Skip to content

P
PaddleOCR

jobily / PaddleOCR
与 Fork 源项目一致

Fork自 PaddlePaddle / PaddleOCR

通知 1
Star 0
Fork 0
P
PaddleOCR

体验新版 GitCode，发现更多精彩内容 >>

提交 f896d5af 编写于 作者: W WenmuZhou
浏览文件
操作

merge upstream

上级 359d81e5 3ec57e8d
显示空白变更内容
内联 并排
Showing with 235 addition and 97 deletion
deploy/cpp_infer/include/utility.h
浏览文件 @ f896d5af
...@@ -44,6 +44,9 @@ public: ...@@ -44,6 +44,9 @@ public:
inline static size_t argmax(ForwardIterator first, ForwardIterator last) { inline static size_t argmax(ForwardIterator first, ForwardIterator last) {
return std::distance(first, std::max_element(first, last)); return std::distance(first, std::max_element(first, last));
} }
static void GetAllFiles(const char *dir_name,
std::vector<std::string> &all_inputs);
}; };
} // namespace PaddleOCR } // namespace PaddleOCR
\ No newline at end of file
deploy/cpp_infer/src/main.cpp
浏览文件 @ f896d5af
...@@ -27,9 +27,12 @@ ...@@ -27,9 +27,12 @@
#include <fstream> #include <fstream>
#include <numeric> #include <numeric>
#include <glog/logging.h>
#include <include/config.h> #include <include/config.h>
#include <include/ocr_det.h> #include <include/ocr_det.h>
#include <include/ocr_rec.h> #include <include/ocr_rec.h>
#include <include/utility.h>
#include <sys/stat.h>
using namespace std; using namespace std;
using namespace cv; using namespace cv;
...@@ -47,13 +50,8 @@ int main(int argc, char **argv) { ...@@ -47,13 +50,8 @@ int main(int argc, char **argv) {
config.PrintConfigInfo(); config.PrintConfigInfo();
std::string img_path(argv[2]); std::string img_path(argv[2]);
std::vector<std::string> all_img_names;
cv::Mat srcimg = cv::imread(img_path, cv::IMREAD_COLOR); Utility::GetAllFiles((char *)img_path.c_str(), all_img_names);
if (!srcimg.data) {
std::cerr << "[ERROR] image read failed! image path: " << img_path << "\n";
exit(1);
}
DBDetector det(config.det_model_dir, config.use_gpu, config.gpu_id, DBDetector det(config.det_model_dir, config.use_gpu, config.gpu_id,
config.gpu_mem, config.cpu_math_library_num_threads, config.gpu_mem, config.cpu_math_library_num_threads,
...@@ -76,7 +74,18 @@ int main(int argc, char **argv) { ...@@ -76,7 +74,18 @@ int main(int argc, char **argv) {
config.use_tensorrt, config.use_fp16); config.use_tensorrt, config.use_fp16);
auto start = std::chrono::system_clock::now(); auto start = std::chrono::system_clock::now();
for (auto img_dir : all_img_names) {
LOG(INFO) << "The predict img: " << img_dir;
cv::Mat srcimg = cv::imread(img_dir, cv::IMREAD_COLOR);
if (!srcimg.data) {
std::cerr << "[ERROR] image read failed! image path: " << img_path
<< "\n";
exit(1);
}
std::vector<std::vector<std::vector<int>>> boxes; std::vector<std::vector<std::vector<int>>> boxes;
det.Run(srcimg, boxes); det.Run(srcimg, boxes);
rec.Run(boxes, srcimg, cls); rec.Run(boxes, srcimg, cls);
