FastDeploy/examples/vision/generation/anemigan/cpp

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AnimeGAN C++ Deployment Example

This directory provides examples that infer.cc fast finishes the deployment of AnimeGAN on CPU/GPU.

Two steps before deployment

• 1. Software and hardware should meet the requirements. Please refer to FastDeploy Environment Requirements
• 2. Download the precompiled deployment library and samples code according to your development environment. Refer to FastDeploy Precompiled Library

Taking the AnimeGAN inference on Linux as an example, the compilation test can be completed by executing the following command in this directory. FastDeploy version 1.0.2 or above (x.x.x>=1.0.2) is required to support this model.

mkdir build
cd build
# Download the FastDeploy precompiled library. Users can choose your appropriate version in the `FastDeploy Precompiled Library` mentioned above 
wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
tar xvf fastdeploy-linux-x64-x.x.x.tgz
cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
make -j

# Download the prepared model files and test images 
wget https://bj.bcebos.com/paddlehub/fastdeploy/style_transfer_testimg.jpg
wget https://bj.bcebos.com/paddlehub/fastdeploy/animegan_v1_hayao_60_v1.0.0.tgz
tar xvfz animegan_v1_hayao_60_v1.0.0.tgz

# CPU inference
./infer_demo --model animegan_v1_hayao_60 --image style_transfer_testimg.jpg  --device cpu
# GPU inference
./infer_demo --model animegan_v1_hayao_60 --image style_transfer_testimg.jpg  --device gpu

The above command works for Linux or MacOS. For SDK in Windows, refer to

• How to use FastDeploy C++ SDK in Windows

AnimeGAN C++ Interface

AnimeGAN Class

fastdeploy::vision::generation::AnimeGAN(
        const string& model_file,
        const string& params_file = "",
        const RuntimeOption& runtime_option = RuntimeOption(),
        const ModelFormat& model_format = ModelFormat::PADDLE)

AnimeGAN model loading and initialization, among which model_file is the exported Paddle model file and params_file is the parameter file.

Parameter

• model_file(str): Model file path
• params_file(str): Parameter file path
• runtime_option(RuntimeOption): Backend Inference configuration. None by default. (use the default configuration)
• model_format(ModelFormat): Model format. Paddle format by default

Predict Function

bool AnimeGAN::Predict(cv::Mat& image, cv::Mat* result)

Model prediction interface. Input an image and output the style transfer result

Parameter

• image: Input data in HWC or BGR format
• result: Image after style style transfer in BGR format

BatchPredict Function

bool AnimeGAN::BatchPredict(const std::vector<cv::Mat>& images, std::vector<cv::Mat>* results);

Model prediction interface. Input a set of images and output style transfer results.

Parameter

• images: Input data in HWC or BGR format
• results: A set of images after style transfer in BGR format.

• Model Description
• Python Deployment
• How to switch the model inference backend engine