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Imgclsmob

Imgclsmob is a Python research repository containing implementations of convolutional neural networks for computer-vision classification, segmentation, detection and pose estimation, plus scripts for training, evaluating and converting models.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Imgclsmob — 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 Imgclsmob when a computer-vision project calls for research-oriented convolutional model implementations and scripts, or when comparing documented framework and pretrained-model coverage before selecting an implementation.

Who it is for

  • Computer-vision researchers comparing convolutional model architectures.
  • Developers seeking implementations across multiple deep-learning frameworks.
  • Practitioners exploring pretrained models or training and evaluating vision models.

Documented uses

  • Inspect and compare implemented classification architectures and their framework or pretrained-dataset coverage.
  • Train or evaluate models for classification, segmentation, detection and pose-estimation tasks.
  • Use a framework-specific model package when model code is needed without auxiliary scripts.
Before you choose

Requirements & limits

The repository is public, identifies an MIT license and documents Python 3.10. Full model and script use requires cloning the repository and installing its requirements.

  • Most models are first implemented in Gluon and then ported, so supported frameworks differ by model.
  • The classification model table records implementation and pretrained-dataset coverage, which can guide model selection.
  • The repository includes auxiliary scripts; separate listed PyPI packages provide models without those scripts.

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 the repository and dependencies

Prepare the repository for using its models and training or evaluation scripts.

Before you start

  • Python 3.10 is identified by the repository.
  • Git and pip for the documented clone and dependency-install commands.

Steps

  1. Clone the repository with the command below.

    Documented command
    git clone git@github.com:osmr/imgclsmob.git

  2. Install the listed dependencies with the command below.

    Documented command
    pip install -r requirements.txt

Expected outcome

The repository and its declared dependencies are installed for use of the models and auxiliary scripts.

Guide limitations

  • The setup instructions do not specify task-specific commands for training or evaluation; consult the relevant framework documentation.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
14 October 2026
Original website title
osmr/imgclsmob · Official homepage title · retained in its source language
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