LAMA - automatic model creation framework

Multi-class metrics for Tensorflow

Experiments with UNET/FPN models and cityscapes/kitti datasets [Pytorch]

This repository contains the implementation for our work "Learning Topological Interactions for Multi-Class Medical Image Segmentation", accepted to ECCV 2022 (Oral)

Fast MOT base on yolo+deepsort, support yolo3 and yolo4

This is an implementation of multi-class focal loss in PyTorch.

This project aims to predict customer booking behaviors by classifying them into three categories: Booked and Canceled Booked and Checked Out Booked and Did Not Show

This repository contains Python code for rice type detection using multiclass classification. The project leverages the MobileNetV2 architecture to classify six different types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. The dataset used for training and evaluation can be found on Kaggle and consists of categorized rice images.

Multi Class Image Classification using Transfer learning with InceptionResNetV2

Discord Bot for computing your AL D&D 5e character's hit points, given the Constitution modifier, its classes and levels, and other HP modifiers such as Tough feat or being a Hill Dwarf.

In this project tutorial we will discover how we can use Keras to develop and evaluate neural network models for multiclass classification problems

"This program trains a model using 'SVM' or 'Softmax' and predicts the input data. Loss history and predicted tags are displayed as results."