deep learning frameworks
Deep Learning Libraries installer for ArcGIS Pro 2.8
ArcGIS Pro, Server and the ArcGIS API for Python all include tools to use AI and Deep Learning to solve geospatial problems, such as feature extraction, pixel classification, and feature categorization. This installer includes a broad collection of components, such as PyTorch, TensorFlow, Fast.ai and scikit-learn, for performing deep learning and machine learning tasks, a total collection of 254 packages. These packages can be used with the Deep Learning Training tools, interactive object detection, by using the arcgis.learn module within the ArcGIS API for Python, and directly imported into your own scripts and tools. Most of the tools in this collection will work on any machine, but common deep learning workflows require a recent NVIDIA graphics processing unit (GPU), and problem sizes are bound by available GPU memory, see the requirements section.
This installer adds all the included packages to the default arcgispro-py3 environment that Pro and Server both ship with, and no additional environments are necessary in order to get started using the tools. If you do create custom environments, these packages will also be included so you can use the same tools in your own custom environments as well.
For an example of the kinds of workflows this installer and ArcGIS enables, see the AI & Deep Learning in the UC 2020 Plenary video
Important
Ensure compatibility by matching the versions of Deep Learning Libraries and ArcGIS software. To upgrade from a previous version, begin by uninstalling both Deep Learning Libraries and your ArcGIS software, following the instructions provided below.
On Windows:
Once you've downloaded the archive for your product, extract the Zip file to a new location, and run the Windows Installer (e.g. ProDeepLearning.msi) on Windows. This will install the deep learning frameworks into the default arcgispro-py3 Python environment, but not any custom environments you've created prior to running this installation. After installation, subsequent clones will also include the full deep learning package set. You'll need to extract the file (not just open the .MSI from within the Zip file) or the installer won't be able to find its contents. After installation, the archive and installer files can be deleted.
On Server Linux:
Extract the .tar.gz archive, e.g. with tar xvf <file>.tar.gz, then run the DeepLearning-Setup.sh script. For Server 10.9 and earlier, this would create a package set inside of the Server runtime environment. Starting at Server 10.9.1, this installation creates a new deeplearning environment located in <Server Install>/framework/runtime/deeplearning and the deep learning packages are all native Linux implementations. Next, please uncomment and update the ARCGIS_CONDA_DEEPLEARNING variable in the <Server Install>/arcgis/server/usr/init_user_param.sh file and restart your ArcGIS Server.
Upgrading From a Previous Version:
If you're upgrading from a previous release, the safest way to upgrade is to uninstall and reinstall both the product and the deep learning installer. For example, to upgrade from Pro 3.2 to Pro 3.3:
C:Program FilesArcGISProbinPythonenvsarcgispro-py3 or equivalent location for your installation. These may have been left over from previously modified environment.After these steps, you should have a clean Pro installation with the Deep Learning package set included in the default arcgispro-py3 environment.
Manual Installation:
| Following these steps will install an uncertified package set | |
|---|---|
| Make sure to clone the default Python environment to backup your install (see below) |
Python Command Prompt window.
Start menu on Windows, or you can launch it from the product's install folder.Python Command Prompt 3--pinned!)
`conda create -n your-clone-name --clone arcgispro-py3 --pinned
activate your-clone-name
(your-clone-name) C:Program FilesArcGISProbinPythonenvs>
conda install deep-learning-essentials
y, and press Enter
proswap your-clone-name
your-clone-name as the active Python Environment and you should now be able to use deep learning toolsIf you will be working in a disconnected environment, download the required metapackage packages from the links below and follow the instructions under the Steps to Install listed on the package's page. The packages place backbones for deep learning models in the specified install location, eliminating the need for internet access when training deep learning models in ArcGIS.
| Backbones packages |
|---|
| ArcGIS Deep Learning Backbones package |
| ArcGIS Timm Deep Learning Backbones Part 1 v1.0.0 package |
| ArcGIS Timm Deep Learning Backbones Part 2 v1.0.0 package |
| ArcGIS Timm Deep Learning Backbones Part 3 v1.0.0 package |
| ArcGIS Timm Deep Learning Backbones Part 4 v1.0.0 package |
| ArcGIS SAM Backbones 1.0.0 package |
| ArcGIS Mistral Backbone package |
| ArcGIS Polygon Segmentation Postprocessing Backbone |
Once you've installed the deep learning libraries, you can use the Deep Learning Tools to train geospatial deep learning models. You can also find out more about the capabilities of the arcgis.learn module which provides specialized access to many geospatial models beyond those directly available as Geoprocessing tools. Finally, you can add any of the above libraries to your own workflows, by importing the packages listed below.
A collection of Esri conference technical workshops on deep learning:
Most of the packages included in the Deep Learning Libraries installer will work out of the box on any machine configuration. For example, PyTorch optionally can take advantage of a GPU, but will fall back to running its calculations on the CPU if a GPU is not available. However, GPU computation is significantly faster, and some packages such as TensorFlow in this distribution only will work with a supported GPU. CUDA, or Compute Unified Device Architecture, is a general purpose computing platform for GPUs, a requirement for current GPU backed deep learning tools.
| GPU requirement | Supported |
|---|---|
| GPU Type | NVIDIA with CUDA Compute Capability 5.0 minimum, 6.1 or later recommended. See the list of CUDA-enabled cards to determine the compute capability of a GPU. |
| GPU driver | NVIDIA GPU drivers — version 527.41 or higher is required. |
| Dedicated graphics memory † | minimum: 4GB recommended: 8GB or more, depending on the deep learning model architecture and the batch size being used |
† GPU memory, unlike system memory, cannot be accessed 'virtually'. If a model training consumes more GPU memory than you have available, it will fail. GPU memory is also shared across all uses of the machine, so open Pro projects with maps and other applications can limit the available memory for use with these tools.