...@@ -88,6 +97,7 @@ int main(int argc, char **argv) { ...@@ -88,6 +97,7 @@ int main(int argc, char **argv) {
std::chrono::microseconds::period::num / std::chrono::microseconds::period::num /
std::chrono::microseconds::period::den std::chrono::microseconds::period::den
<< "s" << std::endl; << "s" << std::endl;
}
return 0; return 0;
} }
deploy/cpp_infer/src/ocr_det.cpp
浏览文件 @ f896d5af
...@@ -30,6 +30,42 @@ void DBDetector::LoadModel(const std::string &model_dir) { ...@@ -30,6 +30,42 @@ void DBDetector::LoadModel(const std::string &model_dir) {
this->use_fp16_ ? paddle_infer::Config::Precision::kHalf this->use_fp16_ ? paddle_infer::Config::Precision::kHalf
: paddle_infer::Config::Precision::kFloat32, : paddle_infer::Config::Precision::kFloat32,
false, false); false, false);
std::map<std::string, std::vector<int>> min_input_shape = {
{"x", {1, 3, 50, 50}},
{"conv2d_92.tmp_0", {1, 96, 20, 20}},
{"conv2d_91.tmp_0", {1, 96, 10, 10}},
{"nearest_interp_v2_1.tmp_0", {1, 96, 10, 10}},
{"nearest_interp_v2_2.tmp_0", {1, 96, 20, 20}},
{"nearest_interp_v2_3.tmp_0", {1, 24, 20, 20}},
{"nearest_interp_v2_4.tmp_0", {1, 24, 20, 20}},
{"nearest_interp_v2_5.tmp_0", {1, 24, 20, 20}},
{"elementwise_add_7", {1, 56, 2, 2}},
{"nearest_interp_v2_0.tmp_0", {1, 96, 2, 2}}};
std::map<std::string, std::vector<int>> max_input_shape = {
{"x", {1, 3, this->max_side_len_, this->max_side_len_}},
{"conv2d_92.tmp_0", {1, 96, 400, 400}},
{"conv2d_91.tmp_0", {1, 96, 200, 200}},
{"nearest_interp_v2_1.tmp_0", {1, 96, 200, 200}},
{"nearest_interp_v2_2.tmp_0", {1, 96, 400, 400}},
{"nearest_interp_v2_3.tmp_0", {1, 24, 400, 400}},
{"nearest_interp_v2_4.tmp_0", {1, 24, 400, 400}},
{"nearest_interp_v2_5.tmp_0", {1, 24, 400, 400}},
{"elementwise_add_7", {1, 56, 400, 400}},
{"nearest_interp_v2_0.tmp_0", {1, 96, 400, 400}}};
std::map<std::string, std::vector<int>> opt_input_shape = {
{"x", {1, 3, 640, 640}},
{"conv2d_92.tmp_0", {1, 96, 160, 160}},
{"conv2d_91.tmp_0", {1, 96, 80, 80}},
{"nearest_interp_v2_1.tmp_0", {1, 96, 80, 80}},
{"nearest_interp_v2_2.tmp_0", {1, 96, 160, 160}},
{"nearest_interp_v2_3.tmp_0", {1, 24, 160, 160}},
{"nearest_interp_v2_4.tmp_0", {1, 24, 160, 160}},
{"nearest_interp_v2_5.tmp_0", {1, 24, 160, 160}},
{"elementwise_add_7", {1, 56, 40, 40}},
{"nearest_interp_v2_0.tmp_0", {1, 96, 40, 40}}};
config.SetTRTDynamicShapeInfo(min_input_shape, max_input_shape,
opt_input_shape);
} }
} else { } else {
config.DisableGpu(); config.DisableGpu();
...@@ -48,7 +84,7 @@ void DBDetector::LoadModel(const std::string &model_dir) { ...@@ -48,7 +84,7 @@ void DBDetector::LoadModel(const std::string &model_dir) {
config.SwitchIrOptim(true); config.SwitchIrOptim(true);
config.EnableMemoryOptim(); config.EnableMemoryOptim();
config.DisableGlogInfo(); // config.DisableGlogInfo();
this->predictor_ = CreatePredictor(config); this->predictor_ = CreatePredictor(config);
} }
......
