys', 'ignore_tags']
+  loader:
+    shuffle: False
+    drop_last: False
+    batch_size_per_card: 1 # must be 1
+    num_workers: 0
+    use_shared_memory: False

PTDN/configs/det_r50_vd_db.yml

+Global:
+  use_gpu: false
+  epoch_num: 5
+  log_smooth_window: 20
+  print_batch_step: 1
+  save_model_dir: ./output/db_mv3/
+  save_epoch_step: 1200
+  # evaluation is run every 2000 iterations
+  eval_batch_step: [0, 400]
+  cal_metric_during_train: False
+  pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained
+  checkpoints:
+  save_inference_dir:
+  use_visualdl: False
+  infer_img: doc/imgs_en/img_10.jpg
+  save_res_path: ./output/det_db/predicts_db.txt
+
+Architecture:
+  model_type: det
+  algorithm: DB
+  Transform:
+  Backbone:
+    name: ResNet  #MobileNetV3
+    layers: 50
+  Neck:
+    name: DBFPN
+    out_channels: 256
+  Head:
+    name: DBHead
+    k: 50
+
+Loss:
+  name: DBLoss
+  balance_loss: true
+  main_loss_type: DiceLoss
+  alpha: 5 #5
+  beta: 10 #10
+  ohem_ratio: 3
+
+Optimizer:
+  name: Adam #Momentum
+  #momentum: 0.9
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    learning_rate: 0.001
+  regularizer:
+    name: 'L2'
+    factor: 0
+
+PostProcess:
+  name: DBPostProcess
+  thresh: 0.3
+  box_thresh: 0.6
+  max_candidates: 1000
+  unclip_ratio: 1.5
+
+Metric:
+  name: DetMetric
+  main_indicator: hmean
+
+Train:
+  dataset:
+    name: SimpleDataSet
+    data_dir: ./train_data/icdar2015/text_localization/
+    label_file_list:
+      - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt
+    ratio_list: [1.0]
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - DetLabelEncode: # Class handling label
+      - Resize:
+          # size: [640, 640]
+      - MakeBorderMap:
+          shrink_ratio: 0.4
+          thresh_min: 0.3
+          thresh_max: 0.7
+      - MakeShrinkMap:
+          shrink_ratio: 0.4
+          min_text_size: 8
+      - NormalizeImage:
+          scale: 1./255.
+          mean: [0.485, 0.456, 0.406]
+          std: [0.229, 0.224, 0.225]
+          order: 'hwc'
+      - ToCHWImage:
+      - KeepKeys:
+          keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list
+  loader:
+    shuffle: False
+    drop_last: False
+    batch_size_per_card: 1
+    num_workers: 0
+    use_shared_memory: False
+
+Eval:
+  dataset:
+    name: SimpleDataSet
+    data_dir: ./train_data/icdar2015/text_localization/
+    label_file_list:
+      - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - DetLabelEncode: # Class handling label
+      - DetResizeForTest:
+          image_shape: [736, 1280]
+      - NormalizeImage:
+          scale: 1./255.
+          mean: [0.485, 0.456, 0.406]
+          std: [0.229, 0.224, 0.225]
+          order: 'hwc'
+      - ToCHWImage:
+      - KeepKeys:
+          keep_keys: ['image', 'shape', 'polys', 'ignore_tags']
+  loader:
+    shuffle: False
+    drop_last: False
+    batch_size_per_card: 1 # must be 1
+    num_workers: 0
+    use_shared_memory: False

