[JOURNAL TIP] 002-IMAGE-ARTIFACT-GENERATION
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Updated
Mar 26, 2020 - Python
[JOURNAL TIP] 002-IMAGE-ARTIFACT-GENERATION
Explore linear regression models for predicting university admissions and implement a non-linear Radial Basis Function (RBF) regression model for image inpainting.
Deploys LaMa Image Inpainting as a microservice. Part of "WolfPack: Application-Network Co-Design for Edge Resource Provisioning"
Generative AI nano degree program
Machine Learning applied to Everybody Edits, powered by Keras
This repository contains tasks focusing on prompt engineering for vision models. Each task explores different aspects of image segmentation, object detection, and image generation using advanced machine learning models. Below are detailed descriptions of the tasks and their respective notebooks.
A small Neural Network for Image Inpainting, developed for educational purpose in an Introduction to Machine Learning course.
URPM v1.3 Inpainting Model (repository for replicate.com)
SPL Paper Codes
Realistic Vision v5.1 Inpainting Model (repository for replicate.com)
Code and reference images for the Deep Capsule Prior experiments
AbsoluteReality v1.8.1 Inpainting Model (repository for replicate.com)
Inpainting project allow us to restore an image partially obstructed by a mask
Measuring how well GANs do at inpainting images.
An UWP app with intuitive controls (drag & drop, mouse wheel / click and keyboard usage) to inpaint images.
Image Inpainting using Partial Convolutions
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