deploy/cpp_infer/src/ocr_rec.cpp
浏览文件 @ f896d5af
...@@ -25,8 +25,9 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes, ...@@ -25,8 +25,9 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
std::cout << "The predicted text is :" << std::endl; std::cout << "The predicted text is :" << std::endl;
int index = 0; int index = 0;
for (int i = boxes.size() - 1; i >= 0; i--) { for (int i = 0; i < boxes.size(); i++) {
crop_img = GetRotateCropImage(srcimg, boxes[i]); crop_img = GetRotateCropImage(srcimg, boxes[i]);
if (cls != nullptr) { if (cls != nullptr) {
crop_img = cls->Run(crop_img); crop_img = cls->Run(crop_img);
} }
...@@ -105,6 +106,15 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) { ...@@ -105,6 +106,15 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
this->use_fp16_ ? paddle_infer::Config::Precision::kHalf this->use_fp16_ ? paddle_infer::Config::Precision::kHalf
: paddle_infer::Config::Precision::kFloat32, : paddle_infer::Config::Precision::kFloat32,
false, false); false, false);
std::map<std::string, std::vector<int>> min_input_shape = {
{"x", {1, 3, 32, 10}}};
std::map<std::string, std::vector<int>> max_input_shape = {
{"x", {1, 3, 32, 2000}}};
std::map<std::string, std::vector<int>> opt_input_shape = {
{"x", {1, 3, 32, 320}}};
config.SetTRTDynamicShapeInfo(min_input_shape, max_input_shape,
opt_input_shape);
} }
} else { } else {
config.DisableGpu(); config.DisableGpu();
......
deploy/cpp_infer/src/preprocess_op.cpp 100755 → 100644
浏览文件 @ f896d5af
...@@ -81,15 +81,9 @@ void ResizeImgType0::Run(const cv::Mat &img, cv::Mat &resize_img, ...@@ -81,15 +81,9 @@ void ResizeImgType0::Run(const cv::Mat &img, cv::Mat &resize_img,
resize_h = max(int(round(float(resize_h) / 32) * 32), 32); resize_h = max(int(round(float(resize_h) / 32) * 32), 32);
resize_w = max(int(round(float(resize_w) / 32) * 32), 32); resize_w = max(int(round(float(resize_w) / 32) * 32), 32);
if (!use_tensorrt) {
cv::resize(img, resize_img, cv::Size(resize_w, resize_h)); cv::resize(img, resize_img, cv::Size(resize_w, resize_h));
ratio_h = float(resize_h) / float(h); ratio_h = float(resize_h) / float(h);
ratio_w = float(resize_w) / float(w); ratio_w = float(resize_w) / float(w);
} else {
cv::resize(img, resize_img, cv::Size(640, 640));
ratio_h = float(640) / float(h);
ratio_w = float(640) / float(w);
}
} }
void CrnnResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img, float wh_ratio, void CrnnResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img, float wh_ratio,
...@@ -108,23 +102,12 @@ void CrnnResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img, float wh_ratio, ...@@ -108,23 +102,12 @@ void CrnnResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img, float wh_ratio,
resize_w = imgW; resize_w = imgW;
else else
resize_w = int(ceilf(imgH * ratio)); resize_w = int(ceilf(imgH * ratio));
if (!use_tensorrt) {
cv::resize(img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f, cv::resize(img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f,
cv::INTER_LINEAR); cv::INTER_LINEAR);
cv::copyMakeBorder(resize_img, resize_img, 0, 0, 0, cv::copyMakeBorder(resize_img, resize_img, 0, 0, 0,
int(imgW - resize_img.cols), cv::BORDER_CONSTANT, int(imgW - resize_img.cols), cv::BORDER_CONSTANT,
{127, 127, 127}); {127, 127, 127});
} else {
int k = int(img.cols * 32 / img.rows);
if (k >= 100) {
cv::resize(img, resize_img, cv::Size(100, 32), 0.f, 0.f,
cv::INTER_LINEAR);
} else {
cv::resize(img, resize_img, cv::Size(k, 32), 0.f, 0.f, cv::INTER_LINEAR);
cv::copyMakeBorder(resize_img, resize_img, 0, 0, 0, int(100 - k),
cv::BORDER_CONSTANT, {127, 127, 127});
}
}
} }
void ClsResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img, void ClsResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img,
...@@ -142,16 +125,12 @@ void ClsResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img, ...@@ -142,16 +125,12 @@ void ClsResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img,
else else
resize_w = int(ceilf(imgH * ratio)); resize_w = int(ceilf(imgH * ratio));
if (!use_tensorrt) {
cv::resize(img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f, cv::resize(img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f,
cv::INTER_LINEAR); cv::INTER_LINEAR);
if (resize_w < imgW) { if (resize_w < imgW) {
cv::copyMakeBorder(resize_img, resize_img, 0, 0, 0, imgW - resize_w, cv::copyMakeBorder(resize_img, resize_img, 0, 0, 0, imgW - resize_w,
cv::BORDER_CONSTANT, cv::Scalar(0, 0, 0)); cv::BORDER_CONSTANT, cv::Scalar(0, 0, 0));
} }
} else {
cv::resize(img, resize_img, cv::Size(100, 32), 0.f, 0.f, cv::INTER_LINEAR);
}
} }
} // namespace PaddleOCR } // namespace PaddleOCR
deploy/cpp_infer/src/utility.cpp
浏览文件 @ f896d5af
...@@ -12,12 +12,14 @@ ...@@ -12,12 +12,14 @@
// See the License for the specific language governing permissions and // See the License for the specific language governing permissions and
// limitations under the License. // limitations under the License.
#include <dirent.h>
#include <include/utility.h>
#include <iostream> #include <iostream>
#include <ostream> #include <ostream>
#include <sys/stat.h>
#include <sys/types.h>
#include <vector> #include <vector>
#include <include/utility.h>
namespace PaddleOCR { namespace PaddleOCR {
std::vector<std::string> Utility::ReadDict(const std::string &path) { std::vector<std::string> Utility::ReadDict(const std::string &path) {
...@@ -57,4 +59,37 @@ void Utility::VisualizeBboxes( ...@@ -57,4 +59,37 @@ void Utility::VisualizeBboxes(
<< std::endl; << std::endl;
} }
// list all files under a directory
void Utility::GetAllFiles(const char *dir_name,
std::vector<std::string> &all_inputs) {
if (NULL == dir_name) {
std::cout << " dir_name is null ! " << std::endl;
return;
}
struct stat s;
lstat(dir_name, &s);
if (!S_ISDIR(s.st_mode)) {
std::cout << "dir_name is not a valid directory !" << std::endl;
all_inputs.push_back(dir_name);
return;
} else {
struct dirent *filename; // return value for readdir()
DIR *dir; // return value for opendir()
dir = opendir(dir_name);
if (NULL == dir) {
std::cout << "Can not open dir " << dir_name << std::endl;
return;
}
std::cout << "Successfully opened the dir !" << std::endl;
while ((filename = readdir(dir)) != NULL) {
if (strcmp(filename->d_name, ".") == 0 ||
strcmp(filename->d_name, "..") == 0)
continue;
// img_dir + std::string("/") + all_inputs[0];
all_inputs.push_back(dir_name + std::string("/") +
std::string(filename->d_name));
}
}
}
} // namespace PaddleOCR } // namespace PaddleOCR
\ No newline at end of file
deploy/cpp_infer/tools/build.sh
浏览文件 @ f896d5af
...@@ -12,9 +12,10 @@ cmake .. \ ...@@ -12,9 +12,10 @@ cmake .. \
-DWITH_MKL=ON \ -DWITH_MKL=ON \
-DWITH_GPU=OFF \ -DWITH_GPU=OFF \
-DWITH_STATIC_LIB=OFF \ -DWITH_STATIC_LIB=OFF \
-DUSE_TENSORRT=OFF \ -DWITH_TENSORRT=OFF \
-DOPENCV_DIR=${OPENCV_DIR} \ -DOPENCV_DIR=${OPENCV_DIR} \
-DCUDNN_LIB=${CUDNN_LIB_DIR} \ -DCUDNN_LIB=${CUDNN_LIB_DIR} \
-DCUDA_LIB=${CUDA_LIB_DIR} \ -DCUDA_LIB=${CUDA_LIB_DIR} \
-DTENSORRT_DIR=${TENSORRT_DIR} \
make -j make -j
deploy/cpp_infer/tools/config.txt
浏览文件 @ f896d5af
...@@ -23,7 +23,7 @@ rec_model_dir ./inference/ch_ppocr_mobile_v2.0_rec_infer/ ...@@ -23,7 +23,7 @@ rec_model_dir ./inference/ch_ppocr_mobile_v2.0_rec_infer/
char_list_file ../../ppocr/utils/ppocr_keys_v1.txt char_list_file ../../ppocr/utils/ppocr_keys_v1.txt
# show the detection results # show the detection results
visualize 1 visualize 0
# use_tensorrt # use_tensorrt
use_tensorrt 0 use_tensorrt 0
......
