Python package for stacking (machine learning technique)
-
Updated
Sep 14, 2020 - Python
Python package for stacking (machine learning technique)
Python package that implements image blend modes
This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.
Python Automated Machine Learning library for tabular data.
Final Project Repository for CMU's Learning Based Image Synthesis Course. Based on StyleGAN2-ADA - Official PyTorch implementation
Optimization algorithms for Machine Learning problems like Hyperparameter tuning and Ensembling.
Powerful stacking/blending ensemble implementation in python.
FastML Framework is a python library that allows to build effective Machine Learning solutions using luigi pipelines.
Stitching RGB/RGBD images into a single image.
This is a script intended to be used along with Automatic 1111 to create a sequence of images by interpolating between multiple prompts.
Image alpha compositing
This is a weighted blending machine implemented using a neural network. The advantage of using a neural network is that the weights assigned to the models for the final result is assigned by the neural network based on backpropagation.
Implementing histogram equalization, low-pass and high-pass filter, and laplacian blending of images.
Code for efficiently matching sky catalogs using KDTrees and graphs.
All-in-one solution for color management.
Add a description, image, and links to the blending topic page so that developers can more easily learn about it.
To associate your repository with the blending topic, visit your repo's landing page and select "manage topics."