An out-of-date GPU driver will cause deep learning tools to fail with runtime errors indicating that CUDA is not installed or an unsupported toolchain is present. Verify that you have up-to-date GPU drivers directly provided by NVIDIA.
Geoprocessing tools using deep learning are integrated into multiple areas of the software, and require the related extensions installed to function:
| Tools | Extension |
|---|---|
| Model training, inferencing and exploration | Image Analyst |
| Point cloud classification | 3D Analyst |
| AutoML and text analysis | Advanced, no extension required |
| Library Name | Version | Description |
|---|---|---|
| absl-py | 2.1.0 | Abseil Python Common Libraries |
| accelerate | 0.33.0 | Accelerate provides access to numerical libraries optimized for performance on Intel CPUs and NVidia GPUs |
| addict | 2.4.0 | Provides a dictionary whose items can be set using both attribute and item syntax |
| affine | 2.3.0 | Matrices describing affine transformation of the plane |
| aiohttp | 3.9.5 | Async http client/server framework (asyncio) |
| aiosignal | 1.2.0 | A list of registered asynchronous callbacks |
| albumentations | 1.0.3 | Fast and flexible image augmentation library |
| alembic | 1.8.1 | A database migration tool for SQLAlchemy |
| aom | 3.9.1 | Alliance for Open Media video codec |
| astunparse | 1.6.3 | An AST unparser for Python |
| atomicwrites | 1.4.0 | Atomic file writes for Python |
| bitsandbytes | 0.43.3 | Accessible large language models via k-bit quantization for PyTorch. |
| blosc | 1.21.3 | A blocking, shuffling and loss-less compression library that can be faster than memcpy() |
| boost | 1.82.0 | Boost provides peer-reviewed portable C++ source libraries |
| branca | 0.6.0 | Generate rich HTML + JS elements from Python |
| bzip2 | 1.0.8 | High-quality data compressor |
| cairo | 1.18.2 | A 2D graphics library with support for multiple output devices |
| catalogue | 2.0.10 | Super lightweight function registries for your library |
| catboost | 1.2.3 | Gradient boosting on decision trees library |
| category_encoders | 2.2.2 | A collection sklearn transformers to encode categorical variables as numeric |
| ccimport | 0.4.2 | Fast C++ Python binding |
| charls | 2.2.0 | CharLS, a C++ JPEG-LS library implementation |
| click-plugins | 1.1.1 | An extension module for click to enable registering CLI commands via setuptools entry-points |
| cliff | 3.8.0 | Command Line Interface Formulation Framework |
| cligj | 0.7.2 | Click params for commmand line interfaces to GeoJSON |
| cloudpathlib | 0.16.0 | pathlib.Path-style classes for interacting with files in different cloud storage services. |
| cmaes | 0.8.2 | Blackbox optimization with the Covariance Matrix Adaptation Evolution Strategy |
| cmd2 | 2.4.3 | A tool for building interactive command line apps |
| coloredlogs | 15.0.1 | Colored terminal output for Python's logging module |
| colorlog | 5.0.1 | Log formatting with colors! |
| colour | 0.1.5 | Python color representations manipulation library (RGB, HSL, web, ...) |
| confection | 0.1.4 | The sweetest config system for Python |
| cudatoolkit | 11.8.0 | NVIDIA's CUDA toolkit |
| cudnn | 8.7.0.84 | NVIDIA's cuDNN deep neural network acceleration library |
| cumm | 0.4.11 | CUda Matrix Multiply library |
| cymem | 2.0.6 | Manage calls to calloc/free through Cython |
| cython | 3.0.10 | The Cython compiler for writing C extensions for the Python language |
| cython-blis | 0.7.9 | Fast matrix-multiplication as a self-contained Python library – no system dependencies! |
| datasets | 2.16.1 | HuggingFace/Datasets is an open library of NLP datasets. |
| dav1d | 1.2.1 | The fastest AV1 decoder on all platforms |
| deep-learning-essentials | 3.4 | Expansive collection of deep learning packages |
| descartes | 1.1.0 | Use geometric objects as matplotlib paths and patches |
| detreg | 1.0.0 | PyTorch Wrapper for CUDA Functions of Multi-Scale Deformable Attention |
| dill | 0.3.7 | Serialize all of python (almost) |
| dm-tree | 0.1.7 | A library for working with nested data structures |
| dtreeviz | 1.3.7 | Decision tree visualization |
| einops | 0.7.0 | A new flavor of deep learning operations |
| ensemble-boxes | 1.0.8 | Methods for ensembling boxes from object detection models |
| expat | 2.6.3 | Expat XML parser library in C |
| fairlearn | 0.8.0 | Simple and easy fairness assessment and unfairness mitigation |
| fastai | 1.0.63 | fastai makes deep learning with PyTorch faster, more accurate, and easier |
| fastprogress | 0.2.3 | A fast and simple progress bar for Jupyter Notebook and console |
| fasttext | 0.9.2 | Efficient text classification and representation learning |
| ffmpeg | 7.0.0 | Cross-platform solution to record, convert and stream audio and video |
| filelock | 3.13.1 | A platform independent file lock |
| fiona | 1.9.6 | OGR's neat, nimble, no-nonsense API for Python programmers |
| fire | 0.4.0 | A library for creating CLIs from absolutely any Python object |
| folium | 0.14.0 | Make beautiful maps with Leaflet.js and Python |
| fribidi | 1.0.10 | The Free Implementation of the Unicode Bidirectional Algorithm |
