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| ## Model Zoo | |
| | Model | Test Size | AP<sup>val</sup> | AP<sub>50</sub><sup>val</sup> | AP<sub>75</sub><sup>val</sup> | AP<sub>S</sub><sup>val</sup> | AP<sub>M</sub><sup>val</sup> | AP<sub>L</sub><sup>val</sup> | batch1 throughput | | |
| | :-- | :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | | |
| | **YOLOv4-CSP** | 640 | **49.1%** | **67.7%** | **53.8%** | **32.1%** | **54.4%** | **63.2%** | 76 *fps* | | |
| | **YOLOR-CSP** | 640 | **49.2%** | **67.6%** | **53.7%** | **32.9%** | **54.4%** | **63.0%** | - | | |
| | | | | | | | | | |
| | **YOLOv4-CSP-X** | 640 | **50.9%** | **69.3%** | **55.4%** | **35.3%** | **55.8%** | **64.8%** | 53 *fps* | | |
| | **YOLOR-CSP-X** | 640 | **51.1%** | **69.6%** | **55.7%** | **35.7%** | **56.0%** | **65.2%** | - | | |
| | | | | | | | | | |
| ## Installation | |
| https://github.com/AlexeyAB/darknet | |
| Docker environment (recommended) | |
| <details><summary> <b>Expand</b> </summary> | |
| ``` | |
| # get code | |
| git clone https://github.com/AlexeyAB/darknet | |
| # create the docker container, you can change the share memory size if you have more. | |
| nvidia-docker run --name yolor -it -v your_coco_path/:/coco/ -v your_code_path/:/yolor --shm-size=64g nvcr.io/nvidia/pytorch:21.02-py3 | |
| # apt install required packages | |
| apt update | |
| apt install -y libopencv-dev | |
| # edit Makefile | |
| #GPU=1 | |
| #CUDNN=1 | |
| #CUDNN_HALF=1 | |
| #OPENCV=1 | |
| #AVX=1 | |
| #OPENMP=1 | |
| #LIBSO=1 | |
| #ZED_CAMERA=0 | |
| #ZED_CAMERA_v2_8=0 | |
| # | |
| #USE_CPP=0 | |
| #DEBUG=0 | |
| # | |
| #ARCH= -gencode arch=compute_52,code=[sm_70,compute_70] \ | |
| # -gencode arch=compute_61,code=[sm_75,compute_75] \ | |
| # -gencode arch=compute_61,code=[sm_80,compute_80] \ | |
| # -gencode arch=compute_61,code=[sm_86,compute_86] | |
| # | |
| #... | |
| # build | |
| make -j8 | |
| ``` | |
| </details> | |
| ## Testing | |
| To reproduce inference speed, using: | |
| ``` | |
| CUDA_VISIBLE_DEVICES=0 ./darknet detector demo cfg/coco.data cfg/yolov4-csp.cfg weights/yolov4-csp.weights source/test.mp4 -dont_show -benchmark | |
| ``` | |