diff --git a/deploy/paddleocr-go/README.md b/deploy/paddleocr-go/README.md new file mode 100644 index 0000000000000000000000000000000000000000..1332c3c0b31c7b6943dfe616deeffc447d6be218 --- /dev/null +++ b/deploy/paddleocr-go/README.md @@ -0,0 +1,328 @@ +# PaddleOCR-GO + +本服务是[PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)的golang部署版本。 + +## 1. 环境准备 + +### 运行环境 + +- go: 1.14 +- OpenCV: 4.3.0 +- PaddlePaddle: 1.8.4 +- 编译环境：cmake 3.15.4 | gcc 4.8.5 +- 基于Centos 7.4运行环境编译，Windows请自行解决`OpenCV`和`PaddlePaddle`的编译问题 + +*另外，以下编译以`.bashrc`个人环境变量配置文件，如果使用`zsh`，请自行更换为`.zshrc`* + +### 1.1 安装golang + +从官网下载[golang](https://golang.org/dl/)，建议选择1.13版本以上进行安装。下载完成后，直接解压你需要的安装目录，并配置相关环境变量，此处以1.14版本为例。 + +```shell +# 下载golang +wget https://golang.org/dl/go1.14.10.linux-amd64.tar.gz + +# 解压到 /usr/local 目录下 +tar -xzvf go1.14.10.linux-amd64.tar.gz -C /usr/local + +# 配置GOROOT，即go的安装目录 +echo "export GOROOT=/usr/local/go" >> ~/.bashrc +# 配置GOPATH，即go相关package的安装目录，可自定义一个目录 +echo "export GOPATH=$HOME/golang" >> ~/.bashrc +# 配置GOPROXY，即go mod包管理器的下载代理，同时打开mod模式 +echo "export GO111MODULE=on" >> ~/.bashrc +echo "export GOPROXY=https://mirrors.aliyun.com/goproxy/" >> ~/.bashrc +source ~/.bashrc +``` + +### 1.2 编译OpenCV库 + +go语言中，OpenCV的使用主要以[gocv](https://github.com/hybridgroup/gocv)包为主，gocv使用cgo调用OpenCV提供接口，因此还是需要编译OpenCV库。 + +**踩坑指南之一：[gocv官方实现](https://github.com/hybridgroup/gocv)中，部分接口并没有与原版C++的OpenCV的API保持一致，导致图片处理结果会出现一定的数值偏差。为处理这种偏差，[该仓库](https://github.com/LKKlein/gocv)fork了一份gocv官方源码，并对部分这些不一致的API进行了修正，保证结果与其他语言的一致性。** + +对于OpenCV的编译，gocv官方提供了[Makefile](https://github.com/LKKlein/gocv/blob/lk/Makefile)，可以一键进行安装，具体安装步骤详见[官方指南](https://github.com/LKKlein/gocv/blob/lk/README_ORIGIN.md#ubuntulinux)。 + +这里提供逐步安装的方式，方便排查错误。 + +- 下载并解压OpenCV-4.3.0和OpenCV-Contrib-4.3.0 + +```shell +# 创建opencv安装目录 +mkdir -p ~/opencv + +# 下载OpenCV +cd ~/opencv +curl -sL https://github.com/opencv/opencv/archive/4.3.0.zip > opencv.zip +unzip -q opencv.zip +rm -rf opencv.zip + +# 下载OpenCV-Contrib +curl -sL https://github.com/opencv/opencv_contrib/archive/4.3.0.zip > opencv-contrib.zip +unzip -q opencv-contrib.zip +rm -rf opencv-contrib.zip +``` + +- 安装相关依赖 + +```shell +sudo yum -y install pkgconfig cmake git gtk2-devel libpng-devel libjpeg-devel libtiff-devel tbb tbb-devel libdc1394-devel +``` + +- 编译安装 + +```shell +mkdir -p ~/.local/opencv-4.3.0 +cd ~/opencv/opencv-4.3.0 +mkdir build +cd build +cmake -D WITH_IPP=OFF \ + -D WITH_OPENGL=OFF \ + -D WITH_QT=OFF \ + -D BUILD_EXAMPLES=OFF \ + -D BUILD_TESTS=OFF \ + -D BUILD_PERF_TESTS=OFF \ + -D BUILD_opencv_java=OFF \ + -D BUILD_opencv_python=OFF \ + -D BUILD_opencv_python2=OFF \ + -D BUILD_opencv_python3=OFF \ + -D OPENCV_GENERATE_PKGCONFIG=ON \ + -D CMAKE_INSTALL_PREFIX=$HOME/.local/opencv-4.3.0 \ + -D OPENCV_ENABLE_NONFREE=ON \ + -D OPENCV_EXTRA_MODULES_PATH=$HOME/opencv/opencv_contrib-4.3.0/modules .. +make -j8 +make install +sudo ldconfig +``` + +make进行编译时，可能出现因`xfeatures2d`的两个模块下载失败导致的编译失败，这里只需要手动下载这部分文件到`$HOME/opencv/opencv_contrib-4.3.0/modules/xfeatures2d/src`目录下，然后重新执行`make -j8`即可。这部分文件地址可参考[这里](https://github.com/opencv/opencv_contrib/issues/1301#issuecomment-447181426)给出的链接。 + +- 配置环境变量 + +```shell +echo "export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:$HOME/.local/opencv-4.3.0/lib64/pkgconfig" >> ~/.bashrc +echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HOME/.local/opencv-4.3.0/lib64" >> ~/.bashrc +source ~/.bashrc +``` + +- 验证安装 + +```shell +# 安装gocv包，先mod init +go mod init opencv +go get -u github.com/LKKlein/gocv + +# 验证安装结果 +cd $GOPATH/pkg/mod/github.com/!l!k!klein/gocv@v0.28.0 +go run ./cmd/version/main.go + +# 输出 +# gocv version: 0.28.0 +# opencv lib version: 4.3.0 +``` + +### 1.3 编译PaddlePaddle的C语言API + +go语言只能通过cgo调用C语言API，而不能直接与C++进行交互，因此需要编译PaddlePaddle的C语言API。当然，也可以自己写C语言调用C++的代码和头文件，这样就可以直接使用PaddlePaddle提供的已编译的C++推理库，无需自己手动编译，详见[该仓库](https://github.com/LKKlein/paddleocr-go/tree/dev_cxx)。 + +- 获取PaddlePaddle源代码 + +```shell +cd ~ +git clone --recurse-submodules https://github.com/paddlepaddle/paddle + +# 切换到v1.8.4版本 +cd paddle +git checkout v1.8.4 + +# 目前版本无论单卡还是多卡都需要先安装nccl +git clone https://github.com/NVIDIA/nccl.git +make -j8 +make install +``` + +- 编译Paddle源代码 + +**踩坑指南之二：PaddlePaddle的C语言API实现有一个bug，即获取输入输出变量名时只能获取到第一个模型的变量名，后续模型都无法获取输入输出变量名，进而无法获取到模型输出，详情见[issue](https://github.com/PaddlePaddle/Paddle/issues/28309)。因此，编译前需要手动将`paddle/fluid/inference/capi/pd_predictor.cc`文件中`210行`与`215行`的`static`删除。** + +在处理完该bug之后，才能进行后续编译。相关编译参数见[官方文档](https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html#id12)，注意部分参数需要相关依赖，请确保依赖完整再启用。 + +```shell +# 创建c++推理库文件夹 +mkdir -p ~/paddle_inference +export PADDLE_ROOT=`$HOME/paddle_inference` + +# 执行编译 +mkdir build +cd build +cmake -DFLUID_INFERENCE_INSTALL_DIR=$PADDLE_ROOT \ + -DWITH_CONTRIB=OFF \ + -DCMAKE_BUILD_TYPE=Release \ + -DWITH_PYTHON=OFF \ + -DWITH_MKL=ON \ + -DWITH_GPU=ON \ + -DON_INFER=ON \ + --WITH_MKLDNN=ON \ + --WITH_XBYAK=ON \ + --WITH_DSO=OFF .. +make +make inference_lib_dist +``` + +编译完成后，可以在`build/fluid_inference_c_install_dir`目录下，看到以下生成的文件 + +``` +build/fluid_inference_c_install_dir +├── paddle +├── third_party +└── version.txt +``` + +其中`paddle`就是Paddle库的C语言预测API，`version.txt`中包含当前预测库的版本信息。 + + +## 2. paddleocr-go预测库 + +### 2.1 安装paddleocr-go + +直接执行安装命令 + +```shell +go get github.com/PaddlePaddle/PaddleOCR/deploy/paddleocr-go +``` + +### 2.2 相关使用API + +在go中使用import引入包 + +```go +import github.com/PaddlePaddle/PaddleOCR/deploy/paddleocr-go/ocr +``` + +- 预测结果结构体 + +```go +type OCRText struct { + BBox [][]int `json:"bbox"` + Text string `json:"text"` + Score float64 `json:"score"` +} +``` + +一张图的OCR结果包含多个`OCRText`结果，每个结果包含预测框、预测文本、预测文本得分。 + +- OCR预测类 + + +```go +func NewOCRSystem(confFile string, a map[string]interface{}) *OCRSystem +``` + +`OCRSystem`是主要对外提供API的结构； + +`confFile`是yaml配置文件的路径，可在配置文件中修改相关预测参数，也可以传空字符串，这时会全部使用默认配置； + +`a`是可以在代码中直接定义的配置参数，优先级高于配置文件，会覆盖配置文件和默认配置的参数。 + +- 单张图预测API + +```go  +func (ocr *OCRSystem) PredictOneImage(img gocv.Mat) []OCRText +``` + + +- 图片文件夹预测API + +```go +func (ocr *OCRSystem) PredictDirImages(dirname string) map[string][]OCRText +``` + +`dirname`图片文件夹的目录，默认会预测改目录下所有`jpg`和`png`图片，并返回每张图的预测结果。 + +- OCR Server + +```go +func (ocr *OCRSystem) StartServer(port string) +``` + +开启OCR预测Server，开启后，使用`post`请求上传需要识别的图片至`http://$ip:$port/ocr`即可直接获取该图片上所有文本的识别结果。其中，`$ip`是开启服务的主机`ip`或`127.0.0.1`的本地ip， `$port`是传入的端口参数。 + + +## 3. 预测demo + +### 3.1 修改预测配置 + +当前给定的配置文件`config/conf.yaml`中，包含了默认的OCR预测配置参数，可根据个人需要更改相关参数。 + +比如，将`use_gpu`改为`false`，使用CPU执行预测；将`det_model_dir`, `rec_model_dir`, `cls_model_dir`都更改为自己的本地模型路径，也或者是更改字典`rec_char_dict_path`的路径。配置参数包含了预测引擎、检测模型、检测阈值、方向分类模型、识别模型及阈值的相关参数，具体参数的意义可参见[PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/whl.md#%E5%8F%82%E6%95%B0%E8%AF%B4%E6%98%8E)。 + +### 3.2 编译预测demo + +- 下载`paddleocr-go`代码 + +```shell +git clone https://github.com/PaddlePaddle/PaddleOCR +cd PaddleOCR/deploy/paddleocr-go +``` + +- 准备paddle_c环境 + +```shell +cp -r ~/paddle/build/fluid_inference_c_install_dir/* paddle_c/ +``` + +- 编译demo + +```shell +go build demo.go +``` + +### 3.3 执行预测demo + +预测demo提供了三种预测方式，分别是单张图预测、文件夹批量预测、OCR Server预测。三者命令行优先级依次降低。 + +#### 3.3.1 单张图预测 + +```shell +./demo --config config/conf.yaml --image images/test.jpg +``` + +执行完成，会输出以下内容： + + + +#### 3.3.2 文件夹批量预测 + +```shell +./demo --config config/conf.yaml --image_dir ./images +``` + +执行完成，会输出以下内容： + + + +#### 3.3.3 开启OCR Server + +```shell +./demo --use_servering --port=18600 +``` + +开启服务后，可以在其他客户端中通过`post`请求进行ocr预测。此处以`Python`客户端为例，如下所示 + +```python +import requests + +files = {'image': open('images/test.jpg','rb')} +url = "http://127.0.0.1:18600/ocr" + +r = requests.post(url, files=files) +print(r.text) +``` + +执行完成可以得到以下结果 + +![](./images/result/python_client_result.jpg) + +最后，在Python中将上述结果可视化可以得到以下结果 + +![](./images/result/python_vis_result.jpg) diff --git a/deploy/paddleocr-go/config/conf.yaml b/deploy/paddleocr-go/config/conf.