| frozenlist | 1.4.0 | A list-like structure which implements collections.abc.MutableSequence |
| gast | 0.5.3 | Python AST that abstracts the underlying Python version |
| gdown | 5.2.0 | Download large files from Google Drive. |
| geopandas | 1.0.1 | Geographic pandas extensions, base package |
| geopandas-base | 1.0.1 | Geographic pandas extensions, metapackage |
| geos | 3.12.1 | A C++ port of the Java Topology Suite (JTS) |
| getopt-win32 | 0.1 | A port of getopt for Visual C++ |
| gflags | 2.2.2 | A C++ library that implements commandline flags processing |
| giflib | 5.2.1 | Library for reading and writing gif images |
| glib | 2.78.4 | Provides core application building blocks for libraries and applications written in C |
| glib-tools | 2.78.4 | Provides core application building blocks for libraries and applications written in C, command line tools |
| google-auth | 2.29.0 | Google authentication library for Python |
| google-auth-oauthlib | 0.5.2 | Google Authentication Library, oauthlib integration with google-auth |
| google-pasta | 0.2.0 | pasta is an AST-based Python refactoring library |
| gputil | 1.4.0 | NVIDIA GPU status from Python |
| graphite2 | 1.3.14 | A "smart font" system that handles the complexities of lesser-known languages of the world |
| graphviz | 8.1.0 | Open Source graph visualization software |
| groundingdino-py | 0.4.0 | open-set object detector |
| grpcio | 1.46.3 | HTTP/2-based RPC framework |
| gts | 0.7.6 | GNU Triangulated Surface Library |
| h3-py | 3.7.6 | H3 Hexagonal Hierarchical Geospatial Indexing System |
| harfbuzz | 4.3.0 | An OpenType text shaping engine |
| huggingface_hub | 0.24.3 | Client library to download and publish models on the huggingface.co hub |
| humanfriendly | 10.0 | Human friendly output for text interfaces using Python |
| icu | 73.1 | International Components for Unicode |
| imagecodecs | 2023.1.23 | Image transformation, compression, and decompression codecs |
| imageio | 2.33.1 | A Python library for reading and writing image data |
| imgaug | 0.4.0 | Image augmentation for machine learning experiments |
| inplace-abn | 1.1.0 | In-Place Activated BatchNorm |
| joblib | 1.4.2 | Python function as pipeline jobs |
| js2py | 0.74 | JavaScript to Python Translator & JavaScript interpreter written in 100% pure Python. |
| jxrlib | 1.1 | jxrlib - JPEG XR Library by Microsoft, built from Debian hosted sources. |
| keras | 2.13.1 | Deep Learning Library for Theano and TensorFlow |
| langcodes | 3.3.0 | Labels and compares human languages in a standardized way |
| lark | 1.1.2 | a modern parsing library |
| laspy | 1.7.1 | A Python library for reading, modifying and creating LAS files |
| lazy_loader | 0.4 | Easily load subpackages and functions on demand |
| lcms2 | 2.16 | The Little color management system |
| lerc | 3.0 | Limited Error Raster Compression |
| libaec | 1.0.4 | Adaptive entropy coding library |
| libavif | 1.1.1 | A friendly, portable C implementation of the AV1 Image File Format |
| libboost | 1.82.0 | Free peer-reviewed portable C++ source libraries |
| libclang | 14.0.6 | Development headers and libraries for the Clang compiler |
| libclang13 | 14.0.6 | Development headers and libraries for the Clang compiler |
| libcurl | 8.9.1 | Tool and library for transferring data with URL syntax |
| libffi | 3.4.4 | Portable foreign-function interface library |
| libgd | 2.3.3 | Library for the dynamic creation of images |
| libglib | 2.78.4 | Provides core application building blocks for libraries and applications written in C |
| libiconv | 1.16 | Convert text between different encodings |
| libnghttp2 | 1.62.1 | HTTP/2 C library |
| libopencv | 4.8.1 | Computer vision and machine learning software library |
| libspatialindex | 1.9.3 | Extensible framework for robust spatial indexing |
| libsrt | 1.5.3 | Secure, Reliable Transport |
| libuv | 1.40.0 | Cross-platform asynchronous I/O |
| libwebp | 1.3.2 | WebP image library |
| libwebp-base | 1.3.2 | WebP image library, minimal base library |
| libxgboost | 2.0.3 | eXtreme Gradient Boosting |
| libzopfli | 1.0.3 | A compression library for very good but slow deflate or zlib compression |
| lightgbm | 4.3.0 | LightGBM is a gradient boosting framework that uses tree based learning algorithms |
| llvmlite | 0.42.0 | A lightweight LLVM python binding for writing JIT compilers |
| mako | 1.2.3 | Template library written in Python |
| mapclassify | 2.5.0 | Classification schemes for choropleth maps |
| markdown | 3.4.1 | Python implementation of Markdown |
| markdown-it-py | 2.2.0 | Python port of markdown-it. Markdown parsing, done right! |
| mdurl | 0.1.0 | URL utilities for markdown-it-py parser |
| mljar-supervised | 0.11.2 | Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning |
| mmcv | 2.0.1 | OpenMMLab Computer Vision Foundation |
| mmdet | 3.1.0 | OpenMMLab Detection Toolbox and Benchmark |
| mmdet3d | 1.2.0 | Next generation platform for general 3D object detection |
| mmengine | 0.8.5 | Engine of OpenMMLab projects |
| mmsegmentation | 1.1.2 | semantic segmentation toolbox and benchmark |
