cd51e1137b
Multi-GPU update with custom collate function to allow variable size target vector per image without needing to pad targets.
54 lines
1.8 KiB
Bash
Executable File
54 lines
1.8 KiB
Bash
Executable File
#!/usr/bin/env bash
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# New VM
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sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3
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bash yolov3/data/get_coco_dataset.sh
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bash yolov3/weights/download_yolov3_weights.sh
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sudo rm -rf cocoapi && 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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# Train
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sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3
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cp -r weights yolov3
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cd yolov3 && python3 train.py --batch-size 48 --epochs 1
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sudo shutdown
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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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# Clone a branch
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sudo rm -rf yolov3 && git clone -b multi_gpu --depth 1 https://github.com/ultralytics/yolov3
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cp -r weights yolov3
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cd yolov3 && python3 train.py --batch-size 48 --epochs 1
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sudo shutdown
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# Git pull branch
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git pull https://github.com/ultralytics/yolov3 multi_gpu
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# Test
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sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3
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sudo rm -rf cocoapi && git clone https://github.com/cocodataset/cocoapi && cd cocoapi/PythonAPI && make && cd ../.. && cp -r cocoapi/PythonAPI/pycocotools yolov3
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cd yolov3 && python3 test.py --save-json --conf-thres 0.001 --img-size 416
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# Test Darknet training
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python3 test.py --img_size 416 --weights ../darknet/backup/yolov3.backup
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# Download with wget
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wget https://storage.googleapis.com/ultralytics/yolov3.pt -O weights/latest.pt
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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/latest.pt
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# Trade Studies
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sudo rm -rf yolov3 && git clone https://github.com/ultralytics/yolov3
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cp -r weights yolov3
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cd yolov3 && python3 train.py --batch-size 16 --epochs 1
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sudo shutdown
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