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Ailia Models

Ailia Models is a public Python repository of pre-trained AI models and example programs for use with the ailia SDK. Its catalog covers tasks including object detection, speech recognition, audio processing, action recognition and anomaly detection; the repository README lists 419 models and a runnable YOLOX object-detection example.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Ailia Models — OpenViST project profile in AI Models.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you want to select a pre-trained model and inspect or run its example code with the ailia SDK, rather than call a hosted AI API.

Who it is for

  • Developers exploring pre-trained models for a specific AI task.
  • Python developers prototyping an object-detection, speech, image or audio workflow.
  • Teams evaluating task-specific model examples for desktop or mobile applications using the ailia SDK.

Documented uses

  • Browse a catalog of models by task or model name.
  • Set up the SDK and repository dependencies for a documented example.
  • Launch the YOLOX object-detection example as a starting point for a prototype.
  • Identify models for speech, audio, image-processing and other listed tasks.
Before you choose

Requirements & limits

  • The repository lists Python 3.9–3.12 and names Windows, macOS, Linux, iOS and Android; Jetson and Raspberry Pi are also listed in the README.
  • The documented YOLOX setup installs the ailia package and repository requirements before running a Python script.
  • Model-specific directories are the relevant place to inspect details when choosing a model; a single example workflow should not be assumed to cover the entire catalog.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up and run the YOLOX object-detection example

Follow the repository’s documented Python setup and launch its YOLOX example script.

Before you start

  • Python 3.9, 3.10, 3.11 or 3.12, as listed by the repository.
  • The ailia package, repository checkout and example requirements.

Steps

  1. Install the package with the command below.

    Documented command
    pip3 install ailia

  2. Clone the ailia-models repository and enter its directory.

  3. Install the repository requirements with the command below.

    Documented command
    pip3 install -r requirements.txt

  4. Enter object_detection/yolox and run the command below.

    Documented command
    python3 yolox.py

Expected outcome

The YOLOX Python example is launched; the README says model weights download automatically.

Guide limitations

  • The README does not specify input-image selection or further configuration for this example.
  • This documented workflow is not a compatibility guarantee for a particular environment.
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Evidence and transparency

Sources & review

Official repository ↗
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Sources checked
14 October 2026
Original website title
ailia-ai/ailia-models · Official homepage title · retained in its source language
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