autogluon.vision
AutoML for Image, Text, and Tabular Data
Decision gist · record as of 2026-08-14
Yes, with conditions. Install if you need rapid AutoML for image classification or object detection and can tolerate the substantial dependency footprint and Python version cap (3.7–3.9). The package is actively maintained and permissively licensed. However, the latest release is from 2023-01-11, so verify ongoing support and compatibility with your target environment before committing to production use.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.7, <3.10.
- Substantial dependency chain (gluoncv, timm, matplotlib, autogluon.core, autogluon.multimodal) may require compatible environments.
- Low friction installation via wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions. Suitable for proprietary and open-source projects.
last release 2023-01-11 (1311 days) · last repo commit 2026-08-14 · 10,596 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 86,231 downloads/mo, #13,879 on PyPI
Alternatives
Verify before relying
pip install autogluon.vision
from autogluon.vision import ImagePredictor
predictor = ImagePredictor().fit(train_data, time_limit=120)
results = predictor.predict(test_data)- Whether autogluon.vision is actively maintained beyond the latest release date (2023-01-11); days since release warrants confirmation of ongoing support.
- Specific GPU/CUDA requirements and whether CPU-only inference is practical for production workloads.
- Memory footprint and typical training time for common image datasets to assess real-world feasibility.
What it is and what it does
AutoGluon Vision is an AutoML toolkit that automates the machine learning pipeline for image classification and object detection tasks. It abstracts away model selection, hyperparameter tuning, and training orchestration, allowing you to achieve competitive results with just a few lines of code. The package wraps deep learning frameworks and integrates with AutoGluon's core ensemble and multimodal infrastructure to handle the full workflow from raw images to predictions.
The package is designed for practitioners who want strong predictive performance without manual architecture search or extensive hyperparameter experimentation. It supports both image classification and object detection, and is part of the broader AutoGluon ecosystem. The dependency chain is substantial—requiring numpy, pandas, Pillow, matplotlib, and multiple AutoGluon submodules—so installation and environment setup are non-trivial.
Use it for
- Rapid prototyping of image classification models for Kaggle competitions or proof-of-concept projects without manual tuning.
- Automated object detection on custom datasets where you want competitive accuracy without deep learning expertise.
- Benchmarking baseline performance on image tasks before investing in custom architecture design.
- Production image inference pipelines where AutoML-selected models provide good accuracy-latency tradeoffs.
- Multi-task learning combining images with tabular or text data via autogluon.multimodal integration.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
Install if you need rapid AutoML for image classification or object detection and can tolerate the substantial dependency footprint and Python version cap (3.7–3.9). The package is actively maintained and permissively licensed. However, the latest release is from 2023-01-11, so verify ongoing support and compatibility with your target environment before committing to production use.
Install
autogluon-vision on PyPI
Before you install
Low friction installation via wheel distribution. Actively maintained with recent commits and a large repository presence (10596 stars). Requires 8 runtime dependencies including numpy, pandas, and gluoncv, which may add setup complexity for new environments.
Requires Python >=3.7, <3.10. Substantial dependency chain (gluoncv, timm, matplotlib, autogluon.core, autogluon.multimodal) may require compatible environments.
License in practice
Licensed under Apache-2.0 (permissive), allowing commercial use, modification, and distribution with minimal restrictions. Suitable for proprietary and open-source projects.
Quickstart
pip install autogluon.vision
from autogluon.vision import ImagePredictor
predictor = ImagePredictor().fit(train_data, time_limit=120)
results = predictor.predict(test_data)Verify before relying
- Whether autogluon.vision is actively maintained beyond the latest release date (2023-01-11); days since release warrants confirmation of ongoing support.
- Specific GPU/CUDA requirements and whether CPU-only inference is practical for production workloads.
- Memory footprint and typical training time for common image datasets to assess real-world feasibility.
Package facts
| License | Apache-2.0 permissive |
| Python support | Capped below the current Python release >=3.7, <3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 8 packagesnumpypandasgluoncvPillowtimmmatplotlibautogluon.coreautogluon.multimodal |
| Maintenance | Actively maintained 1,311 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 86,231 / month, #13,879 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: Customer ServiceIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Financial and Insurance IndustryIntended Audience :: Healthcare IndustryIntended Audience :: Science/ResearchIntended Audience :: Telecommunications IndustryLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: Python :: 3Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Image RecognitionTopic :: Scientific/Engineering :: Information AnalysisTopic :: Software Development |
Evidence: autogluon.vision-0.6.2-py3-none-any.whl
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See also autogluon.text · autogluon · autogluon.multimodal · autogluon.features · autogluon.core · autogluon.common · autogluon.tabular · pyglove · icevision · cleanlab