| motmetrics | 1.1.3 | Benchmark multiple object trackers (MOT) in Python |
| multidict | 6.0.4 | Key-value pairs where keys are sorted and can reoccur |
| multiprocess | 0.70.15 | better multiprocessing and multithreading in python |
| munch | 2.5.0 | A dot-accessible dictionary (a la JavaScript objects) |
| murmurhash | 1.0.7 | A non-cryptographic hash function |
| nb_conda_kernels | 2.5.1 | Launch Jupyter kernels for any installed conda environment |
| neural-structured-learning | 1.4.0 | Train neural networks with structured signals |
| ninja_syntax | 1.7.2 | Python module for generating .ninja files |
| numba | 0.59.1 | NumPy aware dynamic Python compiler using LLVM |
| nuscenes-devkit | 1.1.3 | The devkit of the nuScenes dataset |
| nvidia-ml-py3 | 7.352.0 | Python bindings to the NVIDIA Management Library |
| onnx | 1.13.1 | Open Neural Network Exchange library |
| onnx-tf | 1.9.0 | Experimental Tensorflow Backend for ONNX |
| onnxruntime | 1.18.1 | High performance ML inferencing and training accelerator, Python library |
| onnxruntime-cpp | 1.18.1 | High performance ML inferencing and training accelerator, C++ runtime |
| opencv | 4.8.1 | Computer vision and machine learning software library |
| openjpeg | 2.5.0 | An open-source JPEG 2000 codec written in C |
| opt-einsum | 3.3.0 | Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization |
| optuna | 3.0.4 | A hyperparameter optimization framework |
| pango | 1.50.7 | Text layout and rendering engine |
| pathy | 0.10.3 | A Path interface for local and cloud bucket storage |
| pbr | 5.6.0 | Python Build Reasonableness |
| pccm | 0.4.11 | Python C++ code manager |
| pcre2 | 10.42 | Regular expression pattern matching using the same syntax and semantics as Perl 5 |
| pixman | 0.43.4 | A low-level software library for pixel manipulation |
| plotly | 5.20.0 | An interactive, browser-based graphing library for Python |
| portalocker | 2.3.0 | Portalocker is a library to provide an easy API to file locking. |
| portaudio | 19.6.0 | A cross platform, open-source, audio I/O library |
| preshed | 3.0.6 | Cython Hash Table for Pre-Hashed Keys |
| prettytable | 2.1.0 | Display tabular data in a visually appealing ASCII table format |
| proj4 | 9.4.1 | PROJ coordinate transformation software library |
| py-boost | 1.82.0 | Free peer-reviewed portable C++ source libraries |
| py-opencv | 4.8.1 | Computer vision and machine learning software library |
| py-xgboost | 2.0.3 | Python bindings for the scalable, portable and distributed gradient boosting XGBoost library |
| pyasn1 | 0.4.8 | ASN.1 types and codecs |
| pyasn1-modules | 0.2.8 | A collection of ASN.1-based protocols modules |
| pycocotools | 2.0.7 | Python API for the MS-COCO dataset |
| pyjsparser | 2.7.1 | Fast javascript parser (based on esprima.js) |
| pyopenssl | 24.2.1 | Python wrapper module around the OpenSSL library |
| pyperclip | 1.8.2 | A cross-platform clipboard module for Python |
| pyproj | 3.6.1 | Python interface to PROJ4 library for cartographic transformations |
| pyquaternion | 0.9.9 | Pythonic library for representing and using quaternions |
| pyreadline3 | 3.4.1 | A python implmementation of GNU readline, modernized |
| python-flatbuffers | 23.5.26 | Python runtime library for use with the Flatbuffers serialization format |
| python-graphviz | 0.20.1 | Simple Python interface for Graphviz |
| python-sounddevice | 0.4.4 | Play and record sound with Python |
| python-tzdata | 2023.3 | Provider of IANA time zone data |
| python-xxhash | 2.0.2 | Python binding for xxHash |
| pytorch | 2.0.1 | PyTorch is an optimized tensor library for deep learning using GPUs and CPUs |
| pywin32 | 305 | Python extensions for Windows |
| rasterio | 1.3.10 | Rasterio reads and writes geospatial raster datasets |
| rich | 13.3.5 | Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal |
| rsa | 4.7.2 | Pure-Python RSA implementation |
| rtree | 1.0.1 | R-Tree spatial index for Python GIS |
| safetensors | 0.4.2 | Fast and Safe Tensor serialization |
| samgeo | 3.4 | A collection of the essential packages to work with the Segment Geospatial (samgeo) stack. |
| scikit-image | 0.22.0 | Image processing routines for SciPy |
| scikit-learn | 1.3.0 | A set of python modules for machine learning and data mining |
| scikit-plot | 0.3.7 | Plotting for scikit-learn objects |
| segment-anything | 1.0 | An unofficial Python package for Meta AI's Segment Anything Model |
| segment-anything-hq | 0.3 | Official Python package for Segment Anything in High Quality |
| segment-geospatial | 0.10.2 | A Python package for segmenting geospatial data with the Segment Anything Model (SAM) |
| sentencepiece | 0.1.99 | Unsupervised text tokenizer and detokenizer |
| shap | 0.42.1 | A unified approach to explain the output of any machine learning model |
| shapely | 2.0.5 | Geometric objects, predicates, and operations |
| shellingham | 1.5.0 | Tool to Detect Surrounding Shell |
| slicer | 0.0.7 | A small package for big slicing |
| smart_open | 5.2.1 | Python library for efficient streaming of large files |
| snuggs | 1.4.7 | Snuggs are s-expressions for NumPy |