deploy/lite/readme_en.md
浏览文件 @ f896d5af
...@@ -6,7 +6,7 @@ paddle-lite is a lightweight inference engine for PaddlePaddle. It provides effi ...@@ -6,7 +6,7 @@ paddle-lite is a lightweight inference engine for PaddlePaddle. It provides effi
## 1. Preparation ## 1. Preparation
### 运行准备 ### Preparation environment
- Computer (for Compiling Paddle Lite) - Computer (for Compiling Paddle Lite)
- Mobile phone (arm7 or arm8) - Mobile phone (arm7 or arm8)
...@@ -87,8 +87,8 @@ The following table also provides a series of models that can be deployed on mob ...@@ -87,8 +87,8 @@ The following table also provides a series of models that can be deployed on mob
|Version|Introduction|Model size|Detection model|Text Direction model|Recognition model|Paddle-Lite branch| |Version|Introduction|Model size|Detection model|Text Direction model|Recognition model|Paddle-Lite branch|
|---|---|---|---|---|---|---| |---|---|---|---|---|---|---|
|V2.0|extra-lightweight chinese OCR optimized model|7.8M|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_det_opt.nb)|[download lin](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_cls_opt.nb)|[download lin](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_rec_opt.nb)|v2.9| |V2.0|extra-lightweight chinese OCR optimized model|7.8M|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_det_opt.nb)|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_cls_opt.nb)|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_rec_opt.nb)|v2.9|
|V2.0(slim)|extra-lightweight chinese OCR optimized model|3.3M|[下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_det_slim_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_cls_slim_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_rec_slim_opt.nb)|v2.9| |V2.0(slim)|extra-lightweight chinese OCR optimized model|3.3M|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_det_slim_opt.nb)|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_cls_slim_opt.nb)|[download link](https://paddleocr.bj.bcebos.com/dygraph_v2.0/lite/ch_ppocr_mobile_v2.0_rec_slim_opt.nb)|v2.9|
If you directly use the model in the above table for deployment, you can skip the following steps and directly read [Section 2.2](#2.2 Run optimized model on Phone). If you directly use the model in the above table for deployment, you can skip the following steps and directly read [Section 2.2](#2.2 Run optimized model on Phone).
......
doc/doc_en/models_list_en.md
浏览文件 @ f896d5af
...@@ -103,14 +103,14 @@ python3 generate_multi_language_configs.py -l it \ ...@@ -103,14 +103,14 @@ python3 generate_multi_language_configs.py -l it \
| german_mobile_v2.0_rec | ppocr/utils/dict/german_dict.txt | Lightweight model for German recognition|[rec_german_lite_train.yml](../../configs/rec/multi_language/rec_german_lite_train.yml)|2.65M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_train.tar) | | german_mobile_v2.0_rec | ppocr/utils/dict/german_dict.txt | Lightweight model for German recognition|[rec_german_lite_train.yml](../../configs/rec/multi_language/rec_german_lite_train.yml)|2.65M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_train.tar) |
| korean_mobile_v2.0_rec | ppocr/utils/dict/korean_dict.txt | Lightweight model for Korean recognition|[rec_korean_lite_train.yml](../../configs/rec/multi_language/rec_korean_lite_train.yml)|3.9M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_train.tar) | | korean_mobile_v2.0_rec | ppocr/utils/dict/korean_dict.txt | Lightweight model for Korean recognition|[rec_korean_lite_train.yml](../../configs/rec/multi_language/rec_korean_lite_train.yml)|3.9M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_train.tar) |
| japan_mobile_v2.0_rec | ppocr/utils/dict/japan_dict.txt | Lightweight model for Japanese recognition|[rec_japan_lite_train.yml](../../configs/rec/multi_language/rec_japan_lite_train.yml)|4.23M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_train.tar) | | japan_mobile_v2.0_rec | ppocr/utils/dict/japan_dict.txt | Lightweight model for Japanese recognition|[rec_japan_lite_train.yml](../../configs/rec/multi_language/rec_japan_lite_train.yml)|4.23M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_train.tar) |
