GCP Quickstart

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 Jupyter Notebook and our Docker image at https://hub.docker.com/r/ultralytics/yolov5 .

1. Create VM

Select a PyTorch >=1.7 image from the GCP marketplace, check 'install GPU driver automatically', and select a 300 GB SSD for sufficient I/O speed. All dependencies are typically included in the preinstalled Anaconda distribution.

2. Setup VM

Clone this repo and install requirements.txt dependencies, including Python>=3.8 and PyTorch>=1.7.

$ git clone https://github.com/ultralytics/yolov5  # clone repo
$ cd yolov5
$ pip install -r requirements.txt  # install dependencies

3. Start

• Train: $ python train.py
• Test: $ python test.py
• Detect: $ python detect.py

Optional Extras

Add 64GB of swap memory (to --cache large datasets).

sudo fallocate -l 64G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile
free -h  # check memory

Mount local SSD

lsblk
sudo mkfs.ext4 -F /dev/nvme0n1
sudo mkdir -p /mnt/disks/nvme0n1
sudo mount /dev/nvme0n1 /mnt/disks/nvme0n1
sudo chmod a+w /mnt/disks/nvme0n1
cp -r coco /mnt/disks/nvme0n1