| spacy | 3.7.2 | Industrial-strength Natural Language Processing |
| spacy-legacy | 3.0.12 | spaCy NLP legacy functions and architectures for backwards compatibility |
| spacy-loggers | 1.0.4 | Alternate loggers for spaCy pipeline training |
| spconv | 2.3.6 | Spatial sparse convolution |
| srsly | 2.4.8 | Modern high-performance serialization utilities for Python |
| stevedore | 5.1.0 | Manage dynamic plugins for Python applications |
| supervision | 0.6.0 | A set of easy-to-use utils that will come in handy in any Computer Vision project |
| tabulate | 0.9.0 | Pretty-print tabular data in Python, a library and a command-line utility |
| tbb | 2021.8.0 | High level abstract threading library |
| tenacity | 8.2.3 | Retry a flaky function whenever an exception occurs until it works |
| tensorboard | 2.13.0 | TensorBoard lets you watch Tensors Flow |
| tensorboard-data-server | 0.7.0 | Data server for TensorBoard |
| tensorboard-plugin-wit | 1.6.0 | What-If Tool TensorBoard plugin |
| tensorboardx | 2.6.2.2 | TensorBoardX lets you watch Tensors Flow without Tensorflow |
| tensorflow | 2.13.0 | TensorFlow is a machine learning library |
| tensorflow-addons | 0.22.0 | Useful extra functionality for TensorFlow |
| tensorflow-estimator | 2.13.0 | TensorFlow Estimator |
| tensorflow-hub | 0.16.1 | A library for transfer learning by reusing parts of TensorFlow models |
| tensorflow-io-gcs-filesystem | 0.31.0 | Dataset, streaming, and file system extensions |
| tensorflow-model-optimization | 0.7.5 | TensorFlow Model Optimization Toolkit |
| tensorflow-probability | 0.20.1 | TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow |
| termcolor | 2.1.0 | ANSII Color formatting for output in terminal |
| terminaltables | 3.1.0 | Generate simple tables in terminals from a nested list of strings |
| tflite-model-maker | 0.3.4 | A model customization library for on-device applications |
| tflite-support | 0.4.4 | TensorFlow Lite Support for deploying TFLite models onto ombile devices |
| thinc | 8.2.2 | Learn super-sparse multi-class models |
| threadpoolctl | 3.5.0 | Python helpers to control the threadpools of native libraries |
| tifffile | 2023.4.12 | Read and write TIFF files |
| timm | 0.4.12 | PyTorch image models |
| tokenizers | 0.19.1 | Fast State-of-the-Art Tokenizers optimized for Research and Production |
| torch-cluster | 1.6.3 | Extension library of highly optimized graph cluster algorithms for use in PyTorch |
| torch-geometric | 2.4.0 | Geometric deep learning extension library for PyTorch |
| torch-scatter | 2.1.2 | Extension library of highly optimized sparse update (scatter and segment) operations |
| torch-sparse | 0.6.18 | Extension library of optimized sparse matrix operations with autograd support |
| torch-spline-conv | 1.2.2 | PyTorch implementation of the spline-based convolution operator of SplineCNN |
| torchvision | 0.15.2 | Image and video datasets and models for torch deep learning |
| torchvision-cpp | 0.15.2 | Image and video datasets and models for torch deep learning, C++ interface |
| transformers | 4.43.4 | State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch |
| trimesh | 2.35.39 | Import, export, process, analyze and view triangular meshes. |
| typeguard | 2.12.1 | Runtime type checker for Python |
| typer | 0.9.0 | A library for building CLI applications |
| typing | 3.10.0.0 | Type Hints for Python - backport for Python<3.5 |
| tzlocal | 5.2 | tzinfo object for the local timezone |
| wasabi | 0.9.1 | A lightweight console printing and formatting toolkit |
| weasel | 0.3.4 | A small and easy workflow system |
| werkzeug | 3.0.3 | The Python WSGI Utility Library |
| wordcloud | 1.9.3 | A little word cloud generator in Python |
| xgboost | 2.0.3 | Scalable, portable and distributed Gradient Boosting (GBDT, GBRT or GBM) library |
| xmltodict | 0.13.0 | Makes working with XML feel like you are working with JSON |
| xxhash | 0.8.0 | Extremely fast hash algorithm |
| xyzservices | 2022.9.0 | Source of XYZ tiles providers |
| yapf | 0.40.2 | A formatter for Python files |
| yarl | 1.9.3 | Yet another URL library |
| zfp | 1.0.0 | Library for compressed numerical arrays that support high throughput read and write random access |
| _py-xgboost-mutex | 2.0 | Metapackage for selecting the desired implementation of XGBoost |
| Library Name | Version | Description |
|---|---|---|
| absl-py | 2.1.0 | Abseil Python Common Libraries |
| addict | 3.4.0 | Provides a dictionary whose items can be set using both attribute and item syntax |
| affine | 2.3.0 | Matrices describing affine transformation of the plane |
| aiohttp | 3.9.5 | Async http client/server framework (asyncio) |
| aiosignal | 1.2.0 | A list of registered asynchronous callbacks |
| albumentations | 1.0.3 | Fast and flexible image augmentation library |
| alembic | 1.8.1 | A database migration tool for SQLAlchemy |
| annotated-types | 0.6.0 | Reusable constraint types to use with typing.Annotated |
| aom | 3.6.0 | Alliance for Open Media video codec |
| astunparse | 1.6.3 | An AST unparser for Python |
| atomicwrites | 1.4.0 | Atomic file writes for Python |
