Duke Machine Learning Winter School: Computer Vision 2022

Last update: May 25, 2022

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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

Duke Machine Learning Winter School: Computer Vision 2022

Related tags

Overview

mlwscv2002

Owner

Duke + Data Science (+DS)

Evaluation toolkit of the informative tracking benchmark comprising 9 scenarios, 180 diverse videos, and new challenges.

Multi-query Video Retreival

Massively parallel Monte Carlo diffusion MR simulator written in Python.

Active learning for Mask R-CNN in Detectron2

Load What You Need: Smaller Multilingual Transformers for Pytorch and TensorFlow 2.0.

Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

Elevation Mapping on GPU.

TensorFlow 2 AI/ML library wrapper for openFrameworks

Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.

Python codes for Lite Audio-Visual Speech Enhancement.

Streamlit App For Product Analysis - Streamlit App For Product Analysis

Official implementation of "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers"

Prediction of MBA refinance Index (Mortgage prepayment)

PyTorch implementation of the Crafting Better Contrastive Views for Siamese Representation Learning

Code release of paper "Deep Multi-View Stereo gone wild"

Codes for the compilation and visualization examples to the HIF vegetation dataset

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon.

A general and strong 3D object detection codebase that supports more methods, datasets and tools (debugging, recording and analysis).

Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class.

Official implementation of our paper "Learning to Bootstrap for Combating Label Noise"

Duke Machine Learning Winter School: Computer Vision 2022

Related tags

Overview

mlwscv2002

Owner

Duke + Data Science (+DS)

Evaluation toolkit of the informative tracking benchmark comprising 9 scenarios, 180 diverse videos, and new challenges.

Multi-query Video Retreival

Massively parallel Monte Carlo diffusion MR simulator written in Python.

Active learning for Mask R-CNN in Detectron2

Load What You Need: Smaller Multilingual Transformers for Pytorch and TensorFlow 2.0.

Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

Elevation Mapping on GPU.

TensorFlow 2 AI/ML library wrapper for openFrameworks

Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.

Python codes for Lite Audio-Visual Speech Enhancement.

Streamlit App For Product Analysis - Streamlit App For Product Analysis

Official implementation of "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers"

Prediction of MBA refinance Index (Mortgage prepayment)

PyTorch implementation of the Crafting Better Contrastive Views for Siamese Representation Learning

Code release of paper "Deep Multi-View Stereo gone wild"

Codes for the compilation and visualization examples to the HIF vegetation dataset

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.

A general and strong 3D object detection codebase that supports more methods, datasets and tools (debugging, recording and analysis).

Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class.

Official implementation of our paper "Learning to Bootstrap for Combating Label Noise"

Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon.