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# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
# Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
FROM nvcr.io/nvidia/pytorch:21.10-py3
# Install linux packages
RUN apt update && apt install -y zip htop screen libgl1-mesa-glx
# Install python dependencies
COPY requirements.txt .
RUN python -m pip install --upgrade pip
RUN pip uninstall -y torch torchvision torchtext
RUN pip install --no-cache -r requirements.txt albumentations wandb gsutil notebook \
torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
# RUN pip install --no-cache -U torch torchvision
# Create working directory
RUN mkdir -p /usr/src/app
WORKDIR /usr/src/app
# Copy contents
RUN git clone https://github.com/ultralytics/yolov5 /usr/src/app
# COPY . /usr/src/app
# Downloads to user config dir
ADD https://ultralytics.com/assets/Arial.ttf /root/.config/Ultralytics/
# Set environment variables
ENV OMP_NUM_THREADS=8
# ENV HOME=/usr/src/app
# Usage Examples -------------------------------------------------------------------------------------------------------
# Build and Push
# t=ultralytics/yolov5:latest && sudo docker build -t $t . && sudo docker push $t
# Pull and Run
# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all $t
# Pull and Run with local directory access
# t=ultralytics/yolov5:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/datasets:/usr/src/datasets $t
# Kill all
# sudo docker kill $(sudo docker ps -q)
# Kill all image-based
# sudo docker kill $(sudo docker ps -qa --filter ancestor=ultralytics/yolov5:latest)
# Bash into running container
# sudo docker exec -it 5a9b5863d93d bash
# Bash into stopped container
# id=$(sudo docker ps -qa) && sudo docker start $id && sudo docker exec -it $id bash
# Clean up
# docker system prune -a --volumes
# Update Ubuntu drivers
# https://www.maketecheasier.com/install-nvidia-drivers-ubuntu/
# DDP test
# python -m torch.distributed.run --nproc_per_node 2 --master_port 1 train.py --epochs 3
# GCP VM from Image
# docker.io/ultralytics/yolov5:latest
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