| chinese_cht_mobile_v2.0_rec | ppocr/utils/dict/chinese_cht_dict.txt | Lightweight model for chinese cht recognition|rec_chinese_cht_lite_train.yml|5.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_train.tar) | | chinese_cht_mobile_v2.0_rec | ppocr/utils/dict/chinese_cht_dict.txt | Lightweight model for chinese cht recognition|rec_chinese_cht_lite_train.yml|5.63M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_train.tar) |
| te_mobile_v2.0_rec | ppocr/utils/dict/te_dict.txt | Lightweight model for Telugu recognition|rec_te_lite_train.yml|2.63M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_train.tar) | | te_mobile_v2.0_rec | ppocr/utils/dict/te_dict.txt | Lightweight model for Telugu recognition|rec_te_lite_train.yml|2.63M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_train.tar) |
| ka_mobile_v2.0_rec | ppocr/utils/dict/ka_dict.txt | Lightweight model for Kannada recognition|rec_ka_lite_train.yml|2.63M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_train.tar) | | ka_mobile_v2.0_rec | ppocr/utils/dict/ka_dict.txt | Lightweight model for Kannada recognition|rec_ka_lite_train.yml|2.63M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_train.tar) |
| ta_mobile_v2.0_rec | ppocr/utils/dict/ta_dict.txt | Lightweight model for Tamil recognition|rec_ta_lite_train.yml|2.63M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_train.tar) | | ta_mobile_v2.0_rec | ppocr/utils/dict/ta_dict.txt | Lightweight model for Tamil recognition|rec_ta_lite_train.yml|2.63M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_train.tar) |
| latin_mobile_v2.0_rec | ppocr/utils/dict/latin_dict.txt | Lightweight model for latin recognition | [rec_latin_lite_train.yml](../../configs/rec/multi_language/rec_latin_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_train.tar) | | latin_mobile_v2.0_rec | ppocr/utils/dict/latin_dict.txt | Lightweight model for latin recognition | [rec_latin_lite_train.yml](../../configs/rec/multi_language/rec_latin_lite_train.yml) |2.6M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_train.tar) |
| arabic_mobile_v2.0_rec | ppocr/utils/dict/arabic_dict.txt | Lightweight model for arabic recognition | [rec_arabic_lite_train.yml](../../configs/rec/multi_language/rec_arabic_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_train.tar) | | arabic_mobile_v2.0_rec | ppocr/utils/dict/arabic_dict.txt | Lightweight model for arabic recognition | [rec_arabic_lite_train.yml](../../configs/rec/multi_language/rec_arabic_lite_train.yml) |2.6M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_train.tar) |
| cyrillic_mobile_v2.0_rec | ppocr/utils/dict/cyrillic_dict.txt | Lightweight model for cyrillic recognition | [rec_cyrillic_lite_train.yml](../../configs/rec/multi_language/rec_cyrillic_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_train.tar) | | cyrillic_mobile_v2.0_rec | ppocr/utils/dict/cyrillic_dict.txt | Lightweight model for cyrillic recognition | [rec_cyrillic_lite_train.yml](../../configs/rec/multi_language/rec_cyrillic_lite_train.yml) |2.6M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_train.tar) |
| devanagari_mobile_v2.0_rec | ppocr/utils/dict/devanagari_dict.txt | Lightweight model for devanagari recognition | [rec_devanagari_lite_train.yml](../../configs/rec/multi_language/rec_devanagari_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_train.tar) | | devanagari_mobile_v2.0_rec | ppocr/utils/dict/devanagari_dict.txt | Lightweight model for devanagari recognition | [rec_devanagari_lite_train.yml](../../configs/rec/multi_language/rec_devanagari_lite_train.yml) |2.6M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_train.tar) |
For more supported languages, please refer to : [Multi-language model](./multi_languages_en.md) For more supported languages, please refer to : [Multi-language model](./multi_languages_en.md)
......