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c6b5b7914bfc51cb0e14a614bf696c34083097cf --- /dev/null +++ b/deploy/paddleocr-go/config/conf.yaml @@ -0,0 +1,47 @@ +# params for prediction engine +use_gpu: true +ir_optim: true +enable_mkldnn: false +# use_zero_copy_run: true +use_tensorrt: false +num_cpu_threads: 6 +gpu_id: 0 +gpu_mem: 2000 + +# params for text detector +det_algorithm: "DB" +det_model_dir: "https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar" +det_max_side_len: 960 + +# DB parmas +det_db_thresh: 0.3 +det_db_box_thresh: 0.5 +det_db_unclip_ratio: 2.0 + +# EAST parmas +det_east_score_thresh: 0.8 +det_east_cover_thresh: 0.1 +det_east_nms_thresh: 0.2 + +# params for text recognizer +rec_algorithm: "CRNN" +rec_model_dir: "https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar" +rec_image_shape: [3, 32, 320] +rec_char_type: "ch" +rec_batch_num: 30 +max_text_length: 25 +rec_char_dict_path: "config/ppocr_keys_v1.txt" +use_space_char: true + +# params for text classifier +use_angle_cls: false +cls_model_dir: "https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar" +cls_image_shape: [3, 48, 192] +label_list: ["0", "180"] +cls_batch_num: 30 +cls_thresh: 0.9 + +lang: ch +det: true +rec: true +cls: false \ No newline at end of file diff --git a/deploy/paddleocr-go/config/ppocr_keys_v1.txt b/deploy/paddleocr-go/config/ppocr_keys_v1.txt new file mode 100644 index 0000000000000000000000000000000000000000..84b885d8352226e49b1d5d791b8f43a663e246aa --- /dev/null +++ b/deploy/paddleocr-go/config/ppocr_keys_v1.txt @@ -0,0 +1,6623 @@ +' +疗 +绚 +诚 +娇 +溜 +题 +贿 +者 +廖 +更 +纳 +加 +奉 +公 +一 +就 +汴 +计 +与 +路 +房 +原 +妇 +2 +0 +8 +- +7 +其 +> +: +] +, +， +骑 +刈 +全 +消 +昏 +傈 +安 +久 +钟 +嗅 +不 +影 +处 +驽 +蜿 +资 +关 +椤 +地 +瘸 +专 +问 +忖 +票 +嫉 +炎 +韵 +要 +月 +田 +节 +陂 +鄙 +捌 +备 +拳 +伺 +眼 +网 +盎 +大 +傍 +心 +东 +愉 +汇 +蹿 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confFile string + image string + imageDir string + useServering bool + port string +) + +func init() { + flag.StringVar(&confFile, "config", "config/conf.yaml", "config from ocr system. If not given, will use default config.") + flag.StringVar(&image, "image", "", "image to predict. if not given, will use image_dir") + flag.StringVar(&imageDir, "image_dir", "", "imgs in dir to be predicted. if not given, will check servering") + flag.BoolVar(&useServering, "use_servering", false, "whether to use ocr server. [default: false]") + flag.StringVar(&port, "port", "18600", "which port to serve ocr server. [default: 18600].") +} + +func main() { + flag.Parse() + sys := ocr.NewOCRSystem(confFile, nil) + + if image != "" { + img := ocr.ReadImage(image) + results := sys.PredictOneImage(img) + for _, res := range results { + log.Println(res) + } + return + } + + if imageDir != "" { + results := sys.PredictDirImages(imageDir) + for k, vs := range results { + log.Printf("======== image: %v =======\n", k) + for _, res := range vs { + log.Println(res) + } + } + } + + if useServering { + sys.StartServer(port) + } +} diff --git a/deploy/paddleocr-go/go.mod b/deploy/paddleocr-go/go.mod new file mode 100644 index 0000000000000000000000000000000000000000..43b63477ffa1ba59e7b81e4db6112941183f3114 --- /dev/null +++ b/deploy/paddleocr-go/go.mod @@ -0,0 +1,9 @@ +module paddleocr-go + +go 1.14 + +require ( + github.com/LKKlein/gocv v0.28.0 + github.com/ctessum/go.clipper v0.0.0-20200522184404-9c744fa3e86c + gopkg.in/yaml.v3 v3.0.0-20200615113413-eeeca48fe776 +) diff --git a/deploy/paddleocr-go/go.sum b/deploy/paddleocr-go/go.sum new file mode 100644 index 0000000000000000000000000000000000000000..4f1fd3fa23912e91a9d67d4d34c46661cbfe996d --- /dev/null +++ b/deploy/paddleocr-go/go.sum @@ -0,0 +1,9 @@ +github.com/LKKlein/gocv v0.27.0 h1:JGNBMa2HY7HC0VlVHB4gdFjoc9NlyyrQvlUdBMWWSYw= +github.com/LKKlein/gocv v0.27.0/go.mod h1:MP408EL7eakRU3vzjsozzfELSX7HDDGdMpWANV1IOHY= +github.com/LKKlein/gocv v0.28.0 h1:1MMvs9uYf+QGPi86it2pUmN8RRoyMnPLUefKB/Jf1Q0= +github.com/LKKlein/gocv v0.28.0/go.mod h1:MP408EL7eakRU3vzjsozzfELSX7HDDGdMpWANV1IOHY= +github.com/ctessum/go.clipper v0.0.0-20200522184404-9c744fa3e86c h1:VXCsVlam0R2Yl7VET2GxZBPdOa7gFRexyhfWb9v9QtM= +github.com/ctessum/go.clipper v0.0.0-20200522184404-9c744fa3e86c/go.mod h1:KRMo3PCsooJP3LmCwKI76dkd7f3ki3zwYLHR7Iwbi5k= +gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0= +gopkg.in/yaml.v3 v3.0.0-20200615113413-eeeca48fe776 h1:tQIYjPdBoyREyB9XMu+nnTclpTYkz2zFM+lzLJFO4gQ= +gopkg.in/yaml.v3 v3.0.0-20200615113413-eeeca48fe776/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM= diff --git a/deploy/paddleocr-go/images/0.jpg b/deploy/paddleocr-go/images/0.jpg new file mode 100644 index 0000000000000000000000000000000000000000..b417220d9a6ebf0ed4d5c5578eb0128f8701ab6e Binary files /dev/null and b/deploy/paddleocr-go/images/0.jpg differ diff --git a/deploy/paddleocr-go/images/result/img_dir_result.jpg b/deploy/paddleocr-go/images/result/img_dir_result.jpg new file mode 100644 index 0000000000000000000000000000000000000000..5341f81648d568dc0b844b7779d6cd8a7a4b870f Binary files /dev/null and b/deploy/paddleocr-go/images/result/img_dir_result.jpg differ diff --git a/deploy/paddleocr-go/images/result/python_client_result.jpg b/deploy/paddleocr-go/images/result/python_client_result.jpg new file mode 100644 index 0000000000000000000000000000000000000000..556573a99850552d2859219773ab70589d9ac065 Binary files /dev/null and b/deploy/paddleocr-go/images/result/python_client_result.jpg differ diff --git a/deploy/paddleocr-go/images/result/python_vis_result.jpg b/deploy/paddleocr-go/images/result/python_vis_result.jpg new file mode 100644 index 0000000000000000000000000000000000000000..af26bdd117bf21adba3b80a6d73c7ff54b46b2bc Binary files /dev/null and b/deploy/paddleocr-go/images/result/python_vis_result.jpg differ diff --git a/deploy/paddleocr-go/images/result/single_img_result.jpg b/deploy/paddleocr-go/images/result/single_img_result.jpg new file mode 100644 index 0000000000000000000000000000000000000000..686841d71e12a6142c32288fc41bbc03a9edf177 Binary files /dev/null and b/deploy/paddleocr-go/images/result/single_img_result.jpg differ diff --git a/deploy/paddleocr-go/images/test.jpg b/deploy/paddleocr-go/images/test.jpg new file mode 100644 index 0000000000000000000000000000000000000000..ed91b8c5ca2a348fe7b138e83114ff81ecb107de Binary files /dev/null and b/deploy/paddleocr-go/images/test.jpg differ diff --git a/deploy/paddleocr-go/ocr/core.go b/deploy/paddleocr-go/ocr/core.go new file mode 100644 index 0000000000000000000000000000000000000000..626eeb5410b419bf6bbd9c8fc64f40d495e9c0d8 --- /dev/null +++ b/deploy/paddleocr-go/ocr/core.go @@ -0,0 +1,259 @@ +package ocr + +import ( + "bytes" + "encoding/json" + "errors" + "image" + "image/color" + "io" + "log" + "math" + "net/http" + "paddleocr-go/paddle" + "path" + "path/filepath" + "sort" + "strings" + + "github.com/LKKlein/gocv" +) + +type PaddleModel struct { + predictor *paddle.Predictor + input *paddle.ZeroCopyTensor + outputs []*paddle.ZeroCopyTensor + + useGPU bool + deviceID int + initGPUMem int + numThreads int + useMKLDNN bool + useTensorRT bool + useIROptim bool +} + +func NewPaddleModel(args map[string]interface{}) *PaddleModel { + return &PaddleModel{ + useGPU: getBool(args, "use_gpu", false), + deviceID: getInt(args, "gpu_id", 0), + initGPUMem: getInt(args, "gpu_mem", 1000), + numThreads: getInt(args, "num_cpu_threads", 6), + useMKLDNN: getBool(args, "enable_mkldnn", false), + useTensorRT: getBool(args, "use_tensorrt", false), + useIROptim: getBool(args, "ir_optim", true), + } +} + +func (model *PaddleModel) LoadModel(modelDir string) { + config := paddle.NewAnalysisConfig() + config.DisableGlogInfo() + + config.SetModel(modelDir+"/model", modelDir+"/params") + if model.useGPU { + config.EnableUseGpu(model.initGPUMem, model.deviceID) + } else { + config.DisableGpu() + config.SetCpuMathLibraryNumThreads(model.numThreads) + if model.useMKLDNN { + config.EnableMkldnn() + } + } + + // config.EnableMemoryOptim() + if model.useIROptim { + config.SwitchIrOptim(true) + } + + // false for zero copy tensor + config.SwitchUseFeedFetchOps(false) + config.SwitchSpecifyInputNames(true) + + model.predictor = paddle.NewPredictor(config) + model.input = model.predictor.GetInputTensors()[0] + model.outputs = model.predictor.GetOutputTensors() +} + +type OCRText struct { + BBox [][]int `json:"bbox"` + Text string `json:"text"` + Score float64 `json:"score"` +} + +type TextPredictSystem struct { + detector *DBDetector + cls *TextClassifier + rec *TextRecognizer +} + +func NewTextPredictSystem(args map[string]interface{}) *TextPredictSystem { + sys := &TextPredictSystem{ + detector: NewDBDetector(getString(args, "det_model_dir", ""), args), + rec: NewTextRecognizer(getString(args, "rec_model_dir", ""), args), + } + if getBool(args, "use_angle_cls", false) { + sys.cls = NewTextClassifier(getString(args, "cls_model_dir", ""), args) + } + return sys +} + +func (sys *TextPredictSystem) sortBoxes(boxes [][][]int) [][][]int { + sort.Slice(boxes, func(i, j int) bool { + if boxes[i][0][1] < boxes[j][0][1] { + return true + } + if boxes[i][0][1] > boxes[j][0][1] { + return false + } + return boxes[i][0][0] < boxes[j][0][0] + }) + + for i := 0; i < len(boxes)-1; i++ { + if math.Abs(float64(boxes[i+1][0][1]-boxes[i][0][1])) < 10 && boxes[i+1][0][0] < boxes[i][0][0] { + boxes[i], boxes[i+1] = boxes[i+1], boxes[i] + } + } + return boxes +} + +func (sys *TextPredictSystem) getRotateCropImage(img gocv.Mat, box [][]int) gocv.Mat { + cropW := int(math.Sqrt(math.Pow(float64(box[0][0]-box[1][0]), 2) + math.Pow(float64(box[0][1]-box[1][1]), 2))) + cropH := int(math.Sqrt(math.Pow(float64(box[0][0]-box[3][0]), 2) + math.Pow(float64(box[0][1]-box[3][1]), 2))) + ptsstd := make([]image.Point, 4) + ptsstd[0] = image.Pt(0, 0) + ptsstd[1] = image.Pt(cropW, 0) + ptsstd[2] = image.Pt(cropW, cropH) + ptsstd[3] = image.Pt(0, cropH) + + points := make([]image.Point, 4) + points[0] = image.Pt(box[0][0], box[0][1]) + points[1] = image.Pt(box[1][0], box[1][1]) + points[2] = image.Pt(box[2][0], box[2][1]) + points[3] = image.Pt(box[3][0], box[3][1]) + + M := gocv.GetPerspectiveTransform(points, ptsstd) + defer M.Close() + dstimg := gocv.NewMat() + gocv.WarpPerspectiveWithParams(img, &dstimg, M, image.Pt(cropW, cropH), + gocv.InterpolationCubic, gocv.BorderReplicate, color.RGBA{0, 0, 0, 0}) + + if float64(dstimg.Rows()) >= float64(dstimg.Cols())*1.5 { + srcCopy := gocv.NewMat() + gocv.Transpose(dstimg, &srcCopy) + defer dstimg.Close() + gocv.Flip(srcCopy, &srcCopy, 0) + return srcCopy + } + return dstimg +} + +func (sys *TextPredictSystem) Run(img gocv.Mat) []OCRText { + srcimg := gocv.NewMat() + img.CopyTo(&srcimg) + boxes := sys.detector.Run(img) + if len(boxes) == 0 { + return nil + } + + boxes = sys.sortBoxes(boxes) + cropimages := make([]gocv.Mat, len(boxes)) + for i := 0; i < len(boxes); i++ { + tmpbox := make([][]int, len(boxes[i])) + for j := 0; j < len(tmpbox); j++ { + tmpbox[j] = make([]int, len(boxes[i][j])) + copy(tmpbox[j], boxes[i][j]) + } + cropimg := sys.getRotateCropImage(srcimg, tmpbox) + cropimages[i] = cropimg + } + if sys.cls != nil { + cropimages = sys.cls.Run(cropimages) + } + recResult := sys.rec.Run(cropimages, boxes) + return recResult +} + +type OCRSystem struct { + args map[string]interface{} + tps *TextPredictSystem +} + +func NewOCRSystem(confFile string, a map[string]interface{}) *OCRSystem { + args, err := ReadYaml(confFile) + if err != nil { + log.Printf("Read config file %v failed! Please check. err: %v\n", confFile, err) + log.Println("Program will use default config.") + args = defaultArgs + } + for k, v := range a { + args[k] = v + } + return &OCRSystem{ + args: args, + tps: NewTextPredictSystem(args), + } +} + +func (ocr *OCRSystem) StartServer(port string) { + http.HandleFunc("/ocr", ocr.predictHandler) + log.Println("OCR Server has been started on port :", port) + err := http.ListenAndServe(":"+port, nil) + if err != nil { + log.Panicf("http error! error: %v\n", err) + } +} + +func (ocr *OCRSystem) predictHandler(w http.ResponseWriter, r *http.Request) { + if r.Method != "POST" { + w.Write([]byte(errors.New("post method only").Error())) + return + } + r.ParseMultipartForm(32 << 20) + var buf bytes.Buffer + file, header, err := r.FormFile("image") + if err != nil { + w.Write([]byte(err.Error())) + return + } + defer file.Close() + ext := strings.ToLower(path.Ext(header.Filename)) + if ext != ".jpg" && ext != ".png" { + w.Write([]byte(errors.New("only support image endswith jpg/png").Error())) + return + } + + io.Copy(&buf, file) + img, err2 := gocv.IMDecode(buf.Bytes(), gocv.IMReadColor) + if err2 != nil { + w.Write([]byte(err2.Error())) + return + } + result := ocr.PredictOneImage(img) + if output, err3 := json.Marshal(result); err3 != nil { + w.Write([]byte(err3.Error())) + } else { + w.Write(output) + } +} + +func (ocr *OCRSystem) PredictOneImage(img gocv.Mat) []OCRText { + return ocr.tps.Run(img) +} + +func (ocr *OCRSystem) PredictDirImages(dirname string) map[string][]OCRText { + if dirname == "" { + return nil + } + + imgs, _ := filepath.Glob(dirname + "/*.jpg") + tmpimgs, _ := filepath.Glob(dirname + "/*.png") + imgs = append(imgs, tmpimgs...) + results := make(map[string][]OCRText, len(imgs)) + for i := 0; i < len(imgs); i++ { + imgname := imgs[i] + img := ReadImage(imgname) + res := ocr.PredictOneImage(img) + results[imgname] = res + } + return results +} diff --git a/deploy/paddleocr-go/ocr/default_args.go b/deploy/paddleocr-go/ocr/default_args.go new file mode 100644 index 0000000000000000000000000000000000000000..6afd69e7fa01cd9227c3679a3d07dc781e8a2638 --- /dev/null +++ b/deploy/paddleocr-go/ocr/default_args.go @@ -0,0 +1,46 @@ +package ocr + +var ( + defaultArgs = map[string]interface{}{ + "use_gpu": true, + "ir_optim": true, + "enable_mkldnn": false, + "use_tensorrt": false, + "num_cpu_threads": 6, + "gpu_id": 0, + "gpu_mem": 2000, + + "det_algorithm": "DB", + "det_model_dir": "https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar", + "det_max_side_len": 960, + + "det_db_thresh": 0.3, + "det_db_box_thresh": 0.5, + "det_db_unclip_ratio": 2.0, + + "det_east_score_thresh": 0.8, + "det_east_cover_thresh": 0.1, + "det_east_nms_thresh": 0.2, + + "rec_algorithm": "CRNN", + "rec_model_dir": "https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar", + "rec_image_shape": []interface{}{3, 32, 320}, + "rec_char_type": "ch", + "rec_batch_num": 30, + "max_text_length": 25, + "rec_char_dict_path": "config/ppocr_keys_v1.txt", + "use_space_char": true, + + "use_angle_cls": false, + "cls_model_dir": "https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar", + "cls_image_shape": []interface{}{3, 48, 192}, + "label_list": []interface{}{"0", "180"}, + "cls_batch_num": 30, + "cls_thresh": 0.9, + + "lang": "ch", + "det": true, + "rec": true, + "cls": false, + } +) diff --git a/deploy/paddleocr-go/ocr/ocr_cls.go b/deploy/paddleocr-go/ocr/ocr_cls.go new file mode 100644 index 0000000000000000000000000000000000000000..c46d6e8e55a6090dfd6839badc1963e8c50d18ea --- /dev/null +++ b/deploy/paddleocr-go/ocr/ocr_cls.go @@ -0,0 +1,105 @@ +package ocr + +import ( + "log" + "time" + + "github.com/LKKlein/gocv" +) + +type TextClassifier struct { + *PaddleModel + batchNum int + thresh float64 + shape []int + labels []string +} + +type ClsResult struct { + Score float32 + Label int64 +} + +func NewTextClassifier(modelDir string, args map[string]interface{}) *TextClassifier { + shapes := []int{3, 48, 192} + if v, ok := args["cls_image_shape"]; ok { + for i, s := range v.([]interface{}) { + shapes[i] = s.(int) + } + } + cls := &TextClassifier{ + PaddleModel: NewPaddleModel(args), + batchNum: getInt(args, "cls_batch_num", 30), + thresh: getFloat64(args, "cls_thresh", 0.9), + shape: shapes, + } + if checkModelExists(modelDir) { + modelDir, _ = downloadModel("./inference/cls", modelDir) + } else { + log.Panicf("cls model path: %v not exist! Please check!", modelDir) + } + cls.LoadModel(modelDir) + return cls +} + +func (cls *TextClassifier) Run(imgs []gocv.Mat) []gocv.Mat { + batch := cls.batchNum + var clsTime int64 = 0 + clsout := make([]ClsResult, len(imgs)) + srcimgs := make([]gocv.Mat, len(imgs)) + c, h, w := cls.shape[0], cls.shape[1], cls.shape[2] + for i := 0; i < len(imgs); i += batch { + j := i + batch + if len(imgs) < j { + j = len(imgs) + } + + normImgs := make([]float32, (j-i)*c*h*w) + for k := i; k < j; k++ { + tmp := gocv.NewMat() + imgs[k].CopyTo(&tmp) + srcimgs[k] = tmp + img := clsResize(imgs[k], cls.shape) + data := normPermute(img, []float32{0.5, 0.5, 0.5}, []float32{0.5, 0.5, 0.5}, 255.0) + copy(normImgs[(k-i)*c*h*w:], data) + } + + st := time.Now() + cls.input.SetValue(normImgs) + cls.input.Reshape([]int32{int32(j - i), int32(c), int32(h), int32(w)}) + + cls.predictor.SetZeroCopyInput(cls.input) + cls.predictor.ZeroCopyRun() + cls.predictor.GetZeroCopyOutput(cls.outputs[0]) + cls.predictor.GetZeroCopyOutput(cls.outputs[1]) + + var probout [][]float32 + var labelout []int64 + if len(cls.outputs[0].Shape()) == 2 { + probout = cls.outputs[0].Value().