Registry / ai-ml / autogluon-vision

autogluon-vision

library0.6.2pypypiunverified

AutoGluon Vision is part of the AutoGluon AutoML framework for computer vision tasks. It automates image classification, object detection, and other vision modalities. The latest release is v1.5.0 (Dec 2025). The package is under active development and follows the AutoGluon release cadence (~quarterly). Note: AutoGluon Vision is typically installed via the metapackage 'autogluon' or the standalone 'autogluon.vision' module; 'autogluon-vision' on PyPI is a legacy split package.

ai-ml data

pip install autogluon

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · AUTOGLUON-VISION

autogluon-vision

ai-mlpythonv0.6.2

Install

—

Import

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Disk

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Pass rate

0/ 10

Env Coverage0 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v? · pip install

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

build_error

glibc

py 3.10–3.910 runs

timeout

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

ImagePredictor

✓ from autogluon.vision import ImagePredictor

✗ from autogluon.vision import ImagePredictor

Train an image classification model on a sample dataset with minimal code. The fit method automatically downloads and preprocesses data.

from autogluon.vision import ImagePredictor predictor = ImagePredictor() predictor.fit('https://autogluon.s3.amazonaws.com/datasets/shopee-iet.zip') # Predict on new images results = predictor.predict('https://autogluon.s3.amazonaws.com/datasets/shopee-iet/test/')

autogluon --version

Debug

Known issues

breakingAutoGluon 1.0 dropped support for Python 3.7. Python 3.8 support was dropped in v1.2. Use Python 3.9–3.12.

fix

Use Python >=3.9 (3.10–3.12 recommended). Check your environment with 'python --version'.

affects: >=1.0.0

breakingIn AutoGluon 1.0, the 'autogluon.vision' module was unified under 'autogluon.multimodal'. Direct usage of old vision-specific APIs (e.g., 'ObjectDetector' without the multimodal wrapper) may break.

fix

Migrate to 'from autogluon.multimodal import MultiModalPredictor' and use the unified API for vision tasks.

affects: >=1.0.0

deprecatedThe standalone 'autogluon-vision' package on PyPI may not be updated as frequently as the main 'autogluon' metapackage. Installing 'autogluon-vision' directly could result in an outdated version.

fix

Install 'pip install autogluon' to get the full suite (tabular, vision, text). This is the recommended approach since v1.0.

affects: all

gotchaAutoGluon Vision model training requires a GPU. CPU-only training may be extremely slow or fail due to insufficient memory.

fix

Ensure your environment has a compatible GPU (NVIDIA with CUDA). Use 'import torch; print(torch.cuda.is_available())' to verify.

affects: all

gotchaThe 'fit()' method downloads datasets from S3 by default. Running in an offline or restricted network environment will fail unless you provide local data.

fix

Always specify a local root path for data: predictor.fit('/path/to/local/data') or use a custom Dataset object.

affects: all

Upgrade

Version history

0.6.2latest on PyPI · released Jan 11, 2023

Audit

Dependencies

torchrequiredAutoGluon Vision uses PyTorch as the deep learning backend

torchvisionrequiredRequired for image models and transforms

autogluon.corerequiredCore library for training, prediction, and utilities

autogluon.multimodalrequiredVision models are built on the multimodal framework since v1.0

Agent activity

28 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/autogluon/autogluon ↗

packagehttps://pypi.org/project/autogluon-vision/ ↗

homepagehttps://auto.gluon.ai ↗

docshttps://auto.gluon.ai ↗