Setup and run a local LLM and Chatbot using consumer grade hardware.

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All Algorithms implemented in Python

Experimental flows using nextpnr for Xilinx devices

Minimal HW-based demo of GPUDirect RDMA on NVIDIA Jetson AGX Xavier running L4T

SUPRA: Software Defined Ultrasound Processing for Real-Time Applications - An Open Source 2D and 3D Pipeline from Beamforming to B-Mode

Additional examples to compliment TI's Bluetooth Low Energy Stack offerings.

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on d…

ECG to RR

Geometric Deep Learning Extension Library for PyTorch

Final project for RecVis 18

Freeze (package) Python programs into stand-alone executables

A PyTorch Implementation of Single Shot MultiBox Detector

Deep Extreme Cut http://www.vision.ee.ethz.ch/~cvlsegmentation/dextr

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

PANet for Instance Segmentation and Object Detection

Client side integration example source code and libraries for AI-Assisted Annotation SDK

MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas lik…

Simple way to handle fat files without committing them to git, supports synchronization using rsync

Linux kernel 4.4 forked from Nvidia Linux4Tegra for TX1 and TX2. Supports L4T 28.1 and 28.2.1

A Deep Learning based project for colorizing and restoring old images

USB access for Python

Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018

Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

Semantic Instance Segmentation with a Discriminative Loss Function in PyTorch

PyTorch implementation of DSNT

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.