([][]float32) + } else { + labelout = cls.outputs[0].Value().([]int64) + } + + if len(cls.outputs[1].Shape()) == 2 { + probout = cls.outputs[1].Value().([][]float32) + } else { + labelout = cls.outputs[1].Value().([]int64) + } + clsTime += int64(time.Since(st).Milliseconds()) + + for no, label := range labelout { + score := probout[no][label] + clsout[i+no] = ClsResult{ + Score: score, + Label: label, + } + + if label%2 == 1 && float64(score) > cls.thresh { + gocv.Rotate(srcimgs[i+no], &srcimgs[i+no], gocv.Rotate180Clockwise) + } + } + } + log.Println("cls num: ", len(clsout), ", cls time elapse: ", clsTime, "ms") + return srcimgs +} diff --git a/deploy/paddleocr-go/ocr/ocr_det.go b/deploy/paddleocr-go/ocr/ocr_det.go new file mode 100644 index 0000000000000000000000000000000000000000..4773d5bed17887c91ac21054b162deae9ce962ce --- /dev/null +++ b/deploy/paddleocr-go/ocr/ocr_det.go @@ -0,0 +1,52 @@ +package ocr + +import ( + "log" + "time" + + "github.com/LKKlein/gocv" +) + +type DBDetector struct { + *PaddleModel + preProcess DetPreProcess + postProcess DetPostProcess +} + +func NewDBDetector(modelDir string, args map[string]interface{}) *DBDetector { + maxSideLen := getInt(args, "det_max_side_len", 960) + thresh := getFloat64(args, "det_db_thresh", 0.3) + boxThresh := getFloat64(args, "det_db_box_thresh", 0.5) + unClipRatio := getFloat64(args, "det_db_unclip_ratio", 2.0) + + detector := &DBDetector{ + PaddleModel: NewPaddleModel(args), + preProcess: NewDBProcess(make([]int, 0), maxSideLen), + postProcess: NewDBPostProcess(thresh, boxThresh, unClipRatio), + } + if checkModelExists(modelDir) { + modelDir, _ = downloadModel("./inference/det", modelDir) + } else { + log.Panicf("det model path: %v not exist! Please check!", modelDir) + } + detector.LoadModel(modelDir) + return detector +} + +func (det *DBDetector) Run(img gocv.Mat) [][][]int { + oriH := img.Rows() + oriW := img.Cols() + data, resizeH, resizeW := det.preProcess.Run(img) + st := time.Now() + det.input.SetValue(data) + det.input.Reshape([]int32{1, 3, int32(resizeH), int32(resizeW)}) + + det.predictor.SetZeroCopyInput(det.input) + det.predictor.ZeroCopyRun() + det.predictor.GetZeroCopyOutput(det.outputs[0]) + + ratioH, ratioW := float64(resizeH)/float64(oriH), float64(resizeW)/float64(oriW) + boxes := det.postProcess.Run(det.outputs[0], oriH, oriW, ratioH, ratioW) + log.Println("det_box num: ", len(boxes), ", time elapse: ", time.Since(st)) + return boxes +} diff --git a/deploy/paddleocr-go/ocr/ocr_rec.go b/deploy/paddleocr-go/ocr/ocr_rec.go new file mode 100644 index 0000000000000000000000000000000000000000..661718c87778030bf6efb9d03c51d45a4fb0e30c --- /dev/null +++ b/deploy/paddleocr-go/ocr/ocr_rec.go @@ -0,0 +1,128 @@ +package ocr + +import ( + "log" + "time" + + "github.com/LKKlein/gocv" +) + +type TextRecognizer struct { + *PaddleModel + batchNum int + textLen int + shape []int + charType string + labels []string +} + +func NewTextRecognizer(modelDir string, args map[string]interface{}) *TextRecognizer { + shapes := []int{3, 32, 320} + if v, ok := args["rec_image_shape"]; ok { + for i, s := range v.([]interface{}) { + shapes[i] = s.(int) + } + } + labelpath := getString(args, "rec_char_dict_path", "./config/ppocr_keys_v1.txt") + labels := readLines2StringSlice(labelpath) + if getBool(args, "use_space_char", true) { + labels = append(labels, " ") + } + rec := &TextRecognizer{ + PaddleModel: NewPaddleModel(args), + batchNum: getInt(args, "rec_batch_num", 30), + textLen: getInt(args, "max_text_length", 25), + charType: getString(args, "rec_char_type", "ch"), + shape: shapes, + labels: labels, + } + if checkModelExists(modelDir) { + modelDir, _ = downloadModel("./inference/rec/ch", modelDir) + } else { + log.Panicf("rec model path: %v not exist! Please check!", modelDir) + } + rec.LoadModel(modelDir) + return rec +} + +func (rec *TextRecognizer) Run(imgs []gocv.Mat, bboxes [][][]int) []OCRText { + recResult := make([]OCRText, 0, len(imgs)) + batch := rec.batchNum + var recTime int64 = 0 + c, h, w := rec.shape[0], rec.shape[1], rec.shape[2] + for i := 0; i < len(imgs); i += batch { + j := i + batch + if len(imgs) < j { + j = len(imgs) + } + + maxwhratio := 0.0 + for k := i; k < j; k++ { + h, w := imgs[k].Rows(), imgs[k].Cols() + ratio := float64(w) / float64(h) + if ratio > maxwhratio { + maxwhratio = ratio + } + } + + if rec.charType == "ch" { + w = int(32 * maxwhratio) + } + normimgs := make([]float32, (j-i)*c*h*w) + + for k := i; k < j; k++ { + data := crnnPreprocess(imgs[k], rec.shape, []float32{0.5, 0.5, 0.5}, + []float32{0.5, 0.5, 0.5}, 255.0, maxwhratio, rec.charType) + copy(normimgs[(k-i)*c*h*w:], data) + } + + st := time.Now() + rec.input.SetValue(normimgs) + rec.input.Reshape([]int32{int32(j - i), int32(c), int32(h), int32(w)}) + + rec.predictor.SetZeroCopyInput(rec.input) + rec.predictor.ZeroCopyRun() + rec.predictor.GetZeroCopyOutput(rec.outputs[0]) + rec.predictor.GetZeroCopyOutput(rec.outputs[1]) + + recIdxBatch := rec.outputs[0].Value().([][]int64) + recIdxLod := rec.outputs[0].Lod() + + predictBatch := rec.outputs[1].Value().([][]float32) + predictLod := rec.outputs[1].Lod() + recTime += int64(time.Since(st).Milliseconds()) + + for rno := 0; rno < len(recIdxLod)-1; rno++ { + predIdx := make([]int, 0, 2) + for beg := recIdxLod[rno]; beg < recIdxLod[rno+1]; beg++ { + predIdx = append(predIdx, int(recIdxBatch[beg][0])) + } + if len(predIdx) == 0 { + continue + } + words := "" + for n := 0; n < len(predIdx); n++ { + words += rec.labels[predIdx[n]] + } + + score := 0.0 + count := 0 + blankPosition := int(rec.outputs[1].Shape()[1]) + for beg := predictLod[rno]; beg < predictLod[rno+1]; beg++ { + argMaxID, maxVal := argmax(predictBatch[beg]) + if blankPosition-1-argMaxID > 0 { + score += float64(maxVal) + count++ + } + } + score = score / float64(count) + recResult = append(recResult, OCRText{ + BBox: bboxes[i+rno], + Text: words, + Score: score, + }) + } + } + log.Println("rec num: ", len(recResult), ", rec time elapse: ", recTime, "ms") + return recResult +} diff --git a/deploy/paddleocr-go/ocr/postprocess.go b/deploy/paddleocr-go/ocr/postprocess.go new file mode 100644 index 0000000000000000000000000000000000000000..64d1518b554e5e115a653a4e24d00bc9c4f06478 --- /dev/null +++ b/deploy/paddleocr-go/ocr/postprocess.go @@ -0,0 +1,264 @@ +package ocr + +import ( + "image" + "image/color" + "math" + "paddleocr-go/paddle" + "sort" + + "github.com/LKKlein/gocv" + clipper "github.com/ctessum/go.clipper" +) + +type xFloatSortBy [][]float32 + +func (a xFloatSortBy) Len() int { return len(a) } +func (a xFloatSortBy) Swap(i, j int) { a[i], a[j] = a[j], a[i] } +func (a xFloatSortBy) Less(i, j int) bool { return a[i][0] < a[j][0] } + +type xIntSortBy [][]int + +func (a xIntSortBy) Len() int { return len(a) } +func (a xIntSortBy) Swap(i, j int) { a[i], a[j] = a[j], a[i] } +func (a xIntSortBy) Less(i, j int) bool { return a[i][0] < a[j][0] } + +type DetPostProcess interface { + Run(output *paddle.ZeroCopyTensor, oriH, oriW int, ratioH, ratioW float64) [][][]int +} + +type DBPostProcess struct { + thresh float64 + boxThresh float64 + maxCandidates int + unClipRatio float64 + minSize int +} + +func NewDBPostProcess(thresh, boxThresh, unClipRatio float64) *DBPostProcess { + return &DBPostProcess{ + thresh: thresh, + boxThresh: boxThresh, + unClipRatio: unClipRatio, + maxCandidates: 1000, + minSize: 3, + } +} + +func (d *DBPostProcess) getMinBoxes(rect gocv.RotatedRect) [][]float32 { + points := gocv.NewMat() + gocv.BoxPoints(rect, &points) + defer points.Close() + array := d.mat2slice(points) + sort.Sort(xFloatSortBy(array)) + + point1, point2, point3, point4 := array[0], array[1], array[2], array[3] + if array[3][1] <= array[2][1] { + point2, point3 = array[3], array[2] + } else { + point2, point3 = array[2], array[3] + } + + if array[1][1] <= array[0][1] { + point1, point4 = array[1], array[0] + } else { + point1, point4 = array[0], array[1] + } + + array = [][]float32{point1, point2, point3, point4} + return