86 lines
3.9 KiB
Bash
Executable File
86 lines
3.9 KiB
Bash
Executable File
#!/usr/bin/env bash
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# New VM
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rm -rf yolov3 weights coco
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git clone https://github.com/ultralytics/yolov3
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bash yolov3/weights/download_yolov3_weights.sh && cp -r weights yolov3
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bash yolov3/data/get_coco_dataset.sh
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git clone https://github.com/cocodataset/cocoapi && cd cocoapi/PythonAPI && make && cd ../.. && cp -r cocoapi/PythonAPI/pycocotools yolov3
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sudo shutdown
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# Re-clone
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rm -rf yolov3 # Warning: remove existing
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git clone https://github.com/ultralytics/yolov3 # master
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# git clone -b test --depth 1 https://github.com/ultralytics/yolov3 test # branch
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cp -r cocoapi/PythonAPI/pycocotools yolov3
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cp -r weights yolov3 && cd yolov3
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# Train
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python3 train.py
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# Resume
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python3 train.py --resume
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# Detect
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python3 detect.py
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# Test
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python3 test.py --save-json
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# Git pull
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git pull https://github.com/ultralytics/yolov3 # master
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git pull https://github.com/ultralytics/yolov3 test # branch
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# Test Darknet training
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python3 test.py --weights ../darknet/backup/yolov3.backup
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# Copy latest.pt TO bucket
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gsutil cp yolov3/weights/latest1gpu.pt gs://ultralytics
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# Copy latest.pt FROM bucket
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gsutil cp gs://ultralytics/latest.pt yolov3/weights/latest.pt
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wget https://storage.googleapis.com/ultralytics/yolov3/latest_v1_0.pt -O weights/latest_v1_0.pt
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wget https://storage.googleapis.com/ultralytics/yolov3/best_v1_0.pt -O weights/best_v1_0.pt
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# Reproduce tutorials
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rm results*.txt # WARNING: removes existing results
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python3 train.py --nosave --data data/coco_1img.data && mv results.txt results0r_1img.txt
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python3 train.py --nosave --data data/coco_10img.data && mv results.txt results0r_10img.txt
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python3 train.py --nosave --data data/coco_100img.data && mv results.txt results0r_100img.txt
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#python3 train.py --nosave --data data/coco_100img.data --transfer && mv results.txt results3_100imgTL.txt
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python3 -c "from utils import utils; utils.plot_results()"
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gsutil cp results*.txt gs://ultralytics
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gsutil cp results.png gs://ultralytics
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sudo shutdown
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# Reproduce mAP
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python3 test.py --save-json --img-size 608
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python3 test.py --save-json --img-size 416
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python3 test.py --save-json --img-size 320
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sudo shutdown
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# Unit tests
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python3 detect.py # detect 2 persons, 1 tie
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python3 test.py --data data/coco_32img.data # test mAP = 0.8
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python3 train.py --data data/coco_32img.data --epochs 5 --nosave # train 5 epochs
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python3 train.py --data data/coco_1cls.data --epochs 5 --nosave # train 5 epochs
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python3 train.py --data data/coco_1img.data --epochs 5 --nosave # train 5 epochs
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# AlexyAB Darknet
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gsutil cp -r gs://sm4/supermarket2 . # dataset from bucket
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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
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./darknet detector calc_anchors data/coco_img64.data -num_of_clusters 9 -width 320 -height 320 # kmeans anchor calculation
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./darknet detector train ../supermarket2/supermarket2.data ../yolov3-spp-sm2-1cls-kmeans.cfg darknet53.conv.74 -map -dont_show # train spp
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./darknet detector train ../yolov3/data/coco.data ../yolov3-spp.cfg darknet53.conv.74 -map -dont_show # train spp coco
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./darknet detector train ../supermarket2/supermarket2.data ../yolov3-tiny-sm2-1cls.cfg yolov3-tiny.conv.15 -map -dont_show # train tiny
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./darknet detector train ../supermarket2/supermarket2.data cfg/yolov3-spp-sm2-1cls.cfg backup/yolov3-spp-sm2-1cls_last.weights # resume
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python3 train.py --data ../supermarket2/supermarket2.data --cfg cfg/yolov3-spp-sm2-1cls.cfg --epochs 100 --num-workers 8 --img-size 320 --evolve # train ultralytics
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python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls_5000.weights --cfg cfg/yolov3-spp-sm2-1cls.cfg # test
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gsutil cp -r backup/*.weights gs://sm6/weights # weights to bucket
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# Debug/Development
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python3 train.py --evolve --data data/coco_1k5k.data --epochs 30 --img-size 320
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gsutil cp evolve.txt gs://ultralytics
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sudo shutdown
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