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struct Offering {
  void *doc;
  void *code;
  void *paper;
  void *cv;
  void *ppt;
  void *question;
};

Project * getExcellentOpenSource(CodeWorld *w) {
  
  if (your.interest) {
    if (email("[email protected]") || submit(issue)) {
      return getYourExcellentOpenSource();
    }
  }
  return top(w->star) == NULL ? top(w->fork) : top(w->star);
}

struct Offering * produce(Project *p) {

  Offering *o = malloc(sizeof(struct Offering));
  o->doc = arrangeDocument(p);
  o->code = produceExampleCode(p);
  o->cv = produceVideo(p);
  o->paper = arrangePaper(p);// https://cvpr.thecvf.com/
  o->ppt = arrangePPTpdf(p);
  o->question = arrangeQuestionList(p);
  
  return o;
}

void produceRepo(struct Offering *o) {
  setRepoOrgAutoXCar(o); 
  free(o);
}

int main() {
  CodeWorld world;  // network, OS,computer vision etc. (code with c/c++)
  
#pragma omp parallel num_threads(worker_nums)  
  {
    while(1) {
      Project *p = getExcellentOpenSource(world);
      //Project: slam, cv, cuda, openmp, bev, ros etc.
      struct Offering *o = produce(p);
      produceRepo(o);
    }
  }
}

Phoenix's Projects

how_to_optimize_in_gpu- icon how_to_optimize_in_gpu-

This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.

orb_slam2- icon orb_slam2-

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

pcl-learning icon pcl-learning

🚀🚀🚀🚀PCL(Point Cloud Library)点云库学习记录

pytorch-mnist-celeba-gan-dcgan icon pytorch-mnist-celeba-gan-dcgan

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

stereoalgorithms- icon stereoalgorithms-

Stereo Algorithms (Include:CREStereo,RAFT-Stereo,Hitnet,FastACVNet_plus,Stereo Transformers,RealtimeStereo,DistDepth) with TensorRT,ORT,OpenVINO

tensorrt icon tensorrt

NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.

tensorrt_starter icon tensorrt_starter

This repository give a guidline to learn CUDA and TensorRT from the beginning.

yolov5xxx icon yolov5xxx

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

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