array +} + +func (d *DBPostProcess) mat2slice(mat gocv.Mat) [][]float32 { + array := make([][]float32, mat.Rows()) + for i := 0; i < mat.Rows(); i++ { + tmp := make([]float32, mat.Cols()) + for j := 0; j < mat.Cols(); j++ { + tmp[j] = mat.GetFloatAt(i, j) + } + array[i] = tmp + } + return array +} + +func (d *DBPostProcess) boxScoreFast(array [][]float32, pred gocv.Mat) float64 { + height, width := pred.Rows(), pred.Cols() + boxX := []float32{array[0][0], array[1][0], array[2][0], array[3][0]} + boxY := []float32{array[0][1], array[1][1], array[2][1], array[3][1]} + + xmin := clip(int(math.Floor(float64(minf(boxX)))), 0, width-1) + xmax := clip(int(math.Ceil(float64(maxf(boxX)))), 0, width-1) + ymin := clip(int(math.Floor(float64(minf(boxY)))), 0, height-1) + ymax := clip(int(math.Ceil(float64(maxf(boxY)))), 0, height-1) + + mask := gocv.NewMatWithSize(ymax-ymin+1, xmax-xmin+1, gocv.MatTypeCV8UC1) + ppt := make([][]image.Point, 1) + ppt[0] = make([]image.Point, 4) + ppt[0][0] = image.Point{int(array[0][0]) - xmin, int(array[0][1]) - ymin} + ppt[0][1] = image.Point{int(array[1][0]) - xmin, int(array[1][1]) - ymin} + ppt[0][2] = image.Point{int(array[2][0]) - xmin, int(array[2][1]) - ymin} + ppt[0][3] = image.Point{int(array[3][0]) - xmin, int(array[3][1]) - ymin} + gocv.FillPoly(&mask, ppt, color.RGBA{0, 0, 1, 0}) + croppedImg := pred.Region(image.Rect(xmin, ymin, xmax+1, ymax+1)) + s := croppedImg.MeanWithMask(mask) + return s.Val1 +} + +func (d *DBPostProcess) unClip(box [][]float32) gocv.RotatedRect { + var area, dist float64 + for i := 0; i < 4; i++ { + area += float64(box[i][0]*box[(i+1)%4][1] - box[i][1]*box[(i+1)%4][0]) + dist += math.Sqrt(float64( + (box[i][0]-box[(i+1)%4][0])*(box[i][0]-box[(i+1)%4][0]) + + (box[i][1]-box[(i+1)%4][1])*(box[i][1]-box[(i+1)%4][1]), + )) + } + area = math.Abs(area / 2.0) + distance := area * d.unClipRatio / dist + offset := clipper.NewClipperOffset() + path := make([]*clipper.IntPoint, 4) + path[0] = &clipper.IntPoint{X: clipper.CInt(box[0][0]), Y: clipper.CInt(box[0][1])} + path[1] = &clipper.IntPoint{X: clipper.CInt(box[1][0]), Y: clipper.CInt(box[1][1])} + path[2] = &clipper.IntPoint{X: clipper.CInt(box[2][0]), Y: clipper.CInt(box[2][1])} + path[3] = &clipper.IntPoint{X: clipper.CInt(box[3][0]), Y: clipper.CInt(box[3][1])} + offset.AddPath(clipper.Path(path), clipper.JtRound, clipper.EtClosedPolygon) + soln := offset.Execute(distance) + + points := make([]image.Point, 0, 4) + for i := 0; i < len(soln); i++ { + for j := 0; j < len(soln[i]); j++ { + points = append(points, image.Point{int(soln[i][j].X), int(soln[i][j].Y)}) + } + } + + var res gocv.RotatedRect + if len(points) <= 0 { + points = make([]image.Point, 4) + points[0] = image.Pt(0, 0) + points[1] = image.Pt(1, 0) + points[2] = image.Pt(1, 1) + points[3] = image.Pt(0, 1) + res = gocv.RotatedRect{ + Contour: points, + BoundingRect: image.Rect(0, 0, 1, 1), + Center: gocv.Point2f{X: 0.5, Y: 0.5}, + Width: 1, + Height: 1, + Angle: 0, + } + } else { + res = gocv.MinAreaRect(points) + } + return res +} + +func (d *DBPostProcess) boxesFromBitmap(pred gocv.Mat, mask gocv.Mat, ratioH float64, ratioW float64) [][][]int { + height, width := mask.Rows(), mask.Cols() + mask.MultiplyUChar(255) + contours := gocv.FindContours(mask, gocv.RetrievalList, gocv.ChainApproxSimple) + numContours := len(contours) + if numContours > d.maxCandidates { + numContours = d.maxCandidates + } + + boxes := make([][][]int, 0, numContours) + for i := 0; i < numContours; i++ { + contour := contours[i] + boundingbox := gocv.MinAreaRect(contour) + if boundingbox.Width < float32(d.minSize) || boundingbox.Height < float32(d.minSize) { + continue + } + points := d.getMinBoxes(boundingbox) + score := d.boxScoreFast(points, pred) + if score < d.boxThresh { + continue + } + + box := d.unClip(points) + if box.Width < float32(d.minSize+2) || box.Height < float32(d.minSize+2) { + continue + } + + cliparray := d.getMinBoxes(box) + dstHeight, dstWidth := pred.Rows(), pred.Cols() + intcliparray := make([][]int, 4) + for i := 0; i < 4; i++ { + p := []int{ + int(float64(clip(int(math.Round( + float64(cliparray[i][0]/float32(width)*float32(dstWidth)))), 0, dstWidth)) / ratioW), + int(float64(clip(int(math.Round( + float64(cliparray[i][1]/float32(height)*float32(dstHeight)))), 0, dstHeight)) / ratioH), + } + intcliparray[i] = p + } + boxes = append(boxes, intcliparray) + } + return boxes +} + +func (d *DBPostProcess) orderPointsClockwise(box [][]int) [][]int { + sort.Sort(xIntSortBy(box)) + leftmost := [][]int{box[0], box[1]} + rightmost := [][]int{box[2], box[3]} + + if leftmost[0][1] > leftmost[1][1] { + leftmost[0], leftmost[1] = leftmost[1], leftmost[0] + } + + if rightmost[0][1] > rightmost[1][1] { + rightmost[0], rightmost[1] = rightmost[1], rightmost[0] + } + + return [][]int{leftmost[0], rightmost[0], rightmost[1], leftmost[1]} +} + +func (d *DBPostProcess) filterTagDetRes(boxes [][][]int, oriH, oriW int) [][][]int { + points := make([][][]int, 0, len(boxes)) + for i := 0; i < len(boxes); i++ { + boxes[i] = d.orderPointsClockwise(boxes[i]) + for j := 0; j < len(boxes[i]); j++ { + boxes[i][j][0] = clip(boxes[i][j][0], 0, oriW-1) + boxes[i][j][1] = clip(boxes[i][j][1], 0, oriH-1) + } + } + + for i := 0; i < len(boxes); i++ { + rectW := int(math.Sqrt(math.Pow(float64(boxes[i][0][0]-boxes[i][1][0]), 2.0) + + math.Pow(float64(boxes[i][0][1]-boxes[i][1][1]), 2.0))) + rectH := int(math.Sqrt(math.Pow(float64(boxes[i][0][0]-boxes[i][3][0]), 2.0) + + math.Pow(float64(boxes[i][0][1]-boxes[i][3][1]), 2.0))) + if rectW <= 4 || rectH <= 4 { + continue + } + points = append(points, boxes[i]) + } + return points +} + +func (d *DBPostProcess) Run(output *paddle.ZeroCopyTensor, oriH, oriW int, ratioH, ratioW float64) [][][]int { + v := output.Value().([][][][]float32) + + shape := output.Shape() + height, width := int(shape[2]), int(shape[3]) + + pred := gocv.NewMatWithSize(height, width, gocv.MatTypeCV32F) + bitmap := gocv.NewMatWithSize(height, width, gocv.MatTypeCV8UC1) + thresh := float32(d.thresh) + for i := 0; i < height; i++ { + for j := 0; j < width; j++ { + pred.SetFloatAt(i, j, v[0][0][i][j]) + if v[0][0][i][j] > thresh { + bitmap.SetUCharAt(i, j, 1) + } else { + bitmap.SetUCharAt(i, j, 0) + } + } + } + + mask := gocv.NewMat() + kernel := gocv.GetStructuringElement(gocv.MorphRect, image.Point{2, 2}) + gocv.Dilate(bitmap, &mask, kernel) + boxes := d.boxesFromBitmap(pred, mask, ratioH, ratioW) + dtboxes := d.filterTagDetRes(boxes, oriH, oriW) + return dtboxes +} diff --git a/deploy/paddleocr-go/ocr/preprocess.go b/deploy/paddleocr-go/ocr/preprocess.go new file mode 100644 index 0000000000000000000000000000000000000000..a0939e76d6b289b7b90759fd1c79695d956afbbc --- /dev/null +++ b/deploy/paddleocr-go/ocr/preprocess.go @@ -0,0 +1,171 @@ +package ocr + +import ( + "image" + "image/color" + "math" + + "github.com/LKKlein/gocv" +) + +func resizeByShape(img gocv.Mat, resizeShape []int) (gocv.Mat, int, int) { + resizeH := resizeShape[0] + resizeW := resizeShape[1] + gocv.Resize(img, &img, image.Pt(resizeW, resizeH), 0, 0, gocv.InterpolationLinear) + return img, resizeH, resizeW +} + +func resizeByMaxLen(img gocv.Mat, maxLen int) (gocv.Mat, int, int) { + oriH := img.Rows() + oriW := img.Cols() + var resizeH, resizeW int = oriH, oriW + + var ratio float64 = 1.0 + if resizeH > maxLen || resizeW > maxLen { + if resizeH > resizeW { + ratio = float64(maxLen) / float64(resizeH) + } else { + ratio = float64(maxLen) / float64(resizeW) + } + } + + resizeH = int(float64(resizeH) * ratio) + resizeW = int(float64(resizeW) * ratio) + + if resizeH%32 == 0 { + resizeH = resizeH + } else if resizeH/32 <= 1 { + resizeH = 32 + } else { + resizeH = (resizeH/32 - 1) * 32 + } + + if resizeW%32 == 0 { + resizeW = resizeW + } else if resizeW/32 <= 1 { + resizeW = 32 + } else { + resizeW = (resizeW/32 - 1) * 32 + } + + if resizeW <= 0 || resizeH <= 0 { + return gocv.NewMat(), 0, 0 + } + + gocv.Resize(img, &img, image.Pt(resizeW, resizeH), 0, 0, gocv.InterpolationLinear) + return img, resizeH, resizeW +} + +func normPermute(img gocv.Mat, mean []float32, std []float32, scaleFactor float32) []float32 { + img.ConvertTo(&img, gocv.MatTypeCV32F) + img.DivideFloat(scaleFactor) + defer