The core runtime engine for Ambianic Edge devices.

Train and Inference your custom YOLO-NAS model by Single Command Line

Realtime Portrait Segmentation with Tflite and MediaPipe

Tensorflow 2 Object Detection API kurulumu, GPU desteği, custom model hazırlama, label map oluşturma

PyTorch tutorial for computer vision

A demo of Azure Form Recognizer (Custom Model) with Azure Function blob trigger to process, tag, and move a patient referral form, then save extracted data to Azure Table Storage.

An efficient disease detection application with GUI based (tkinter) frontend and a custom CNN model as backend which detects if a cell is parasitized or normal from its image in real time with an accuracy of 95.22%.

This repository has a internal model changer with FindMDL Hook for Counter-Strike: Global Offensive game. It's fully open source and loadable into the game as a Dynamic-link library (DLL)

It is a project built using opencv python library and darknet-yolov3.

Sentiment analysis using TensorFlow Lite and Firebase.

Tensorflow Advanced Technique Specialization - Solution

Projeto criado em Laravel na versão 8, utilizando JWT, utlizando Model e Middleware customizada para tratamento de autenticação e Docker como infraestrutura

A simple custom QLoRA implementation for fine-tuning a language model (LLM) with basic tools such as PyTorch and Bitsandbytes, completely decoupled from Hugging Face.

This repository contains Final project of CSE428 Brac University

Tensorflow 2.0 implementation of GradCAM

In this Amazon SageMaker tutorial, you'll find labs for setting up a notebook instance, feature engineering with XGBoost, regression modeling, hyperparameter tuning, bring your custom model etc.

Azure Logic App that scores a custom Azure Form Recognizer model in response to an Azure Event Grid event

This represents a complete android application with login and registration system , session , database (sqlite) and recyclerview with custom adapter and model.

Neural Style Transfer implementation for images and videos using Tensorflow2.