doc/joinus.PNG
查看替换文件 @ 359d81e5 浏览文件 @ f896d5af
doc/joinus.PNG

102.2 KB | W: | H:

doc/joinus.PNG

99.7 KB | W: | H:

doc/joinus.PNG
doc/joinus.PNG
doc/joinus.PNG
doc/joinus.PNG
  • 2-up
  • Swipe
  • Onion skin
tools/infer/utility.py
浏览文件 @ f896d5af
...@@ -21,6 +21,9 @@ import json ...@@ -21,6 +21,9 @@ import json
from PIL import Image, ImageDraw, ImageFont from PIL import Image, ImageDraw, ImageFont
import math import math
from paddle import inference from paddle import inference
import time
from ppocr.utils.logging import get_logger
logger = get_logger()
def str2bool(v): def str2bool(v):
...@@ -40,6 +43,7 @@ inference_args_list = [ ...@@ -40,6 +43,7 @@ inference_args_list = [
['total_process_num', int, 1], ['total_process_num', int, 1],
['process_id', int, 0], ['process_id', int, 0],
['gpu_mem', int, 500], ['gpu_mem', int, 500],
['cpu_threads', int, 10],
# params for text detector # params for text detector
['image_dir', str, None], ['image_dir', str, None],
['det_algorithm', str, 'DB'], ['det_algorithm', str, 'DB'],
...@@ -128,19 +132,97 @@ def create_predictor(args, mode, logger): ...@@ -128,19 +132,97 @@ def create_predictor(args, mode, logger):
config.enable_use_gpu(args.gpu_mem, 0) config.enable_use_gpu(args.gpu_mem, 0)
if args.use_tensorrt: if args.use_tensorrt:
config.enable_tensorrt_engine( config.enable_tensorrt_engine(
precision_mode=inference.PrecisionType.Half precision_mode=inference.PrecisionType.Float32,
if args.use_fp16 else inference.PrecisionType.Float32, max_batch_size=args.max_batch_size,
max_batch_size=args.max_batch_size) min_subgraph_size=3) # skip the minmum trt subgraph
if mode == "det" and "mobile" in model_file_path:
min_input_shape = {
"x": [1, 3, 50, 50],
"conv2d_92.tmp_0": [1, 96, 20, 20],
"conv2d_91.tmp_0": [1, 96, 10, 10],
"nearest_interp_v2_1.tmp_0": [1, 96, 10, 10],
"nearest_interp_v2_2.tmp_0": [1, 96, 20, 20],
"nearest_interp_v2_3.tmp_0": [1, 24, 20, 20],
"nearest_interp_v2_4.tmp_0": [1, 24, 20, 20],
"nearest_interp_v2_5.tmp_0": [1, 24, 20, 20],
"elementwise_add_7": [1, 56, 2, 2],
"nearest_interp_v2_0.tmp_0": [1, 96, 2, 2]
}
max_input_shape = {
"x": [1, 3, 2000, 2000],
"conv2d_92.tmp_0": [1, 96, 400, 400],
"conv2d_91.tmp_0": [1, 96, 200, 200],
"nearest_interp_v2_1.tmp_0": [1, 96, 200, 200],
"nearest_interp_v2_2.tmp_0": [1, 96, 400, 400],
"nearest_interp_v2_3.tmp_0": [1, 24, 400, 400],
"nearest_interp_v2_4.tmp_0": [1, 24, 400, 400],
"nearest_interp_v2_5.tmp_0": [1, 24, 400, 400],
"elementwise_add_7": [1, 56, 400, 400],
"nearest_interp_v2_0.tmp_0": [1, 96, 400, 400]
}
opt_input_shape = {
"x": [1, 3, 640, 640],
"conv2d_92.tmp_0": [1, 96, 160, 160],
"conv2d_91.tmp_0": [1, 96, 80, 80],
"nearest_interp_v2_1.tmp_0": [1, 96, 80, 80],
"nearest_interp_v2_2.tmp_0": [1, 96, 160, 160],
"nearest_interp_v2_3.tmp_0": [1, 24, 160, 160],
"nearest_interp_v2_4.tmp_0": [1, 24, 160, 160],
"nearest_interp_v2_5.tmp_0": [1, 24, 160, 160],
"elementwise_add_7": [1, 56, 40, 40],
"nearest_interp_v2_0.tmp_0": [1, 96, 40, 40]
}
if mode == "det" and "server" in model_file_path:
min_input_shape = {
"x": [1, 3, 50, 50],
"conv2d_59.tmp_0": [1, 96, 20, 20],
"nearest_interp_v2_2.tmp_0": [1, 96, 20, 20],
"nearest_interp_v2_3.tmp_0": [1, 24, 20, 20],