img.Close() + + c := gocv.Split(img) + data := make([]float32, img.Rows()*img.Cols()*img.Channels()) + for i := 0; i < 3; i++ { + c[i].SubtractFloat(mean[i]) + c[i].DivideFloat(std[i]) + defer c[i].Close() + x, _ := c[i].DataPtrFloat32() + copy(data[i*img.Rows()*img.Cols():], x) + } + return data +} + +type DetPreProcess interface { + Run(gocv.Mat) ([]float32, int, int) +} + +type DBPreProcess struct { + resizeType int + imageShape []int + maxSideLen int + mean []float32 + std []float32 + scaleFactor float32 +} + +func NewDBProcess(shape []int, sideLen int) *DBPreProcess { + db := &DBPreProcess{ + resizeType: 0, + imageShape: shape, + maxSideLen: sideLen, + mean: []float32{0.485, 0.456, 0.406}, + std: []float32{0.229, 0.224, 0.225}, + scaleFactor: 255.0, + } + if len(shape) > 0 { + db.resizeType = 1 + } + if sideLen == 0 { + db.maxSideLen = 2400 + } + return db +} + +func (d *DBPreProcess) Run(img gocv.Mat) ([]float32, int, int) { + var resizeH, resizeW int + if d.resizeType == 0 { + img, resizeH, resizeW = resizeByMaxLen(img, d.maxSideLen) + } else { + img, resizeH, resizeW = resizeByShape(img, d.imageShape) + } + + im := normPermute(img, d.mean, d.std, d.scaleFactor) + return im, resizeH, resizeW +} + +func clsResize(img gocv.Mat, resizeShape []int) gocv.Mat { + imgH, imgW := resizeShape[1], resizeShape[2] + h, w := img.Rows(), img.Cols() + ratio := float64(w) / float64(h) + var resizeW int + if math.Ceil(float64(imgH)*ratio) > float64(imgW) { + resizeW = imgW + } else { + resizeW = int(math.Ceil(float64(imgH) * ratio)) + } + gocv.Resize(img, &img, image.Pt(resizeW, imgH), 0, 0, gocv.InterpolationLinear) + if resizeW < imgW { + gocv.CopyMakeBorder(img, &img, 0, 0, 0, imgW-resizeW, gocv.BorderConstant, color.RGBA{0, 0, 0, 0}) + } + return img +} + +func crnnPreprocess(img gocv.Mat, resizeShape []int, mean []float32, std []float32, + scaleFactor float32, whRatio float64, charType string) []float32 { + imgH := resizeShape[1] + imgW := resizeShape[2] + if charType == "ch" { + imgW = int(32 * whRatio) + } + h, w := img.Rows(), img.Cols() + ratio := float64(w) / float64(h) + var resizeW int + if math.Ceil(float64(imgH)*ratio) > float64(imgW) { + resizeW = imgW + } else { + resizeW = int(math.Ceil(float64(imgH) * ratio)) + } + gocv.Resize(img, &img, image.Pt(resizeW, imgH), 0, 0, gocv.InterpolationLinear) + + img.ConvertTo(&img, gocv.MatTypeCV32F) + img.DivideFloat(scaleFactor) + img.SubtractScalar(gocv.NewScalar(float64(mean[0]), float64(mean[1]), float64(mean[2]), 0)) + img.DivideScalar(gocv.NewScalar(float64(std[0]), float64(std[1]), float64(std[2]), 0)) + defer img.Close() + + if resizeW < imgW { + gocv.CopyMakeBorder(img, &img, 0, 0, 0, imgW-resizeW, gocv.BorderConstant, color.RGBA{0, 0, 0, 0}) + } + + c := gocv.Split(img) + data := make([]float32, img.Rows()*img.Cols()*img.Channels()) + for i := 0; i < 3; i++ { + defer c[i].Close() + x, _ := c[i].DataPtrFloat32() + copy(data[i*img.Rows()*img.Cols():], x) + } + return data +} diff --git a/deploy/paddleocr-go/ocr/utils.go b/deploy/paddleocr-go/ocr/utils.go new file mode 100644 index 0000000000000000000000000000000000000000..0603d2bba54e9eb9cd744121ca2aaa4df144cee1 --- /dev/null +++ b/deploy/paddleocr-go/ocr/utils.go @@ -0,0 +1,268 @@ +package ocr + +import ( + "archive/tar" + "io" + "io/ioutil" + "log" + "net/http" + "os" + "path" + "path/filepath" + "regexp" + "strings" + + "github.com/LKKlein/gocv" + "gopkg.in/yaml.v3" +) + +func getString(args map[string]interface{}, key string, dv string) string { + if f, ok := args[key]; ok { + return f.(string) + } + return dv +} + +func getFloat64(args map[string]interface{}, key string, dv float64) float64 { + if f, ok := args[key]; ok { + return f.(float64) + } + return dv +} + +func getInt(args map[string]interface{}, key string, dv int) int { + if i, ok := args[key]; ok { + return i.(int) + } + return dv +} + +func getBool(args map[string]interface{}, key string, dv bool) bool { + if b, ok := args[key]; ok { + return b.(bool) + } + return dv +} + +func ReadImage(image_path string) gocv.Mat { + img := gocv.IMRead(image_path, gocv.IMReadColor) + if img.Empty() { + log.Printf("Could not read image %s\n", image_path) + os.Exit(1) + } + return img +} + +func clip(value, min, max int) int { + if value <= min { + return min + } else if value >= max { + return max + } + return value +} + +func minf(data []float32) float32 { + v := data[0] + for _, val := range data { + if val < v { + v = val + } + } + return v +} + +func maxf(data []float32) float32 { + v := data[0] + for _, val := range data { + if val > v { + v = val + } + } + return v +} + +func mini(data []int) int { + v := data[0] + for _, val := range data { + if val < v { + v = val + } + } + return v +} + +func maxi(data []int) int { + v := data[0] + for _, val := range data { + if val > v { + v = val + } + } + return v +} + +func argmax(arr []float32) (int, float32) { + max_value, index := arr[0], 0 + for i, item := range arr { + if item > max_value { + max_value = item + index = i + } + } + return index, max_value +} + +func checkModelExists(modelPath string) bool { + if isPathExist(modelPath+"/model") && isPathExist(modelPath+"/params") { + return true + } + if strings.HasPrefix(modelPath, "http://") || + strings.HasPrefix(modelPath, "ftp://") || strings.HasPrefix(modelPath, "https://") { + return true + } + return false +} + +func downloadFile(filepath, url string) error { + resp, err := http.Get(url) + if err != nil { + return err + } + defer resp.Body.Close() + + out, err := os.Create(filepath) + if err != nil { + return err + } + defer out.Close() + + _, err = io.Copy(out, resp.Body) + log.Println("[download_file] from:", url, " to:", filepath) + return err +} + +func isPathExist(path string) bool { + if _, err := os.Stat(path); err == nil { + return true + } else if os.IsNotExist(err) { + return false + } + return false +} + +func downloadModel(modelDir, modelPath string) (string, error) { + if modelPath != "" && (strings.HasPrefix(modelPath, "http://") || + strings.HasPrefix(modelPath, "ftp://") || strings.HasPrefix(modelPath, "https://")) { + reg := regexp.MustCompile("^(http|https|ftp)://[^/]+/(.+)") + suffix := reg.FindStringSubmatch(modelPath)[2] + outPath := filepath.Join(modelDir, suffix) + outDir := filepath.Dir(outPath) + if !isPathExist(outDir) { + os.MkdirAll(outDir, os.ModePerm) + } + + if !isPathExist(outPath) { + err := downloadFile(outPath, modelPath) + if err != nil { + return "", err + } + } + if strings.HasSuffix(outPath, ".tar") { + _, f := path.Split(suffix) + nextDir := strings.TrimSuffix(f, ".tar") + finalPath := modelDir + "/" + nextDir + if !checkModelExists(finalPath) { + unTar(modelDir, outPath) + } + return finalPath, nil + } + return outPath, nil + } + return modelPath, nil +} + +func unTar(dst, src string) (err error) { + fr, err := os.Open(src) + if err != nil { + return err + } + defer fr.Close() + + tr := tar.NewReader(fr) + for { + hdr, err := tr.Next() + + switch { + case err == io.EOF: + return nil + case err != nil: + return err + case hdr == nil: + continue + } + + dstFileDir := filepath.Join(dst, hdr.Name) + + switch hdr.Typeflag { + case tar.TypeDir: + if b := isPathExist(dstFileDir); !b { + if err := os.MkdirAll(dstFileDir, 0775); err != nil { + return err + } + } + case tar.TypeReg: + file, err := os.OpenFile(dstFileDir, os.O_CREATE|os.O_RDWR, os.FileMode(hdr.Mode)) + if err != nil { + return err + } + _, err2 := io.Copy(file, tr) + if err2 != nil { + return err2 + } + file.Close() + } + } + + return nil +} + +func readLines2StringSlice(path string) []string { + content, err := ioutil.ReadFile(path) + if err != nil { + log.Println("read file error!") + return nil + } + lines := strings.Split(string(content), "\n") + return lines +} + +func ReadYaml(yamlPath string) (map[string]interface{}, error) { + data, err := ioutil.ReadFile(yamlPath) + if err != nil { + return nil, err + } + var body interface{} + if err := yaml.Unmarshal(data, &body); err != nil { + return nil, err + } + + body = convertYaml2Map(body) + return body.(map[string]interface{}), nil +} + +func convertYaml2Map(i interface{}) interface{} { + switch x := i.(type) { + case map[interface{}]interface{}: + m2 := map[string]interface{}{} + for k, v := range x { + m2[k.