FastDeploy

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Installation

Prerequisites

• CUDA >= 11.2 、cuDNN >= 8.0 、 Python >= 3.6
• OS: Linux x86_64/macOS/Windows 10

Install FastDeploy SDK with both CPU and GPU support

pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html

Conda Installation (Recommended)

conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2

Install FastDeploy SDK with only CPU support

pip install fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html

Python Inference Example

• Prepare model and picture

wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
tar xvf ppyoloe_crn_l_300e_coco.tgz
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg

• Test inference results

# For deployment of GPU/TensorRT, please refer to examples/vision/detection/paddledetection/python
import cv2
import fastdeploy.vision as vision

im = cv2.imread("000000014439.jpg")
model = vision.detection.PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
                                 "ppyoloe_crn_l_300e_coco/model.pdiparams",
                                 "ppyoloe_crn_l_300e_coco/infer_cfg.yml")

result = model.predict(im)
print(result)

vis_im = vision.vis_detection(im, result, score_threshold=0.5)
cv2.imwrite("vis_image.jpg", vis_im)

Installation

• Please refer to C++ Prebuilt Libraries Download

C++ Inference Example

• Prepare models and pictures

wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
tar xvf ppyoloe_crn_l_300e_coco.tgz
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg

• Test inference results

// For GPU/TensorRT deployment, please refer to examples/vision/detection/paddledetection/cpp
#include "fastdeploy/vision.h"

int main(int argc, char* argv[]) {
  namespace vision = fastdeploy::vision;
  auto im = cv::imread("000000014439.jpg");
  auto model = vision::detection::PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel",
                                          "ppyoloe_crn_l_300e_coco/model.pdiparams",
                                          "ppyoloe_crn_l_300e_coco/infer_cfg.yml");

  vision::DetectionResult res;
  model.Predict(&im, &res);

  auto vis_im = vision::VisDetection(im, res, 0.5);
  cv::imwrite("vis_image.jpg", vis_im);
  return 0;
 }