| blosc | 1.21.3 | A blocking, shuffling and loss-less compression library that can be faster than memcpy() |
| boost | 1.82.0 | Boost provides peer-reviewed portable C++ source libraries |
| branca | 0.6.0 | Generate rich HTML + JS elements from Python |
| bzip2 | 1.0.8 | High-quality data compressor |
| cairo | 1.16.0 | A 2D graphics library with support for multiple output devices |
| catalogue | 2.0.10 | Super lightweight function registries for your library |
| catboost | 1.2.3 | Gradient boosting on decision trees library |
| category_encoders | 2.2.2 | A collection sklearn transformers to encode categorical variables as numeric |
| ccimport | 0.4.2 | Fast C++ Python binding |
| charls | 2.2.0 | CharLS, a C++ JPEG-LS library implementation |
| click-plugins | 1.1.1 | An extension module for click to enable registering CLI commands via setuptools entry-points |
| cliff | 3.8.0 | Command Line Interface Formulation Framework |
| cligj | 0.7.2 | Click params for commmand line interfaces to GeoJSON |
| cloudpathlib | 0.16.0 | pathlib.Path-style classes for interacting with files in different cloud storage services. |
| cmaes | 0.8.2 | Blackbox optimization with the Covariance Matrix Adaptation Evolution Strategy |
| cmd2 | 2.4.3 | A tool for building interactive command line apps |
| coloredlogs | 15.0.1 | Colored terminal output for Python's logging module |
| colorlog | 5.0.1 | Log formatting with colors! |
| colour | 0.1.5 | Python color representations manipulation library (RGB, HSL, web, ...) |
| confection | 0.1.4 | The sweetest config system for Python |
| cudatoolkit | 11.8.0 | NVIDIA's CUDA toolkit |
| cudnn | 8.7.0.84 | NVIDIA's cuDNN deep neural network acceleration library |
| cumm | 0.4.11 | CUda Matrix Multiply library |
| cymem | 2.0.6 | Manage calls to calloc/free through Cython |
| cython | 3.0.10 | The Cython compiler for writing C extensions for the Python language |
| cython-blis | 0.7.9 | Fast matrix-multiplication as a self-contained Python library – no system dependencies! |
| datasets | 2.16.1 | HuggingFace/Datasets is an open library of NLP datasets. |
| dav1d | 1.2.1 | The fastest AV1 decoder on all platforms |
| deep-learning-essentials | 3.3 | Expansive collection of deep learning packages |
| descartes | 1.1.0 | Use geometric objects as matplotlib paths and patches |
| detreg | 1.0.0 | PyTorch Wrapper for CUDA Functions of Multi-Scale Deformable Attention |
| dill | 0.3.7 | Serialize all of python (almost) |
| dm-tree | 0.1.7 | A library for working with nested data structures |
| dtreeviz | 1.3.7 | Decision tree visualization |
| einops | 0.7.0 | A new flavor of deep learning operations |
| ensemble-boxes | 1.0.8 | Methods for ensembling boxes from object detection models |
| expat | 2.6.0 | Expat XML parser library in C |
| fairlearn | 0.8.0 | Simple and easy fairness assessment and unfairness mitigation |
| fastai | 1.0.63 | fastai makes deep learning with PyTorch faster, more accurate, and easier |
| fastprogress | 0.2.3 | A fast and simple progress bar for Jupyter Notebook and console |
| fasttext | 0.9.2 | Efficient text classification and representation learning |
| ffmpeg | 6.1.1 | Cross-platform solution to record, convert and stream audio and video |
| filelock | 3.13.1 | A platform independent file lock |
| fiona | 1.9.5 | OGR's neat, nimble, no-nonsense API for Python programmers |
| fire | 0.4.0 | A library for creating CLIs from absolutely any Python object |
| folium | 0.14.0 | Make beautiful maps with Leaflet.js and Python |
| fontconfig | 2.14.1 | A library for configuring and customizing font access |
| fribidi | 1.0.10 | The Free Implementation of the Unicode Bidirectional Algorithm |
| frozenlist | 1.4.0 | A list-like structure which implements collections.abc.MutableSequence |
| gast | 0.5.3 | Python AST that abstracts the underlying Python version |
| gdown | 4.7.1 | Download large files from Google Drive. |
| geopandas | 0.14.1 | Geographic pandas extensions, base package |
| geopandas-base | 0.14.1 | Geographic pandas extensions, metapackage |
| geos | 3.12.1 | A C++ port of the Java Topology Suite (JTS) |
| getopt-win32 | 0.1 | A port of getopt for Visual C++ |
| gflags | 2.2.2 | A C++ library that implements commandline flags processing |
| giflib | 5.2.1 | Library for reading and writing gif images |
| glib | 2.78.4 | Provides core application building blocks for libraries and applications written in C |
| glib-tools | 2.78.4 | Provides core application building blocks for libraries and applications written in C, command line tools |
| google-auth | 2.29.0 | Google authentication library for Python |
| google-auth-oauthlib | 0.5.2 | Google Authentication Library, oauthlib integration with google-auth |
| google-pasta | 0.2.0 | pasta is an AST-based Python refactoring library |
| gputil | 1.4.0 | NVIDIA GPU status from Python |
| graphite2 | 1.3.14 | A "smart font" system that handles the complexities of lesser-known languages of the world |
| graphviz | 8.1.0 | Open Source graph visualization software |
| groundingdino-py | 0.4.0 | open-set object detector |