PTDN/configs/ppocr_det_mobile_params.txt

+===========================train_params===========================
+model_name:ocr_det
+python:python3.7
+gpu_list:0|0,1
+Global.use_gpu:True|True
+Global.auto_cast:null
+Global.epoch_num:lite_train_infer=1|whole_train_infer=300
+Global.save_model_dir:./output/
+Train.loader.batch_size_per_card:lite_train_infer=2|whole_train_infer=4
+Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
+null:null
+##
+trainer:norm_train|pact_train|fpgm_train
+norm_train:tools/train.py -c tests/configs/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
+pact_train:deploy/slim/quantization/quant.py -c tests/configs/det_mv3_db.yml -o
+fpgm_train:deploy/slim/prune/sensitivity_anal.py -c tests/configs/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:null
+null:null
+##
+===========================infer_params===========================
+Global.save_inference_dir:./output/
+Global.pretrained_model:
+norm_export:tools/export_model.py -c tests/configs/det_mv3_db.yml -o 
+quant_export:deploy/slim/quantization/export_model.py -c tests/configs/det_mv3_db.yml -o 
+fpgm_export:deploy/slim/prune/export_prune_model.py -c tests/configs/det_mv3_db.yml -o 
+distill_export:null
+export1:null
+export2:null
+##
+train_model:./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy
+infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
+infer_quant:False
+inference:tools/infer/predict_det.py
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16|int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+null:null
+===========================cpp_infer_params===========================
+use_opencv:True
+infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
+infer_quant:False
+inference:./deploy/cpp_infer/build/ppocr det
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+===========================serving_params===========================
+model_name:ocr_det
+python:python3.7
+trans_model:-m paddle_serving_client.convert
+--dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/
+--serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/
+serving_dir:./deploy/pdserving
+web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1
+op.det.local_service_conf.devices:null|0
+op.det.local_service_conf.use_mkldnn:True|False
+op.det.local_service_conf.thread_num:1|6
+op.det.local_service_conf.use_trt:False|True
+op.det.local_service_conf.precision:fp32|fp16|int8
+pipline:pipeline_http_client.py --image_dir=../../doc/imgs
+===========================kl_quant_params===========================
+infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
+infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
+infer_quant:True
+inference:tools/infer/predict_det.py
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+null:null
+null:null

PTDN/configs/ppocr_det_server_params.txt

+===========================train_params===========================
+model_name:ocr_server_det
+python:python3.7
+gpu_list:0|0,1
+Global.use_gpu:True|True
+Global.auto_cast:null
+Global.epoch_num:lite_train_infer=2|whole_train_infer=300
+Global.save_model_dir:./output/
+Train.loader.batch_size_per_card:lite_train_infer=2|whole_train_infer=4
+Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
+null:null
+##
+trainer:norm_train|pact_train|fpgm_export
+norm_train:tools/train.py -c tests/configs/det_r50_vd_db.yml -o 
+quant_export:deploy/slim/quantization/export_model.py -c tests/configs/det_r50_vd_db.yml -o 
+fpgm_export:deploy/slim/prune/export_prune_model.py -c tests/configs/det_r50_vd_db.yml -o 
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c tests/configs/det_r50_vd_db.yml -o
+null:null
+##
+===========================infer_params===========================
+Global.save_inference_dir:./output/
+Global.pretrained_model:
+norm_export:tools/export_model.py -c tests/configs/det_r50_vd_db.yml -o 
+quant_export:null 
+fpgm_export:null
+distill_export:null
+export1:null
+export2:null
+##
+train_model:./inference/ch_ppocr_server_v2.0_det_train/best_accuracy
+infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml -o
+infer_quant:False
+inference:tools/infer/predict_det.py
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16|int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+--save_log_path:null
+--benchmark:True
+null:null
+===========================cpp_infer_params===========================
+use_opencv:True
+infer_model:./inference/ch_ppocr_server_v2.0_det_infer/
+infer_quant:False
+inference:./deploy/cpp_infer/build/ppocr det
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+null:null
+--benchmark:True
+===========================serving_params===========================
+model_name:ocr_det_server
+python:python3.7
+trans_model:-m paddle_serving_client.convert
+--dirname:./inference/ch_ppocr_server_v2.0_det_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/
+--serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/
+serving_dir:./deploy/pdserving
+web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1
+op.det.local_service_conf.devices:null|0
+op.det.local_service_conf.use_mkldnn:True|False
+op.det.local_service_conf.thread_num:1|6
+op.det.local_service_conf.use_trt:False|True
+op.det.local_service_conf.precision:fp32|fp16|int8
+pipline:pipeline_http_client.py --image_dir=../../doc/imgs

