Package: deepdataspace
DeepDataSpaceThe Go-To Choice for CV Data Visualization, Annotation, and Model Analysis.Website•Docs•Tutorials•Deep Data Space (DDS) is an open-source dataset tool with these features out-of-box:interactive dataset visualization and explorationintelligent annotation with a collaborative workflowefficient model management and performance analysis1. Installation1.1 PrerequisitesDeepDataSpace(DDS) requiresPython 3.8 - 3.10and runs on the following platforms:Mac OS: ✅ x86/x64, ✅ arm64Windows 10: ✅ x86/x64, ❌ arm64Ubuntu LTS since 18.04: ✅ x86/x64, ❌ arm64Docker Compose: ✅ x86/x64, ✅ arm641.2 Installing from PyPIpython3-mpipinstallpip--upgrade
python3-mpipinstalldeepdataspace2. Quick StartTheddscommand will be available once thedeepdataspaceis installed, with which you can quickly start the DDS
tool.dds--quickstart# Started DDS[${pid}] at http://127.0.0.1:8765.# The DDS tool is importing datasets inside dir in the background: $HOME/.deepdataspace/dataset-samples.# Explore other useful commands by: ddsop --help.# You can quit the DDS tool with Ctrl+C.It takes a while the first time you start the DDS tool, as it is downloading extra dependencies to set up a runtime
environment.Once the DDS tool is started, visithttp://127.0.0.1:8765and you will see the flowing sample datasets:https://user-images.githubusercontent.com/10917115/240788538-f1fa8d52-7d93-4fe3-bf42-55284074febd.mp43. Alternative Installation Methods3.1 Installing from Source Code# clone the source codegitclonehttps://github.com/IDEA-Research/deepdataspace.git# prepare the node environment（if you haven't installed the Pnpm and Node environment yet）curl-fsSLhttps://get.pnpm.io/install.sh|sh-
pnpmenvuse--globallts# compile frontend filespnpmi
pnpmrunbuild:app# copy frontend files to python package dirrm-rfdeepdataspace/server/static/*
cp-Rpackages/app/dist/*deepdataspace/server/static/
cpdeepdataspace/server/static/index.htmldeepdataspace/server/templates/# install the packagepython3-mpipinstallpip--upgrade
python3-mpipinstall-rrequirements.txt
python3setup.pyinstallAfter the installation, you can start DDS the same way as above:dds --quickstart3.2 Installing by Docker Compose# clone the source codegitclonehttps://github.com/IDEA-Research/deepdataspace.git# prepare dataset directory(where you put all your datasets inside)mkdir-pdatasetsexportDDS_DATASET_DIR=$PWD/datasets# choose a visiting port for DDSexportDDS_PORT=8765# start DDS with docker composecddeepdataspace
dockercomposeupIf everything goes well, you can start visiting DDS athttp://127.0.0.1:87654. DocumentationVisit ourdocumentationfor more details on how to utilize the powers of DDS.Quick StartTutorialsAPI Reference5. UninstallationFor users who installed DDS from PyPi or source code, just uninstall DDS withpipand delete the runtime files.pipuninstalldeepdataspace

rm-rf~/.deepdataspace/*# use with caution, it will delete all datasets imported beforeFor users who installed DDS from docker image, just stop the container and remove the docker image and volume.docker stop dds
docker rmi deepdataspace/dds
docker volume remove dds-runtime # use with caution, it will delete all datasets imported before6. LicenseThis project is released under theApache 2.0 License.Copyright 2023-present, IDEA

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.