#!/usr/bin/env bash # New VM rm -rf sample_data yolov3 darknet apex coco cocoapi knife knifec git clone https://github.com/ultralytics/yolov3 git clone https://github.com/NVIDIA/apex && cd apex && pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" . --user && cd .. && rm -rf apex sudo conda install -yc conda-forge scikit-image pycocotools python3 -c " from yolov3.utils.google_utils import gdrive_download gdrive_download('1WQT6SOktSe8Uw6r10-2JhbEhMY5DJaph','coco.zip')" sudo shutdown # Re-clone rm -rf yolov3 # Warning: remove existing git clone https://github.com/ultralytics/yolov3 && cd yolov3 # master # git clone -b test --depth 1 https://github.com/ultralytics/yolov3 test # branch python3 train.py --img-size 320 --weights weights/darknet53.conv.74 --epochs 27 --batch-size 64 --accumulate 1 # Train python3 train.py # Resume python3 train.py --resume # Detect python3 detect.py # Test python3 test.py --save-json # Evolve export t=ultralytics/yolov3:v0 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t clear sleep 200 while true do python3 train.py --data data/coco.data --img-size 416 --epochs 27 --batch-size 32 --accumulate 2 --evolve --weights '' --prebias --bucket yolov4/416_coco_27e --device 7 done # Git pull git pull https://github.com/ultralytics/yolov3 # master git pull https://github.com/ultralytics/yolov3 test # branch # Test Darknet training python3 test.py --weights ../darknet/backup/yolov3.backup # Copy last.pt TO bucket gsutil cp yolov3/weights/last1gpu.pt gs://ultralytics # Copy last.pt FROM bucket gsutil cp gs://ultralytics/last.pt yolov3/weights/last.pt wget https://storage.googleapis.com/ultralytics/yolov3/last_v1_0.pt -O weights/last_v1_0.pt wget https://storage.googleapis.com/ultralytics/yolov3/best_v1_0.pt -O weights/best_v1_0.pt # Reproduce tutorials rm results*.txt # WARNING: removes existing results python3 train.py --nosave --data data/coco_1img.data && mv results.txt results0r_1img.txt python3 train.py --nosave --data data/coco_10img.data && mv results.txt results0r_10img.txt python3 train.py --nosave --data data/coco_100img.data && mv results.txt results0r_100img.txt # python3 train.py --nosave --data data/coco_100img.data --transfer && mv results.txt results3_100imgTL.txt python3 -c "from utils import utils; utils.plot_results()" # gsutil cp results*.txt gs://ultralytics gsutil cp results.png gs://ultralytics sudo shutdown # Reproduce mAP python3 test.py --save-json --img-size 608 python3 test.py --save-json --img-size 416 python3 test.py --save-json --img-size 320 sudo shutdown # Benchmark script git clone https://github.com/ultralytics/yolov3 # clone our repo git clone https://github.com/NVIDIA/apex && cd apex && pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" . --user && cd .. && rm -rf apex # install nvidia apex python3 -c "from yolov3.utils.google_utils import gdrive_download; gdrive_download('1HaXkef9z6y5l4vUnCYgdmEAj61c6bfWO','coco.zip')" # download coco dataset (20GB) cd yolov3 && clear && python3 train.py --epochs 1 # run benchmark (~30 min) # Unit tests python3 detect.py # detect 2 persons, 1 tie python3 test.py --data data/coco_32img.data # test mAP = 0.8 python3 train.py --data data/coco_32img.data --epochs 5 --nosave # train 5 epochs python3 train.py --data data/coco_1cls.data --epochs 5 --nosave # train 5 epochs python3 train.py --data data/coco_1img.data --epochs 5 --nosave # train 5 epochs # AlexyAB Darknet gsutil cp -r gs://sm6/supermarket2 . # dataset from bucket rm -rf darknet && git clone https://github.com/AlexeyAB/darknet && cd darknet && wget -c https://pjreddie.com/media/files/darknet53.conv.74 # sudo apt install libopencv-dev && make ./darknet detector calc_anchors data/coco_img64.data -num_of_clusters 9 -width 320 -height 320 # kmeans anchor calculation ./darknet detector train ../supermarket2/supermarket2.data ../yolo_v3_spp_pan_scale.cfg darknet53.conv.74 -map -dont_show # train spp ./darknet detector train ../yolov3/data/coco.data ../yolov3-spp.cfg darknet53.conv.74 -map -dont_show # train spp coco #Docker sudo docker kill "$(sudo docker ps -q)" sudo docker pull ultralytics/yolov3:v0 sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco ultralytics/yolov3:v0 export t=ultralytics/yolov3:v70 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 70 --device 0 --multi export t=ultralytics/yolov3:v0 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 71 --device 0 --multi --img-weights export t=ultralytics/yolov3:v73 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 73 --device 5 --cfg cfg/yolov3s.cfg export t=ultralytics/yolov3:v74 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 74 --device 0 --cfg cfg/yolov3s.cfg export t=ultralytics/yolov3:v75 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 75 --device 7 --cfg cfg/yolov3s.cfg export t=ultralytics/yolov3:v76 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 76 --device 0 --cfg cfg/yolov3-spp.cfg export t=ultralytics/yolov3:v79 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 79 --device 5 export t=ultralytics/yolov3:v80 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 80 --device 0 export t=ultralytics/yolov3:v81 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 81 --device 7 export t=ultralytics/yolov3:v82 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 82 --device 0 --cfg cfg/yolov3s.cfg export t=ultralytics/yolov3:v83 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 83 --device 1 --multi export t=ultralytics/yolov3:v84 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 84 --device 0 --multi export t=ultralytics/yolov3:v85 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 85 --device 0 --multi export t=ultralytics/yolov3:v86 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 86 --device 1 --multi export t=ultralytics/yolov3:v87 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 87 --device 2 --multi export t=ultralytics/yolov3:v88 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 273 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 88 --device 3 --multi export t=ultralytics/yolov3:v89 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 89 --device 1 export t=ultralytics/yolov3:v90 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 90 --device 0 --cfg cfg/yolov3-spp-matrix.cfg export t=ultralytics/yolov3:v91 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 91 --device 0 --cfg cfg/yolov3-spp-matrix.cfg export t=ultralytics/yolov3:v92 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t python3 train.py --weights '' --epochs 27 --batch-size 16 --accumulate 4 --prebias --bucket yolov4 --name 92 --device 0 #SM4 export t=ultralytics/yolov3:v0 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host --mount type=bind,source="$(pwd)"/data,target=/usr/src/data $t python3 train.py --weights 'ultralytics49.pt' --epochs 500 --img-size 320 --batch-size 32 --accumulate 2 --prebias --bucket yolov4 --name 78 --device 0 --multi --cfg cfg/yolov3-spp-3cls.cfg --data ../data/sm4/out.data export t=ultralytics/yolov3:v2 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t clear sleep 120 while true do python3 train.py --weights '' --epochs 27 --batch-size 32 --accumulate 2 --prebias --evolve --device 7 --bucket yolov4/416_coco_27e done while true; do python3 train.py --data data/coco.data --img-size 320 --batch-size 64 --accumulate 1 --evolve --epochs 1 --adam --bucket yolov4/adamdefaultpw_coco_1e; done