| grpcio | 1.46.3 | HTTP/2-based RPC framework |
| gts | 0.7.6 | GNU Triangulated Surface Library |
| h3-py | 3.7.6 | H3 Hexagonal Hierarchical Geospatial Indexing System |
| harfbuzz | 4.3.0 | An OpenType text shaping engine |
| huggingface_hub | 0.20.3 | Client library to download and publish models on the huggingface.co hub |
| humanfriendly | 10.0 | Human friendly output for text interfaces using Python |
| icu | 68.1 | International Components for Unicode |
| imagecodecs | 2023.1.23 | Image transformation, compression, and decompression codecs |
| imageio | 2.33.1 | A Python library for reading and writing image data |
| imgaug | 0.4.0 | Image augmentation for machine learning experiments |
| inplace-abn | 1.1.0 | In-Place Activated BatchNorm |
| joblib | 1.4.0 | Python function as pipeline jobs |
| js2py | 0.74 | JavaScript to Python Translator & JavaScript interpreter written in 100% pure Python. |
| jxrlib | 1.1 | jxrlib - JPEG XR Library by Microsoft, built from Debian hosted sources. |
| keras | 2.13.1 | Deep Learning Library for Theano and TensorFlow |
| langcodes | 3.3.0 | Labels and compares human languages in a standardized way |
| lark | 1.1.2 | a modern parsing library |
| laspy | 1.7.1 | A Python library for reading, modifying and creating LAS files |
| lazy_loader | 0.3 | Easily load subpackages and functions on demand |
| lcms2 | 2.12 | The Little color management system |
| lerc | 3.0 | Limited Error Raster Compression |
| libaec | 1.0.4 | Adaptive entropy coding library |
| libavif | 0.11.1 | A friendly, portable C implementation of the AV1 Image File Format |
| libboost | 1.82.0 | Free peer-reviewed portable C++ source libraries |
| libclang | 14.0.6 | Development headers and libraries for the Clang compiler |
| libclang13 | 14.0.6 | Development headers and libraries for the Clang compiler |
| libcurl | 8.6.0 | Tool and library for transferring data with URL syntax |
| libffi | 3.4.4 | Portable foreign-function interface library |
| libgd | 2.3.3 | Library for the dynamic creation of images |
| libglib | 2.78.4 | Provides core application building blocks for libraries and applications written in C |
| libiconv | 1.16 | Convert text between different encodings |
| libnghttp2 | 1.59.0 | HTTP/2 C library |
| libopencv | 4.8.1 | Computer vision and machine learning software library |
| libspatialindex | 1.9.3 | Extensible framework for robust spatial indexing |
| libsrt | 1.4.4 | Secure, Reliable Transport |
| libuv | 1.40.0 | Cross-platform asynchronous I/O |
| libwebp | 1.3.2 | WebP image library |
| libwebp-base | 1.3.2 | WebP image library, minimal base library |
| libxgboost | 2.0.3 | eXtreme Gradient Boosting |
| libzopfli | 1.0.3 | A compression library for very good but slow deflate or zlib compression |
| lightgbm | 4.3.0 | LightGBM is a gradient boosting framework that uses tree based learning algorithms |
| llvmlite | 0.42.0 | A lightweight LLVM python binding for writing JIT compilers |
| mako | 1.2.3 | Template library written in Python |
| mapclassify | 2.5.0 | Classification schemes for choropleth maps |
| markdown | 3.4.1 | Python implementation of Markdown |
| markdown-it-py | 2.2.0 | Python port of markdown-it. Markdown parsing, done right! |
| mdurl | 0.1.0 | URL utilities for markdown-it-py parser |
| mljar-supervised | 0.11.2 | Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning |
| mmcv | 2.0.1 | OpenMMLab Computer Vision Foundation |
| mmdet | 3.1.0 | OpenMMLab Detection Toolbox and Benchmark |
| mmdet3d | 1.2.0 | Next generation platform for general 3D object detection |
| mmengine | 0.8.5 | Engine of OpenMMLab projects |
| mmsegmentation | 1.1.2 | semantic segmentation toolbox and benchmark |
| motmetrics | 1.1.3 | Benchmark multiple object trackers (MOT) in Python |
| multidict | 6.0.4 | Key-value pairs where keys are sorted and can reoccur |
| multiprocess | 0.70.15 | better multiprocessing and multithreading in python |
| munch | 2.5.0 | A dot-accessible dictionary (a la JavaScript objects) |
| murmurhash | 1.0.7 | A non-cryptographic hash function |
| nb_conda_kernels | 2.3.1 | Launch Jupyter kernels for any installed conda environment |
| neural-structured-learning | 1.4.0 | Train neural networks with structured signals |
| ninja_syntax | 1.7.2 | Python module for generating .ninja files |
| numba | 0.59.1 | NumPy aware dynamic Python compiler using LLVM |
| nuscenes-devkit | 1.1.3 | The devkit of the nuScenes dataset |
| nvidia-ml-py3 | 7.352.0 | Python bindings to the NVIDIA Management Library |
| onnx | 1.13.1 | Open Neural Network Exchange library |
| onnx-tf | 1.9.0 | Experimental Tensorflow Backend for ONNX |
| onnxruntime | 1.17.1 | cross-platform, high performance ML inferencing and training accelerator |
| opencv | 4.8.1 | Computer vision and machine learning software library |
| openjpeg | 2.5.0 | An open-source JPEG 2000 codec written in C |
| opt-einsum | 3.3.0 | Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization |
| optuna | 3.0.4 | A hyperparameter optimization framework |
| pango | 1.50.7 | Text layout and rendering engine |
