In the case of your data having only 1 channel while want to use timm models

Overview

timm_custom

Description

In the case of your data having only 1 channel while want to use timm models (with or without pretrained weights), run the following command to get the model with appropriate number of input channels.

python load_timm.py --model "densenet" --model_depth 121 --pretrained True --num_classes=4 --n_input_channels 1

Argument

The argument explanation is below:

usage: load_timm.py [-h] [--model MODEL] [--model_depth MODEL_DEPTH]
                    [--pretrained PRETRAINED] [--num_classes NUM_CLASSES]
                    [--n_input_channels N_INPUT_CHANNELS]

optional arguments:
  -h, --help            show this help message and exit
  --model MODEL         Model name
  --model_depth MODEL_DEPTH
                        Depth of the model
  --pretrained PRETRAINED
                        If true, will use ImageNet pretrained weight
  --num_classes NUM_CLASSES
                        number of classes
  --n_input_channels N_INPUT_CHANNELS
                        number of input channels

Notice that the script will check if the given model + model_depth is in timm models. Additionally, if pretrained=True, it will check if that particular model has a pretraiend weight or not. If not, it will just set pretrained=False.

Usage

In the case of a project where it handles CT images, it only has 1 channel since there is no RGB channel.

Example

When running python load_timm.py --model "densenet" --model_depth 121 --pretrained True --num_classes=4 --n_input_channels 3, the model architecture is shown below:

DenseNet(
  (features): Sequential(
    (conv0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
    (norm0): BatchNormAct2d(
      64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True
      (act): ReLU(inplace=True)
    )
...

When running python load_timm.py --model "densenet" --model_depth 121 --pretrained True --num_classes=4 --n_input_channels 1, the model architecture has been updated as shown below:

DenseNet(
  (features): Sequential(
    (conv0): Conv2d(1, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
    (norm0): BatchNormAct2d(
      64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True
      (act): ReLU(inplace=True)
    )
...

Warning

Since timm models pretrained weights are trained on the ImageNet dataset (which has 3 channels), it will lose the "initial benefit" of pretrained weights.

A Pytorch Implementation of [Source data‐free domain adaptation of object detector through domain

A Pytorch Implementation of Source data‐free domain adaptation of object detector through domain‐specific perturbation Please follow Faster R-CNN and

1 Dec 25, 2021
Use unsupervised and supervised learning to predict stocks

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

Vivek Palaniappan 1.5k Dec 26, 2022
iNAS: Integral NAS for Device-Aware Salient Object Detection

iNAS: Integral NAS for Device-Aware Salient Object Detection Introduction Integral search design (jointly consider backbone/head structures, design/de

顾宇超 77 Dec 02, 2022
Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"

Trajectory Transformer Code release for Offline Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are

Michael Janner 266 Dec 27, 2022
Official repository of "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment"

BasicVSR_PlusPlus (CVPR 2022) [Paper] [Project Page] [Code] This is the official repository for BasicVSR++. Please feel free to raise issue related to

Kelvin C.K. Chan 227 Jan 01, 2023
Image processing in Python

scikit-image: Image processing in Python Website (including documentation): https://scikit-image.org/ Mailing list: https://mail.python.org/mailman3/l

Image Processing Toolbox for SciPy 5.2k Dec 31, 2022
To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

Kunal Wadhwa 2 Jan 05, 2022
Pytorch implementation of Decoupled Spatial-Temporal Transformer for Video Inpainting

Decoupled Spatial-Temporal Transformer for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu Sun, Xiaogang Wang, J

51 Dec 13, 2022
Fully Adaptive Bayesian Algorithm for Data Analysis (FABADA) is a new approach of noise reduction methods. In this repository is shown the package developed for this new method based on \citepaper.

Fully Adaptive Bayesian Algorithm for Data Analysis FABADA FABADA is a novel non-parametric noise reduction technique which arise from the point of vi

18 Oct 20, 2022
This repository contains all code and data for the Inside Out Visual Place Recognition task

Inside Out Visual Place Recognition This repository contains code and instructions to reproduce the results for the Inside Out Visual Place Recognitio

15 May 21, 2022
A flexible and extensible framework for gait recognition.

A flexible and extensible framework for gait recognition. You can focus on designing your own models and comparing with state-of-the-arts easily with the help of OpenGait.

Shiqi Yu 335 Dec 22, 2022
Open source annotation tool for machine learning practitioners.

doccano doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequ

7.1k Jan 01, 2023
Modular Probabilistic Programming on MXNet

MXFusion | | | | Tutorials | Documentation | Contribution Guide MXFusion is a modular deep probabilistic programming library. With MXFusion Modules yo

Amazon 100 Dec 10, 2022
MLP-Like Vision Permutator for Visual Recognition (PyTorch)

Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition (arxiv) This is a Pytorch implementation of our paper. We present Vision

Qibin (Andrew) Hou 162 Nov 28, 2022
OpenMMLab Detection Toolbox and Benchmark

MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.

OpenMMLab 22.5k Jan 05, 2023
Pgn2tex - Scripts to convert pgn files to latex document. Useful to build books or pdf from pgn studies

Pgn2Latex (WIP) A simple script to make pdf from pgn files and studies. It's sti

12 Jul 23, 2022
This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state.

This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state. Dependencies Account wi

Balamurugan Soundararaj 21 Dec 14, 2022
ProMP: Proximal Meta-Policy Search

ProMP: Proximal Meta-Policy Search Implementations corresponding to ProMP (Rothfuss et al., 2018). Overall this repository consists of two branches: m

Jonas Rothfuss 212 Dec 20, 2022
Training and Evaluation Code for Neural Volumes

Neural Volumes This repository contains training and evaluation code for the paper Neural Volumes. The method learns a 3D volumetric representation of

Meta Research 370 Dec 08, 2022