# YOLOv5 🚀 by Ultralytics, AGPL-3.0 license

# Builds ultralytics/yolov5:latest image on DockerHub https://hub.docker.com/r/ultralytics/yolov5

# Image is CUDA-optimized for YOLOv5 single/multi-GPU training and inference

# Start FROM PyTorch image https://hub.docker.com/r/pytorch/pytorch

FROM pytorch/pytorch:2.0.0-cuda11.7-cudnn8-runtime

# Downloads to user config dir

ADD https://ultralytics.com/assets/Arial.ttf https://ultralytics.com/assets/Arial.Unicode.ttf /root/.config/Ultralytics/

# Install linux packages

ENV DEBIAN_FRONTEND noninteractive

RUN apt update

RUN TZ=Etc/UTC apt install -y tzdata

RUN apt install --no-install-recommends -y gcc git zip curl htop libgl1 libglib2.0-0 libpython3-dev gnupg

# RUN alias python=python3

# Security updates

# https://security.snyk.io/vuln/SNYK-UBUNTU1804-OPENSSL-3314796

RUN apt upgrade --no-install-recommends -y openssl

# Create working directory

RUN rm -rf /usr/src/app && mkdir -p /usr/src/app

WORKDIR /usr/src/app

# Copy contents

COPY . /usr/src/app

# Install pip packages

COPY requirements.txt .

RUN python3 -m pip install --upgrade pip wheel

RUN pip install --no-cache -r requirements.txt albumentations comet gsutil notebook \

    coremltools onnx onnx-simplifier onnxruntime 'openvino-dev>=2023.0'

    # tensorflow tensorflowjs \

# Set environment variables

ENV OMP_NUM_THREADS=1

# Cleanup

ENV DEBIAN_FRONTEND teletype

# Usage Examples -------------------------------------------------------------------------------------------------------

# Build and Push

# t=ultralytics/yolov5:latest && sudo docker build -f utils/docker/Dockerfile -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)

# DockerHub tag update

# t=ultralytics/yolov5:latest tnew=ultralytics/yolov5:v6.2 && sudo docker pull $t && sudo docker tag $t $tnew && sudo docker push $tnew

# Clean up

# sudo 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