tests/ocr_rec_params.txt → PTDN/configs/ppocr_rec_mobile_params.txt

 ===========================train_params===========================
 model_name:ocr_rec
 python:python3.7
-gpu_list:0|2,3
+gpu_list:0|0,1
 Global.use_gpu:True|True
 Global.auto_cast:null
 Global.epoch_num:lite_train_infer=2|whole_train_infer=300
@@ -9,7 +9,7 @@ Global.save_model_dir:./output/
 Train.loader.batch_size_per_card:lite_train_infer=128|whole_train_infer=128
 Global.pretrained_model:null
 train_model_name:latest
-train_infer_img_dir:./train_data/ic15_data/train
+train_infer_img_dir:./inference/rec_inference
 null:null
 ##
 trainer:norm_train|pact_train
@@ -41,7 +41,7 @@ inference:tools/infer/predict_rec.py
 --use_gpu:True|False
 --enable_mkldnn:True|False
 --cpu_threads:1|6
---rec_batch_num:1
+--rec_batch_num:1|6
 --use_tensorrt:True|False
 --precision:fp32|fp16|int8
 --rec_model_dir:
@@ -49,3 +49,35 @@ inference:tools/infer/predict_rec.py
 --save_log_path:./test/output/
 --benchmark:True
 null:null
+===========================cpp_infer_params===========================
+use_opencv:True
+infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/
+infer_quant:False
+inference:./deploy/cpp_infer/build/ppocr rec
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16
+--rec_model_dir:
+--image_dir:./inference/rec_inference/
+null:null
+--benchmark:True
+===========================serving_params===========================
+model_name:ocr_rec
+python:python3.7
+trans_model:-m paddle_serving_client.convert
+--dirname:./inference/ch_ppocr_mobile_v2.0_rec_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/pdserving/ppocr_rec_mobile_2.0_serving/
+--serving_client:./deploy/pdserving/ppocr_rec_mobile_2.0_client/
+serving_dir:./deploy/pdserving
+web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency=1
+op.rec.local_service_conf.devices:null|0
+op.rec.local_service_conf.use_mkldnn:True|False
+op.rec.local_service_conf.thread_num:1|6
+op.rec.local_service_conf.use_trt:False|True
+op.rec.local_service_conf.precision:fp32|fp16|int8
+pipline:pipeline_http_client.py --image_dir=../../doc/imgs_words_en

PTDN/configs/ppocr_rec_server_params.txt

+===========================train_params===========================
+model_name:ocr_server_rec
+python:python3.7
+gpu_list:0|0,1
+Global.use_gpu:True|True
+Global.auto_cast:null
+Global.epoch_num:lite_train_infer=2|whole_train_infer=300
+Global.save_model_dir:./output/
+Train.loader.batch_size_per_card:lite_train_infer=128|whole_train_infer=128
+Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./inference/rec_inference
+null:null
+##
+trainer:norm_train|pact_train
+norm_train:tools/train.py -c tests/configs/rec_icdar15_r34_train.yml -o
+pact_train:deploy/slim/quantization/quant.py -c tests/configs/rec_icdar15_r34_train.yml -o
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c tests/configs/rec_icdar15_r34_train.yml -o
+null:null
+##
+===========================infer_params===========================
+Global.save_inference_dir:./output/
+Global.pretrained_model:
+norm_export:tools/export_model.py -c tests/configs/rec_icdar15_r34_train.yml -o
+quant_export:deploy/slim/quantization/export_model.py -c tests/configs/rec_icdar15_r34_train.yml -o
+fpgm_export:null
+distill_export:null
+export1:null
+export2:null
+##
+infer_model:./inference/ch_ppocr_server_v2.0_rec_infer/
+infer_export:null
+infer_quant:False
+inference:tools/infer/predict_rec.py
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1|6
+--use_tensorrt:True|False
+--precision:fp32|fp16|int8
+--rec_model_dir:
+--image_dir:./inference/rec_inference
+--save_log_path:./test/output/
+--benchmark:True
+null:null
+===========================cpp_infer_params===========================
+use_opencv:True
+infer_model:./inference/ch_ppocr_server_v2.0_rec_infer/
+infer_quant:False
+inference:./deploy/cpp_infer/build/ppocr rec
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16
+--rec_model_dir:
+--image_dir:./inference/rec_inference/
+null:null
+--benchmark:True
+===========================serving_params===========================
+model_name:ocr_server_rec
+python:python3.7
+trans_model:-m paddle_serving_client.convert
+--dirname:./inference/ch_ppocr_server_v2.0_rec_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/pdserving/ppocr_rec_mobile_2.0_serving/
+--serving_client:./deploy/pdserving/ppocr_rec_mobile_2.0_client/
+serving_dir:./deploy/pdserving
+web_service:web_service_rec.py --config=config.yml --opt op.rec.concurrency=1
+op.rec.local_service_conf.devices:null|0
+op.rec.local_service_conf.use_mkldnn:True|False
+op.rec.local_service_conf.thread_num:1|6
+op.rec.local_service_conf.use_trt:False|True
+op.rec.local_service_conf.precision:fp32|fp16|int8
+pipline:pipeline_http_client.py --image_dir=../../doc/imgs_words_en

tests/ocr_det_params.txt → PTDN/configs/ppocr_sys_mobile_params.txt

 ===========================train_params===========================
-model_name:ocr_det
+model_name:ocr_system_mobile
 python:python3.7
-gpu_list:0|0,1
-Global.use_gpu:True|True
+gpu_list:null
+Global.use_gpu:null
 Global.auto_cast:null
-Global.epoch_num:lite_train_infer=2|whole_train_infer=300
+Global.epoch_num:null
 Global.save_model_dir:./output/
-Train.loader.batch_size_per_card:lite_train_infer=2|whole_train_infer=4
+Train.loader.batch_size_per_card:null
 Global.pretrained_model:null
-train_model_name:latest
-train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
+train_model_name:null
+train_infer_img_dir:null
 null:null
 ##
-trainer:norm_train|pact_train
-norm_train:tools/train.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
-pact_train:deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o
+trainer:
+norm_train:null
+pact_train:null
 fpgm_train:null
 distill_train:null
 null:null
 null:null
 ##
 ===========================eval_params=========================== 
-eval:tools/eval.py -c configs/det/det_mv3_db.yml -o
+eval:null
 null:null
 ##
 ===========================infer_params===========================
 Global.save_inference_dir:./output/
 Global.pretrained_model:
-norm_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o 
-quant_export:deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o 
-fpgm_export:deploy/slim/prune/export_prune_model.py
+norm_export:null 
+quant_export:null 
+fpgm_export:null 
 distill_export:null
 export1:null
 export2:null
@@ -37,8 +37,8 @@ export2:null
 infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
 infer_export:null
 infer_quant:False
-inference:tools/infer/predict_det.py
---use_gpu:True|False
+inference:tools/infer/predict_system.py
+--use_gpu:True
 --enable_mkldnn:True|False
 --cpu_threads:1|6
 --rec_batch_num:1
@@ -48,5 +48,20 @@ inference:tools/infer/predict_det.py
 --image_dir:./inference/ch_det_data_50/all-sum-510/
 --save_log_path:null
 --benchmark:True
-null:null
+--rec_model_dir:./inference/ch_ppocr_mobile_v2.0_rec_infer/
+===========================cpp_infer_params===========================
+use_opencv:True
+infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
+infer_quant:False
+inference:./deploy/cpp_infer/build/ppocr system
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+--rec_model_dir:./inference/ch_ppocr_mobile_v2.0_rec_infer/
+--benchmark:True
 

PTDN/configs/ppocr_sys_server_params.txt

+===========================train_params===========================
+model_name:ocr_system_server
+python:python3.7
+gpu_list:null
+Global.use_gpu:null
+Global.auto_cast:null
+Global.epoch_num:null
+Global.save_model_dir:./output/
+Train.loader.batch_size_per_card:null
+Global.pretrained_model:null
+train_model_name:null
+train_infer_img_dir:null
+null:null
+##
+trainer:
+norm_train:null
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:null
+null:null
+##
+===========================infer_params===========================
+Global.save_inference_dir:./output/
+Global.pretrained_model:
+norm_export:null
+quant_export:null
+fpgm_export:null
+distill_export:null
+export1:null
+export2:null
+##
+infer_model:./inference/ch_ppocr_server_v2.0_det_infer/
+infer_export:null
+infer_quant:False
+inference:tools/infer/predict_system.py
+--use_gpu:True
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16|int8
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+--save_log_path:null
+--benchmark:True
+--rec_model_dir:./inference/ch_ppocr_server_v2.0_rec_infer/
+===========================cpp_infer_params===========================
+use_opencv:True
+infer_model:./inference/ch_ppocr_server_v2.0_det_infer/
+infer_quant:False
+inference:./deploy/cpp_infer/build/ppocr system
+--use_gpu:True|False
+--enable_mkldnn:True|False
+--cpu_threads:1|6
+--rec_batch_num:1
+--use_tensorrt:False|True
+--precision:fp32|fp16
+--det_model_dir:
+--image_dir:./inference/ch_det_data_50/all-sum-510/
+--rec_model_dir:./inference/ch_ppocr_server_v2.0_rec_infer/
+--benchmark:True
\ No newline at end of file

PTDN/configs/rec_icdar15_r34_train.yml

+Global:
+  use_gpu: true
+  epoch_num: 72
+  log_smooth_window: 20
+  print_batch_step: 10
+  save_model_dir: ./output/rec/ic15/
+  save_epoch_step: 3
+  # evaluation is run every 2000 iterations
+  eval_batch_step: [0, 2000]
+  cal_metric_during_train: True
+  pretrained_model:
+  checkpoints:
+  save_inference_dir: ./
+  use_visualdl: False
+  infer_img: doc/imgs_words_en/word_10.png
+  # for data or label process
+  character_dict_path: ppocr/utils/en_dict.txt
+  character_type: EN
+  max_text_length: 25
+  infer_mode: False
+  use_space_char: False
+  save_res_path: ./output/rec/predicts_ic15.txt
+
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    learning_rate: 0.0005
+  regularizer:
+    name: 'L2'
+    factor: 0
+
+Architecture:
+  model_type: rec
+  algorithm: CRNN
+  Transform:
+  Backbone:
+    name: ResNet
+    layers: 34
+  Neck:
+    name: SequenceEncoder
+    encoder_type: rnn
+    hidden_size: 256
+  Head:
+    name: CTCHead
+    fc_decay: 0
+
+Loss:
+  name: CTCLoss
+
+PostProcess:
+  name: CTCLabelDecode
+
+Metric:
+  name: RecMetric
+  main_indicator: acc
+
+Train:
+  dataset:
+    name: SimpleDataSet
+    data_dir: ./train_data/ic15_data/
+    label_file_list: ["./train_data/ic15_data/rec_gt_train.txt"]
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - CTCLabelEncode: # Class handling label
+      - RecResizeImg:
+          image_shape: [3, 32, 100]
+      - KeepKeys:
+          keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
+  loader:
+    shuffle: True
+    batch_size_per_card: 256
+    drop_last: True
+    num_workers: 8
+    use_shared_memory: False
+
+Eval:
+  dataset:
+    name: SimpleDataSet
+    data_dir: ./train_data/ic15_data
+    label_file_list: ["./train_data/ic15_data/rec_gt_test.txt"]
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - CTCLabelEncode: # Class handling label
+      - RecResizeImg:
+          image_shape: [3, 32, 100]
+      - KeepKeys:
+          keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
+  loader:
+    shuffle: False
+    drop_last: False
+    batch_size_per_card: 256
+    num_workers: 4
+    use_shared_memory: False

PTDN/docs/install.md

+
+## 环境配置
+
+本教程适用于PTDN目录下基础功能测试的运行环境搭建。
+
+推荐环境：
+- CUDA 10.1
+- CUDNN 7.6
+- TensorRT 6.1.0.5 / 7.1
+
+
+推荐docker镜像安装，按照如下命令创建镜像，当前目录映射到镜像中的`/paddle`目录下
+```
+nvidia-docker run --name paddle -it -v $PWD:/paddle paddlepaddle/paddle:latest-dev-cuda10.1-cudnn7-gcc82 /bin/bash
+cd /paddle
+
+# 安装带TRT的paddle
+pip3.7 install https://paddle-wheel.bj.bcebos.com/with-trt/2.1.3/linux-gpu-cuda10.1-cudnn7-mkl-gcc8.2-trt6-avx/paddlepaddle_gpu-2.1.3.post101-cp37-cp37m-linux_x86_64.whl
+
+# 安装AutoLog
+git clone https://github.com/LDOUBLEV/AutoLog
+cd AutoLog
+pip3.7 install -r requirements.txt
+python3.7 setup.py bdist_wheel
+pip3.7 install ./dist/auto_log-1.0.0-py3-none-any.whl
+
+
+# 下载OCR代码
+cd ../
+git clone https://github.com/PaddlePaddle/PaddleOCR
+
+```
+
+安装PaddleOCR依赖：
+```
+cd PaddleOCR
+pip3.7 install -r requirements.txt
+```
+
+## FAQ :
+Q. You are using Paddle compiled with TensorRT, but TensorRT dynamic library is not found. Ignore this if TensorRT is not needed.
+
+A. 问题一般是当前安装paddle版本带TRT，但是本地环境找不到TensorRT的预测库，需要下载TensorRT库，解压后设置环境变量LD_LIBRARY_PATH;
+如：
+```
+export LD_LIBRARY_PATH=/usr/local/python3.7.0/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/paddle/package/TensorRT-6.0.1.5/lib
+```
+或者问题是下载的TensorRT版本和当前paddle中编译的TRT版本不匹配，需要下载版本相符的TRT。