"nearest_interp_v2_4.tmp_0": [1, 24, 20, 20],
"nearest_interp_v2_5.tmp_0": [1, 24, 20, 20]
}
max_input_shape = {
"x": [1, 3, 2000, 2000],
"conv2d_59.tmp_0": [1, 96, 400, 400],
"nearest_interp_v2_2.tmp_0": [1, 96, 400, 400],
"nearest_interp_v2_3.tmp_0": [1, 24, 400, 400],
"nearest_interp_v2_4.tmp_0": [1, 24, 400, 400],
"nearest_interp_v2_5.tmp_0": [1, 24, 400, 400]
}
opt_input_shape = {
"x": [1, 3, 640, 640],
"conv2d_59.tmp_0": [1, 96, 160, 160],
"nearest_interp_v2_2.tmp_0": [1, 96, 160, 160],
"nearest_interp_v2_3.tmp_0": [1, 24, 160, 160],
"nearest_interp_v2_4.tmp_0": [1, 24, 160, 160],
"nearest_interp_v2_5.tmp_0": [1, 24, 160, 160]
}
elif mode == "rec":
min_input_shape = {"x": [args.rec_batch_num, 3, 32, 10]}
max_input_shape = {"x": [args.rec_batch_num, 3, 32, 2000]}
opt_input_shape = {"x": [args.rec_batch_num, 3, 32, 320]}
elif mode == "cls":
min_input_shape = {"x": [args.rec_batch_num, 3, 48, 10]}
max_input_shape = {"x": [args.rec_batch_num, 3, 48, 2000]}
opt_input_shape = {"x": [args.rec_batch_num, 3, 48, 320]}
else:
min_input_shape = {"x": [1, 3, 10, 10]}
max_input_shape = {"x": [1, 3, 1000, 1000]}
opt_input_shape = {"x": [1, 3, 500, 500]}
config.set_trt_dynamic_shape_info(min_input_shape, max_input_shape,
opt_input_shape)
else: else:
config.disable_gpu() config.disable_gpu()
config.set_cpu_math_library_num_threads(6) if hasattr(args, "cpu_threads"):
config.set_cpu_math_library_num_threads(args.cpu_threads)
else:
config.set_cpu_math_library_num_threads(
10) # default cpu threads as 10
if args.enable_mkldnn: if args.enable_mkldnn:
# cache 10 different shapes for mkldnn to avoid memory leak # cache 10 different shapes for mkldnn to avoid memory leak
config.set_mkldnn_cache_capacity(10) config.set_mkldnn_cache_capacity(10)
config.enable_mkldnn() config.enable_mkldnn()
# TODO LDOUBLEV: fix mkldnn bug when bach_size > 1
# config.set_mkldnn_op({'conv2d', 'depthwise_conv2d', 'pool2d', 'batch_norm'})
args.rec_batch_num = 1
# enable memory optim # enable memory optim
config.enable_memory_optim() config.enable_memory_optim()
...@@ -203,7 +285,7 @@ def draw_ocr(image, ...@@ -203,7 +285,7 @@ def draw_ocr(image,
txts=None, txts=None,
scores=None, scores=None,
drop_score=0.5, drop_score=0.5,
font_path="./doc/simfang.ttf"): font_path="./doc/fonts/simfang.ttf"):
""" """
Visualize the results of OCR detection and recognition Visualize the results of OCR detection and recognition
args: args:
...@@ -411,22 +493,4 @@ def draw_boxes(image, boxes, scores=None, drop_score=0.5): ...@@ -411,22 +493,4 @@ def draw_boxes(image, boxes, scores=None, drop_score=0.5):
if __name__ == '__main__': if __name__ == '__main__':
test_img = "./doc/test_v2" pass
predict_txt = "./doc/predict.txt"
f = open(predict_txt, 'r')
data = f.readlines()
img_path, anno = data[0].strip().split('\t')
img_name = os.path.basename(img_path)
img_path = os.path.join(test_img, img_name)
image = Image.open(img_path)
data = json.loads(anno)
boxes, txts, scores = [], [], []
for dic in data:
boxes.append(dic['points'])
txts.append(dic['transcription'])
scores.append(round(dic['scores'], 3))
new_img = draw_ocr(image, boxes, txts, scores)
cv2.imwrite(img_name, new_img)
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或