Duke Machine Learning Winter School: Computer Vision 2022

Overview

mlwscv2002

Welcome to the Duke Machine Learning Winter School: Computer Vision 2022!

The MLWS-CV includes 3 hands-on training sessions on implementing machine learning tools with the PyTorch software platform. You can see the full description at https://plus.datascience.duke.edu/mlwscv2022

Day 1: Introduction to PyTorch (Billy Carson)

Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day1_student_notebook.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day1_solution_notebook.ipynb

Day 2: Pytorch for image analysis with convolutional neural networks (Gavin Karr)

Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day2_student_notebook.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day2_solution_notebook.ipynb

Day 3: PyTorch for image analysis including image segmentation and object detection (Akhil Ambekar)

Part 1:
Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day3_student_notebook_part1.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day3_solutions_notebook_part1.ipynb

Part 2:
Student notebook (contains space for student to code along): https://github.com/dukeplusds/mlwscv2022/blob/main/day3_student_notebook_part2.ipynb
Full solutions notebook: https://github.com/dukeplusds/mlwscv2022/blob/main/day3_solutions_notebook_part2.ipynb

We are using a virtual computing environment provided by Duke's Office of Information Technology (OIT). For those that are interested, the source code for the Docker container can be found here: https://gitlab.oit.duke.edu/mccahill/ml-winter-school

Owner
Duke + Data Science (+DS)
Duke + Data Science (+DS)
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach"

Stock Market Buy/Sell/Hold prediction Using convolutional Neural Network This repo is an attempt to implement the research paper titled "Algorithmic F

Asutosh Nayak 136 Dec 28, 2022
Vehicles Counting using YOLOv4 + DeepSORT + Flask + Ngrok

A project for counting vehicles using YOLOv4 + DeepSORT + Flask + Ngrok

Duong Tran Thanh 37 Dec 16, 2022
3D ResNet Video Classification accelerated by TensorRT

Activity Recognition TensorRT Perform video classification using 3D ResNets trained on Kinetics-400 dataset and accelerated with TensorRT P.S Click on

Akash James 39 Nov 21, 2022
Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

Nils Thuerey 1.3k Jan 08, 2023
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

Felix Wimbauer 494 Jan 06, 2023
KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

CAiRE 42 Nov 10, 2022
Official Repsoitory for "Activate or Not: Learning Customized Activation." [CVPR 2021]

CVPR 2021 | Activate or Not: Learning Customized Activation. This repository contains the official Pytorch implementation of the paper Activate or Not

184 Dec 27, 2022
Collection of sports betting AI tools.

sports-betting sports-betting is a collection of tools that makes it easy to create machine learning models for sports betting and evaluate their perf

George Douzas 109 Dec 31, 2022
This repository contains a re-implementation of the code for the CVPR 2021 paper "Omnimatte: Associating Objects and Their Effects in Video."

Omnimatte in PyTorch This repository contains a re-implementation of the code for the CVPR 2021 paper "Omnimatte: Associating Objects and Their Effect

Erika Lu 728 Dec 28, 2022
Using this codebase as a tool for my own research. Making some modifications to the original repo for my own purposes.

For SwapNet Create a list.txt file containing all the images to process. This can be done with the GNU find command: find path/to/input/folder -name '

Andrew Jong 2 Nov 10, 2021
Learning to Prompt for Vision-Language Models.

CoOp Paper: Learning to Prompt for Vision-Language Models Authors: Kaiyang Zhou, Jingkang Yang, Chen Change Loy, Ziwei Liu CoOp (Context Optimization)

Kaiyang 679 Jan 04, 2023
Top #1 Submission code for the first https://alphamev.ai MEV competition with best AUC (0.9893) and MSE (0.0982).

alphamev-winning-submission Top #1 Submission code for the first alphamev MEV competition with best AUC (0.9893) and MSE (0.0982). The code won't run

70 Oct 29, 2022
TorchDistiller - a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and instance segmentation.

This project is a collection of the open source pytorch code for knowledge distillation, especially for the perception tasks, including semantic segmentation, depth estimation, object detection and i

yifan liu 147 Dec 03, 2022
Official implementation of "A Shared Representation for Photorealistic Driving Simulators" in PyTorch.

A Shared Representation for Photorealistic Driving Simulators The official code for the paper: "A Shared Representation for Photorealistic Driving Sim

VITA lab at EPFL 7 Oct 13, 2022
Drone Task1 - Drone Task1 With Python

Drone_Task1 Matching Results 3.mp4 1.mp4

MLV Lab (Machine Learning and Vision Lab at Korea University) 11 Nov 14, 2022
Official repo for AutoInt: Automatic Integration for Fast Neural Volume Rendering in CVPR 2021

AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021 Project Page | Video | Paper PyTorch implementation of automatic integration

Stanford Computational Imaging Lab 149 Dec 22, 2022
Learning to Predict Gradients for Semi-Supervised Continual Learning

Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le

Yan Luo 2 Mar 05, 2022
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

PyStan NOTE: This documentation describes a BETA release of PyStan 3. PyStan is a Python interface to Stan, a package for Bayesian inference. StanĀ® is

Stan 229 Dec 29, 2022
Code for "Steerable Pyramid Transform Enables Robust Left Ventricle Quantification"

Code for "Steerable Pyramid Transform Enables Robust Left Ventricle Quantification" This is an end-to-end framework for accurate and robust left ventr

2 Jul 09, 2022
An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise

45 Dec 08, 2022