| pathy | 0.10.3 | A Path interface for local and cloud bucket storage |
| pbr | 5.6.0 | Python Build Reasonableness |
| pccm | 0.4.11 | Python C++ code manager |
| pcre2 | 10.42 | Regular expression pattern matching using the same syntax and semantics as Perl 5 |
| pixman | 0.42.2 | A low-level software library for pixel manipulation |
| plotly | 5.20.0 | An interactive, browser-based graphing library for Python |
| portalocker | 2.3.0 | Portalocker is a library to provide an easy API to file locking. |
| portaudio | 19.6.0 | A cross platform, open-source, audio I/O library |
| preshed | 3.0.6 | Cython Hash Table for Pre-Hashed Keys |
| prettytable | 2.1.0 | Display tabular data in a visually appealing ASCII table format |
| proj4 | 9.3.1 | PROJ coordinate transformation software library |
| py-boost | 1.82.0 | Free peer-reviewed portable C++ source libraries |
| py-opencv | 4.8.1 | Computer vision and machine learning software library |
| py-xgboost | 2.0.3 | Python bindings for the scalable, portable and distributed gradient boosting XGBoost library |
| pyasn1 | 0.4.8 | ASN.1 types and codecs |
| pyasn1-modules | 0.2.8 | A collection of ASN.1-based protocols modules |
| pycocotools | 2.0.7 | Python API for the MS-COCO dataset |
| pydantic | 2.4.2 | Data validation and settings management using python type hinting |
| pydantic-core | 2.10.1 | Data validation and settings management using python type hinting, core package |
| pyjsparser | 2.7.1 | Fast javascript parser (based on esprima.js) |
| pyperclip | 1.8.2 | A cross-platform clipboard module for Python |
| pyproj | 3.6.1 | Python interface to PROJ4 library for cartographic transformations |
| pyquaternion | 0.9.9 | Pythonic library for representing and using quaternions |
| pyreadline3 | 3.4.1 | A python implmementation of GNU readline, modernized |
| python-flatbuffers | 23.5.26 | Python runtime library for use with the Flatbuffers serialization format |
| python-graphviz | 0.20.1 | Simple Python interface for Graphviz |
| python-sounddevice | 0.4.4 | Play and record sound with Python |
| python-tzdata | 2023.3 | Provider of IANA time zone data |
| python-xxhash | 2.0.2 | Python binding for xxHash |
| pytorch | 2.0.1 | PyTorch is an optimized tensor library for deep learning using GPUs and CPUs |
| pywin32 | 305 | Python extensions for Windows |
| rasterio | 1.3.9 | Rasterio reads and writes geospatial raster datasets |
| rich | 13.3.5 | Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal |
| rsa | 4.7.2 | Pure-Python RSA implementation |
| rtree | 1.0.1 | R-Tree spatial index for Python GIS |
| safetensors | 0.4.2 | Fast and Safe Tensor serialization |
| samgeo | 3.3 | A collection of the essential packages to work with the Segment Geospatial (samgeo) stack. |
| scikit-image | 0.22.0 | Image processing routines for SciPy |
| scikit-learn | 1.3.0 | A set of python modules for machine learning and data mining |
| scikit-plot | 0.3.7 | Plotting for scikit-learn objects |
| segment-anything | 1.0 | An unofficial Python package for Meta AI's Segment Anything Model |
| segment-anything-hq | 0.3 | Official Python package for Segment Anything in High Quality |
| segment-geospatial | 0.10.2 | A Python package for segmenting geospatial data with the Segment Anything Model (SAM) |
| sentencepiece | 0.1.99 | Unsupervised text tokenizer and detokenizer |
| shap | 0.42.1 | A unified approach to explain the output of any machine learning model |
| shapely | 2.0.1 | Geometric objects, predicates, and operations |
| shellingham | 1.5.0 | Tool to Detect Surrounding Shell |
| slicer | 0.0.7 | A small package for big slicing |
| smart_open | 5.2.1 | Python library for efficient streaming of large files |
| snuggs | 1.4.7 | Snuggs are s-expressions for NumPy |
| spacy | 3.7.2 | Industrial-strength Natural Language Processing |
| spacy-legacy | 3.0.12 | spaCy NLP legacy functions and architectures for backwards compatibility |
| spacy-loggers | 1.0.4 | Alternate loggers for spaCy pipeline training |
| spconv | 2.3.6 | Spatial sparse convolution |
| srsly | 2.4.8 | Modern high-performance serialization utilities for Python |
| stevedore | 5.1.0 | Manage dynamic plugins for Python applications |
| supervision | 0.6.0 | A set of easy-to-use utils that will come in handy in any Computer Vision project |
| tabulate | 0.9.0 | Pretty-print tabular data in Python, a library and a command-line utility |
| tbb | 2021.8.0 | High level abstract threading library |
| tenacity | 8.2.2 | Retry a flaky function whenever an exception occurs until it works |
| tensorboard | 2.13.0 | TensorBoard lets you watch Tensors Flow |
| tensorboard-data-server | 0.7.0 | Data server for TensorBoard |
| tensorboard-plugin-wit | 1.6.0 | What-If Tool TensorBoard plugin |
| tensorboardx | 2.6.2.2 | TensorBoardX lets you watch Tensors Flow without Tensorflow |
| tensorflow | 2.13.0 | TensorFlow is a machine learning library |
| tensorflow-addons | 0.22.0 | Useful extra functionality for TensorFlow |
| tensorflow-estimator | 2.13.0 | TensorFlow Estimator |
| tensorflow-hub | 0.16.1 | A library for transfer learning by reusing parts of TensorFlow models |
