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CFM - model zoo

Project description

CFM-Task-Models

Popular CV models modified for various approaches of Compression for Machines (aka Coding for Machines)

Installation

The easiest way to install CFM-Task-Models is through PyPI, to do this simply use pip install cfm-task-models However, CFM-Task-Models has requirements that currently cannot be handled by pip, thus before using CFM-Task-Models for the first time please run miminstaller.py in your virutal environment. If using poetry consider: poetry run -m cfm_task_models.split_utils.miminstaller

Requirements

CFM-Task-Models currently relies on several tools from OpenMMLab, which require custom installation using the openmim installer. Openmim is a tool provided by OpenMMLab which installs their libraries based on the user's pytorch and cuda versions.

See pyproject.toml for standard requirements and miminstaller.py for OpenMMLAB requirements

Usage

To test Swin_Transformer, run the following command from the root directory:

python models/Swin-Transformer/models/swin_transformer_v2.py

Semantic Segmentation

To download the config and pretrained weights for swin-tiny-upernet-ade20k, run the following command from the root directory:

mim download mmsegmentation --config swin-tiny-patch4-window7-in1k-pre_upernet_8xb2-160k_ade20k-512x512 --dest ./

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