Yolo-Fastest

C LINK

⚡ Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB

:zap:Yolo-Fastest:zap:

• Simple, fast, compact, easy to transplant
• A real-time target detection algorithm for all platforms
• The fastest and smallest known universal target detection algorithm based on yolo
• Optimized design for ARM mobile terminal, optimized to support NCNN reasoning framework
• The speed is 45% faster than mobilenetv2-yolov3-nano, and the parameter amount is reduced by 56%

Evaluating indicator

• Test platform Kirin 990 CPU，Based on NCNN
• Suitable for hardware with extremely tight computing resources
• This model is recommended to do some simple single object detection suitable for simple application scenarios

  Compile

  How to compile on Linux

• This repo is based on Darknet project so the instructions for compiling the project are same (https://github.com/MuhammadAsadJaved/darknet#how-to-compile-on-windows-legacy-way)

Just do make in the Yolo-Fastest-master directory. Before make, you can set such options in the Makefile: link

• GPU=1 to build with CUDA to accelerate by using GPU (CUDA should be in /usr/local/cuda)
• CUDNN=1 to build with cuDNN v5-v7 to accelerate training by using GPU (cuDNN should be in /usr/local/cudnn)
• CUDNN_HALF=1 to build for Tensor Cores (on Titan V / Tesla V100 / DGX-2 and later) speedup Detection 3x, Training 2x
• OPENCV=1 to build with OpenCV 4.x/3.x/2.4.x - allows to detect on video files and video streams from network cameras or web-cams
• Set the other options in the Makefile according to your need.

Test/Demo

*Run Yolo-Fastest , Yolo-Fastest-x1 , Yolov3 or Yolov4 on image or video inputs

Demo on image input

*Note: change .data , .cfg , .weights and input image file in image_yolov3.sh for Yolo-Fastest-x1, Yolov3 and Yolov4

  sh image_yolov3.sh

Demo on video input

*Note: Use any input video and place in the data folder or use 0 in the video_yolov3.sh for webcam

*Note: change .data , .cfg , .weights and input video file in video_yolov3.sh for Yolo-Fastest-x1, Yolov3 and Yolov4

  sh video_yolov3.sh

How to Train

Generate a pre-trained model for the initialization of the model backbone

  ./darknet partial yolo-fastest.cfg yolo-fastest.weights yolo-fastest.conv.109 109

Train

• 交流qq群:1062122604
• https://github.com/AlexeyAB/darknet

  ./darknet detector train voc.data yolo-fastest.cfg yolo-fastest.conv.109 
  

  Thanks

• https://github.com/AlexeyAB/darknet
• https://github.com/Tencent/ncnn