(string)] = convertYaml2Map(v) + } + return m2 + case []interface{}: + for i, v := range x { + x[i] = convertYaml2Map(v) + } + } + return i +} diff --git a/deploy/paddleocr-go/paddle/common.go b/deploy/paddleocr-go/paddle/common.go new file mode 100644 index 0000000000000000000000000000000000000000..4bcd443cf247f54943e53f7795aa649b1896242f --- /dev/null +++ b/deploy/paddleocr-go/paddle/common.go @@ -0,0 +1,28 @@ +package paddle + +// #cgo CFLAGS: -I../paddle_c/paddle/include +// #cgo LDFLAGS: -L${SRCDIR}/../paddle_c/paddle/lib -Wl,-rpath=\$ORIGIN/paddle_c/paddle/lib -lpaddle_fluid_c +// #include +// #include "paddle_c_api.h" +import "C" +import "fmt" + +func ConvertCBooleanToGo(b C.bool) bool { + var c_false C.bool + if b != c_false { + return true + } + return false +} + +func numel(shape []int32) int32 { + n := int32(1) + for _, d := range shape { + n *= d + } + return n +} + +func bug(format string, args ...interface{}) error { + return fmt.Errorf("Bug %v", fmt.Sprintf(format, args...)) +} diff --git a/deploy/paddleocr-go/paddle/config.go b/deploy/paddleocr-go/paddle/config.go new file mode 100644 index 0000000000000000000000000000000000000000..3201923936dca57aa809a058a76e34d00790057d --- /dev/null +++ b/deploy/paddleocr-go/paddle/config.go @@ -0,0 +1,183 @@ +package paddle + +// #cgo CFLAGS: -I../paddle_c/paddle/include +// #cgo LDFLAGS: -L${SRCDIR}/../paddle_c/paddle/lib -Wl,-rpath,$ORIGIN/paddle_c/paddle/lib -lpaddle_fluid_c +// #include +// #include +// #include +import "C" + +import ( + "runtime" + "unsafe" +) + +type Precision C.Precision + +const ( + Precision_FLOAT32 Precision = C.kFloat32 + Precision_INT8 Precision = C.kInt8 + Precision_HALF Precision = C.kHalf +) + +type AnalysisConfig struct { + c *C.PD_AnalysisConfig +} + +func NewAnalysisConfig() *AnalysisConfig { + c_config := C.PD_NewAnalysisConfig() + config := &AnalysisConfig{c: c_config} + runtime.SetFinalizer(config, (*AnalysisConfig).finalize) + return config +} + +func (config *AnalysisConfig) finalize() { + C.PD_DeleteAnalysisConfig(config.c) +} + +func (config *AnalysisConfig) SetModel(model, params string) { + c_model := C.CString(model) + defer C.free(unsafe.Pointer(c_model)) + var c_params *C.char + if params == "" { + c_params = nil + } else { + c_params = C.CString(params) + defer C.free(unsafe.Pointer(c_params)) + } + + C.PD_SetModel(config.c, c_model, c_params) +} + +func (config *AnalysisConfig) ModelDir() string { + return C.GoString(C.PD_ModelDir(config.c)) +} + +func (config *AnalysisConfig) ProgFile() string { + return C.GoString(C.PD_ProgFile(config.c)) +} + +func (config *AnalysisConfig) ParamsFile() string { + return C.GoString(C.PD_ParamsFile(config.c)) +} + +func (config *AnalysisConfig) EnableUseGpu(memory_pool_init_size_mb int, device_id int) { + C.PD_EnableUseGpu(config.c, C.int(memory_pool_init_size_mb), C.int(device_id)) +} + +func (config *AnalysisConfig) DisableGpu() { + C.PD_DisableGpu(config.c) +} + +func (config *AnalysisConfig) UseGpu() bool { + return ConvertCBooleanToGo(C.PD_UseGpu(config.c)) +} + +func (config *AnalysisConfig) GpuDeviceId() int { + return int(C.PD_GpuDeviceId(config.c)) +} + +func (config *AnalysisConfig) MemoryPoolInitSizeMb() int { + return int(C.PD_MemoryPoolInitSizeMb(config.c)) +} + +func (config *AnalysisConfig) EnableCudnn() { + C.PD_EnableCUDNN(config.c) +} + +func (config *AnalysisConfig) CudnnEnabled() bool { + return ConvertCBooleanToGo(C.PD_CudnnEnabled(config.c)) +} + +func (config *AnalysisConfig) SwitchIrOptim(x bool) { + C.PD_SwitchIrOptim(config.c, C.bool(x)) +} + +func (config *AnalysisConfig) IrOptim() bool { + return ConvertCBooleanToGo(C.PD_IrOptim(config.c)) +} + +func (config *AnalysisConfig) SwitchUseFeedFetchOps(x bool) { + C.PD_SwitchUseFeedFetchOps(config.c, C.bool(x)) +} + +func (config *AnalysisConfig) UseFeedFetchOpsEnabled() bool { + return ConvertCBooleanToGo(C.PD_UseFeedFetchOpsEnabled(config.c)) +} + +func (config *AnalysisConfig) SwitchSpecifyInputNames(x bool) { + C.PD_SwitchSpecifyInputNames(config.c, C.bool(x)) +} + +func (config *AnalysisConfig) SpecifyInputName() bool { + return ConvertCBooleanToGo(C.PD_SpecifyInputName(config.c)) +} + +func (config *AnalysisConfig) EnableTensorRtEngine(workspace_size int, max_batch_size int, min_subgraph_size int, precision Precision, use_static bool, use_calib_mode bool) { + C.PD_EnableTensorRtEngine(config.c, C.int(workspace_size), C.int(max_batch_size), C.int(min_subgraph_size), C.Precision(precision), C.bool(use_static), C.bool(use_calib_mode)) +} + +func (config *AnalysisConfig) TensorrtEngineEnabled() bool { + return ConvertCBooleanToGo(C.PD_TensorrtEngineEnabled(config.c)) +} + +func (config *AnalysisConfig) SwitchIrDebug(x bool) { + C.PD_SwitchIrDebug(config.c, C.bool(x)) +} + +func (config *AnalysisConfig) EnableMkldnn() { + C.PD_EnableMKLDNN(config.c) +} + +func (config *AnalysisConfig) SetCpuMathLibraryNumThreads(n int) { + C.PD_SetCpuMathLibraryNumThreads(config.c, C.int(n)) +} + +func (config *AnalysisConfig) CpuMathLibraryNumThreads() int { + return int(C.PD_CpuMathLibraryNumThreads(config.c)) +} + +func (config *AnalysisConfig) EnableMkldnnQuantizer() { + C.PD_EnableMkldnnQuantizer(config.c) +} + +func (config *AnalysisConfig) MkldnnQuantizerEnabled() bool { + return ConvertCBooleanToGo(C.PD_MkldnnQuantizerEnabled(config.c)) +} + +// SetModelBuffer +// ModelFromMemory + +func (config *AnalysisConfig) EnableMemoryOptim() { + C.PD_EnableMemoryOptim(config.c) +} + +func (config *AnalysisConfig) MemoryOptimEnabled() bool { + return ConvertCBooleanToGo(C.PD_MemoryOptimEnabled(config.c)) +} + +func (config *AnalysisConfig) EnableProfile() { + C.PD_EnableProfile(config.c) +} + +func (config *AnalysisConfig) ProfileEnabled() bool { + return ConvertCBooleanToGo(C.PD_ProfileEnabled(config.c)) +} + +func (config *AnalysisConfig) DisableGlogInfo() { + C.PD_DisableGlogInfo(config.c) +} + +func (config *AnalysisConfig) DeletePass(pass string) { + c_pass := C.CString(pass) + defer C.free(unsafe.Pointer(c_pass)) + C.PD_DeletePass(config.c, c_pass) +} + +func (config *AnalysisConfig) SetInValid() { + C.PD_SetInValid(config.c) +} + +func (config *AnalysisConfig) IsValid() bool { + return ConvertCBooleanToGo(C.PD_IsValid(config.c)) +} diff --git a/deploy/paddleocr-go/paddle/predictor.go b/deploy/paddleocr-go/paddle/predictor.go new file mode 100644 index 0000000000000000000000000000000000000000..f6cba7bc7756aab7f68cb5f84be1fae659c5f61c --- /dev/null +++ b/deploy/paddleocr-go/paddle/predictor.go @@ -0,0 +1,103 @@ +package paddle + +// #cgo CFLAGS: -I../paddle_c/paddle/include +// #cgo LDFLAGS: -L${SRCDIR}/../paddle_c/paddle/lib -Wl,-rpath,$ORIGIN/paddle_c/paddle/lib -lpaddle_fluid_c +// #include +// #include "paddle_c_api.h" +import "C" + +import ( + "reflect" + "runtime" + "unsafe" +) + +type Predictor struct { + c *C.PD_Predictor +} + +func NewPredictor(config *AnalysisConfig) *Predictor { + c_predictor := C.PD_NewPredictor((*config).c) + predictor := &Predictor{c: c_predictor} + runtime.SetFinalizer(predictor, (*Predictor).finalize) + return predictor +} + +func (predictor *Predictor) finalize() { + C.PD_DeletePredictor(predictor.c) +} + +func DeletePredictor(predictor *Predictor) { + C.PD_DeletePredictor(predictor.c) +} + +func (predictor *Predictor) GetInputNum() int { + return int(C.PD_GetInputNum(predictor.c)) +} + +func (predictor *Predictor) GetOutputNum() int { + return int(C.PD_GetOutputNum(predictor.c)) +} + +func (predictor *Predictor) GetInputName(n int) string { + return C.GoString(C.PD_GetInputName(predictor.c, C.int(n))) +} + +func (predictor *Predictor) GetOutputName(n int) string { + return C.GoString(C.PD_GetOutputName(predictor.c, C.int(n))) +} + +func (predictor *Predictor) GetInputTensors() [](*ZeroCopyTensor) { + var result [](*ZeroCopyTensor) + for i := 0; i < predictor.GetInputNum(); i++ { + tensor := NewZeroCopyTensor() + tensor.c.name = C.PD_GetInputName(predictor.c, C.int(i)) + result = append(result, tensor) + } + return result +} + +func (predictor *Predictor) GetOutputTensors() [](*ZeroCopyTensor) { + var result [](*ZeroCopyTensor) + for i := 0; i < predictor.GetOutputNum(); i++ { + tensor := NewZeroCopyTensor() + tensor.c.name = C.PD_GetOutputName(predictor.c, C.int(i)) + result = append(result, tensor) + } + return result +} + +func (predictor *Predictor) GetInputNames() []string { + names := make([]string, predictor.GetInputNum()) + for i := 0; i < len(names); i++ { + names[i] = predictor.GetInputName(i) + } + return names +} + +func (predictor *Predictor) GetOutputNames() []string { + names := make([]string, predictor.GetOutputNum()) + for i := 0; i < len(names); i++ { + names[i] = predictor.GetOutputName(i) + } + return names +} + +func (predictor *Predictor) SetZeroCopyInput(tensor *ZeroCopyTensor) { + C.PD_SetZeroCopyInput(predictor.c, tensor.c) +} + +func (predictor *Predictor) GetZeroCopyOutput(tensor *ZeroCopyTensor) { + C.PD_GetZeroCopyOutput(predictor.c, tensor.c) + tensor.name = C.GoString(tensor.c.name) + var shape []int32 + shape_hdr := (*reflect.SliceHeader)(unsafe.Pointer(&shape)) + shape_hdr.Data = uintptr(unsafe.Pointer(tensor.c.shape.data)) + shape_hdr.Len = int(tensor.c.shape.length / C.sizeof_int) + shape_hdr.Cap = int(tensor.c.shape.length / C.sizeof_int) + tensor.Reshape(shape) +} + +func (predictor *Predictor) ZeroCopyRun() { + C.PD_ZeroCopyRun(predictor.c) +} diff --git a/deploy/paddleocr-go/paddle/tensor.go b/deploy/paddleocr-go/paddle/tensor.go new file mode 100644 index 0000000000000000000000000000000000000000..cf462dcd886861f23ab504569662456d86db9107 --- /dev/null +++ b/deploy/paddleocr-go/paddle/tensor.go @@ -0,0 +1,249 @@ +package paddle + +// #cgo CFLAGS: -I../paddle_c/paddle/include +// #cgo LDFLAGS: -L${SRCDIR}/../paddle_c/paddle/lib -Wl,-rpath,$ORIGIN/paddle_c/paddle/lib -lpaddle_fluid_c +// #include +// #include +// #include +// #include +import "C" + +import ( + "bytes" + "encoding/binary" + "reflect" + "runtime" + "unsafe" +) + +type PaddleDType C.PD_DataType + +const ( + FLOAT32 PaddleDType = C.PD_FLOAT32 + INT32 PaddleDType = C.PD_INT32 + INT64 PaddleDType = C.PD_INT64 + UINT8 PaddleDType = C.PD_UINT8 + UNKDTYPE PaddleDType = C.PD_UNKDTYPE +) + +var types = []struct { + gotype reflect.Type + dtype PaddleDType +}{ + {reflect.TypeOf(float32(0)), FLOAT32}, + {reflect.TypeOf(int32(0)), INT32}, + {reflect.TypeOf(int64(0)), INT64}, + {reflect.TypeOf(uint8(0)), UINT8}, +} + +func TypeOfShape(dtype PaddleDType, shape []int32) reflect.Type { + var ret reflect.Type + for _, t := range types { + if dtype == PaddleDType(t.dtype) { + ret = t.gotype + break + } + } + + if ret == nil { + panic(bug("Data %v type is not support", dtype)) + } + + for range shape { + ret = reflect.SliceOf(ret) + } + return ret +} + +type ZeroCopyTensor struct { + c *C.PD_ZeroCopyTensor + name string + shape []int32 +} + +func NewZeroCopyTensor() *ZeroCopyTensor { + c_tensor := C.PD_NewZeroCopyTensor() + + tensor := &ZeroCopyTensor{c: c_tensor} + runtime.SetFinalizer(tensor, (*ZeroCopyTensor).finalize) + return tensor +} + +func (tensor *ZeroCopyTensor) finalize() { + C.PD_DeleteZeroCopyTensor(tensor.c) +} + +func (tensor *ZeroCopyTensor) Shape() []int32 { + return tensor.shape +} + +func (tensor *ZeroCopyTensor) Name() string { + return C.GoString(tensor.c.name) +} + +func (tensor *ZeroCopyTensor) Rename(name string) { + tensor.name = name + tensor.c.name = (*C.char)(unsafe.Pointer(tensor.c.name)) + //tensor.c.name = C.CString(tensor.name) + //defer C.free(unsafe.Pointer(tensor.c.name)) +} + +func (tensor *ZeroCopyTensor) Reshape(shape []int32) { + tensor.shape = make([]int32, len(shape)) + copy(tensor.shape, shape) + length := C.sizeof_int * C.size_t(len(shape)) + if tensor.c.shape.capacity < C.size_t(length) { + if tensor.c.shape.capacity != C.size_t(0) { + C.free(tensor.c.shape.data) + } + tensor.c.shape.data = C.malloc(length) + tensor.c.shape.capacity = length + } + tensor.c.shape.length = length + C.memcpy(tensor.c.shape.data, unsafe.Pointer(&shape[0]), length) +} + +func (tensor *ZeroCopyTensor) DataType() PaddleDType { + return PaddleDType(tensor.c.dtype) +} + +func (tensor *ZeroCopyTensor) SetValue(value interface{}) { + val := reflect.ValueOf(value) + shape, dtype := ShapeAndTypeOf(val) + num := numel(shape) + length := C.size_t(SizeofDataType(dtype) * num) + if tensor.c.data.capacity < length { + if tensor.c.data.capacity != C.size_t(0) { + C.free(tensor.c.data.data) + } + tensor.c.data.data = C.malloc(length) + tensor.c.data.capacity = length + } + tensor.c.data.length = length + + switch dtype { + case PaddleDType(UINT8): + data := val.Interface().([]uint8) + C.memcpy(tensor.c.data.data, unsafe.Pointer(&data[0]), length) + case PaddleDType(INT32): + data := val.Interface().([]int32) + C.memcpy(tensor.c.data.data, unsafe.Pointer(&data[0]), length) + case PaddleDType(INT64): + data := val.Interface().([]int64) + C.memcpy(tensor.c.data.data, unsafe.Pointer(&data[0]), length) + case PaddleDType(FLOAT32): + data := val.Interface().([]float32) + C.memcpy(tensor.c.data.data, unsafe.Pointer(&data[0]), length) + } + tensor.c.dtype = C.PD_DataType(dtype) +} + +func TypeOf(dtype PaddleDType, shape []int32) reflect.Type { + var ret reflect.Type + for _, t := range types { + if t.dtype == dtype { + ret = t.gotype + break + } + } + + for range shape { + ret = reflect.SliceOf(ret) + } + return ret +} + +func (tensor *ZeroCopyTensor) Value() interface{} { + t := TypeOf(PaddleDType(tensor.c.dtype), tensor.shape) + value := reflect.New(t) + c_bytes := tensor.c.data.data + length := tensor.c.data.length + var slice []byte + if unsafe.Sizeof(unsafe.Pointer(nil)) == 8 { + slice = (*[1<<50 - 1]byte)(unsafe.Pointer(c_bytes))[:length:length] + } else { + slice = (*[1 << 30]byte)(unsafe.Pointer(c_bytes))[:length:length] + } + r := bytes.NewReader(slice) + DecodeTensor(r, tensor.Shape(), t, value) + return reflect.Indirect(value).Interface() +} + +func (tensor *ZeroCopyTensor) Lod() []uint { + var val []uint + valHdr := (*reflect.SliceHeader)(unsafe.Pointer(&val)) + valHdr.Data = uintptr(unsafe.Pointer(tensor.c.lod.data)) + valHdr.Len = int(tensor.c.lod.length / C.sizeof_size_t) + valHdr.Cap = int(tensor.c.lod.length / C.sizeof_size_t) + return val +} + +func Endian() binary.ByteOrder { + buf := [2]byte{} + *(*uint16)(unsafe.Pointer(&buf[0])) = uint16(0xABCD) + + var endian binary.ByteOrder + + switch buf { + case [2]byte{0xCD, 0xAB}: + endian = binary.LittleEndian + case [2]byte{0xAB, 0xCD}: + endian = binary.BigEndian + default: + panic("Could not determine native endianness.") + } + return endian +} + +func DecodeTensor(r *bytes.Reader, shape []int32, t reflect.Type, ptr reflect.Value) { + switch t.Kind() { + case reflect.Uint8, reflect.Int32, reflect.Int64, reflect.Float32: + binary.Read(r, Endian(), ptr.Interface()) + case reflect.Slice: + value := reflect.Indirect(ptr) + value.Set(reflect.MakeSlice(t, int(shape[0]), int(shape[0]))) + if len(shape) == 1 && value.Len() > 0 { + switch value.Index(0).Kind() { + case reflect.Uint8, reflect.Int32, reflect.Int64, reflect.Float32: + binary.Read(r, Endian(), value.Interface()) + return + } + } + + for i := 0; i < value.Len(); i++ { + DecodeTensor(r, shape[1:], t.Elem(), value.Index(i).Addr()) + } + } +} + +func SizeofDataType(dtype PaddleDType) int32 { + switch dtype { + case UINT8: + return int32(C.sizeof_uchar) + case INT32: + return int32(C.sizeof_int) + case INT64: + return int32(C.sizeof_longlong) + case FLOAT32: + return int32(C.sizeof_float) + } + return -1 +} + +func ShapeAndTypeOf(val reflect.Value) (shape []int32, dt PaddleDType) { + gotype := val.Type() + for gotype.Kind() == reflect.Array || gotype.Kind() == reflect.Slice { + shape = append(shape, int32(val.Len())) + if val.Len() > 0 { + val = val.Index(0) + } + gotype = gotype.Elem() + } + + for _, t := range types { + if gotype.Kind() == t.gotype.Kind() { + return shape, PaddleDType(t.dtype) + } + } + return shape, dt +} diff --git a/deploy/paddleocr-go/paddle_c/README.md b/deploy/paddleocr-go/paddle_c/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e3565d6fbd54d3d3f39f6b75eac100f666d42f00 --- /dev/null +++ b/deploy/paddleocr-go/paddle_c/README.md @@ -0,0 +1,6 @@ +# Paddle C预测库目录 + +## 编译安装 +使用cmake编译paddle，并打开-DON_INFER=ON，在编译目录下得到paddle_inference_c_install_dir,将该目录下的所有文件复制到本目录下。 + +详细编译步骤请参见[README.md](../README.md) 或者官方文档指导 https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html#id12 \ No newline at end of file