Implementation of ConjugateGradients method using C and Nvidia CUDA

Fundamentals of heterogeneous parallel programming with CUDA C/C++ at the beginner level.

This system tracks artifacts in museum and triggers alarm if artifact goes missing from the frame.

PyTorch Image and Video Super-Resolution, specialized for vehicle and traffic view processing and performed by using Deep Convolutional Neural Networks

A simple image classifier built with Keras using NVIDIA cuda libraries.

This script collects some informations about NVLink and PCI bus traffic of NVidia GPUs. Results are published as prometheus metrics via a websocket.

A YOLOv4 model that can detect 5 classes on the road and a comparison with YOLOv3.

Automatic transcriber made with the Nvidia NeMo AI toolkit. Used to transcribe speech to text in real-time from any source. Requires CUDA capable GPU to run on the local machine, if setup using virtual audio cables can transcribe the audio that is being played in real-time without any other requirements.

This repository contains scripts and commands for exporting YOLO models to different formats, including TensorRT (.engine) and ONNX (.onnx).

The simplest & most comprehensible tutorial on speaker identification with NVIDIA's `Nemo`.

my thesis works on mri image segmentation of brain tumour using deep learning models

A pre-configured instant-ngp workspace that includes helpful scripts for getting started with NeRF training.

for nvidia graphic metrics on datadog

This repository is a one stop documentation for the tensorrt framework provided by NVIDIA. This repository contains every details starting from installation of tensorrt to deployment of model using Tensorrt.

Convert Your Videos into Frame By Frame Png's... Useful for Rotoscoping

Python script for collectd, wrapping system calls to nvidia-smi.

Real-time Embedded Deep Learning for Autonomous Lane Change Systems of Autonomous Driving

This project analyzes GPU performance metrics from AI training and inference tasks, highlighting the optimal power settings for efficient operation. It generates visualizations to help identify the best max power settings for training and inference based on energy consumption.

A deepfake face detection system using transfer learning with Xception CNN. Trained on real and fake face datasets using data augmentation, mixed precision, and GPU acceleration. Accurately classifies facial images as real or fake with high confidence. Ideal for media forensics.

I created this repository as an interest to how well apple metal will do in a sample deep learning models opposed to Nvidia Cuda