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GCP Quickstart
Glenn Jocher edited this page Apr 8, 2020
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To get started using this repo quickly using a Google Cloud Platform (GCP) Deep Learning Virtual Machine (VM) follow the instructions below. New GCP users are eligible for a $300 free credit offer. Other quickstart options for this repo include our Google Colab Notebook and our latest Docker Image.
Select a PyTorch >=1.3 image from the GCP marketplace, check 'install GPU driver automatically', and select a 100 GB SSD for sufficient I/O speed. All dependencies are included in the preinstalled Anaconda distribution.
Clone repo:
git clone https://github.com/ultralytics/yolov3
Download COCO dataset:
bash yolov3/data/get_coco_dataset_gdrive.sh
cd yolov3
and:
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Train:
python3 train.py
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Test:
python3 test.py
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Detect:
python3 detect.py
Add 128GB of swap memory (to --cache
large datasets).
sudo fallocate -l 128G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile
free -h # check memory
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