From 3f612e5a5942d9c7a12eb30e1d17ea3770669a54 Mon Sep 17 00:00:00 2001
From: Maksym Ostapenko <mak7.ostapenko@gmail.com>
Date: Tue, 25 Mar 2025 18:44:35 +0100
Subject: [PATCH] Added dockerfile and description how to use it.

---
 Dockerfile | 31 +++++++++++++++++++++++++++++++
 README.md  | 28 ++++++++++++++++++++++++++++
 2 files changed, 59 insertions(+)
 create mode 100644 Dockerfile

diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..065377e
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,31 @@
+FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
+
+# Set the timezone
+ENV TZ Europe/Berlin
+ARG DEBIAN_FRONTEND noninteractive
+
+# Update the system timezone
+RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
+
+# Set the working directory inside the container
+ENV APP_WORKDIR /home/depth_estimation
+WORKDIR $APP_WORKDIR
+
+RUN apt update -y && apt upgrade -y 
+RUN apt-get install libopenblas-dev liblapack-dev -y
+
+# needed for cv2 
+RUN apt-get install ffmpeg libsm6 libxext6 -y
+
+# install pip
+RUN apt install python3-pip -y
+RUN python3 -m pip install --upgrade setuptools pip wheel
+
+COPY ./requirements.txt $APP_WORKDIR/requirements.txt
+
+# Install UniDepth and dependencies
+RUN pip3 install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu118
+
+EXPOSE 80
+
+CMD ["/bin/bash"]
diff --git a/README.md b/README.md
index 3114098..63e2b94 100644
--- a/README.md
+++ b/README.md
@@ -62,6 +62,8 @@ Requirements are not in principle hard requirements, but there might be some dif
 - Python 3.10+ 
 - CUDA 11.8+
 
+
+### Local installation
 Install the environment needed to run UniDepth with:
 ```shell
 export VENV_DIR=<YOUR-VENVS-DIR>
@@ -102,6 +104,32 @@ If everything runs correctly, `demo.py` should print: `ARel: 7.45%`.
 
 If you encounter `Segmentation Fault` after running the demo, you may need to uninstall torch via pip (`pip uninstall torch`) and install the torch version present in [requirements](requirements.txt) with `conda`.
 
+
+### Installation with Docker
+
+Make sure that you have installed [Docker]() and [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html).
+
+First, build the image:
+```shell
+docker build -t unidepth_image .
+```
+
+Second, run the container:
+```shell
+docker run -it --gpus all \
+    --name unidepth_container_1 \
+    -v "$(pwd):/home/depth_estimation" \
+    unidepth_image
+```
+
+Run the example inside of the containner:
+```shell
+# move the target file to the project root
+mv ./scripts/demo.py .
+# run the demo
+python3 demo.py
+```
+
 ## Get Started
 
 After installing the dependencies, you can load the pre-trained models easily from [Hugging Face](https://huggingface.co/models?other=UniDepth) as follows: