model-optimizer

Trabajo Fin de Máster: Estudio comparativo de un clasificador de imágenes en Raspberry Pi, de forma que se compara el tiempo de la inferencia en la Raspberry Pi con y sin el Neural Compute Stick (NCS). También se estudia como la complejidad de una red neuronal repercute en el tiempo de inferencia y se analiza si los tiempos obtenidos con el NCS …

scikit-learn-compatible hyperparameter search: BayesHalvingSearchCV (or HalvingBayesianSearchCV - Bayesian/GP) and PatternSearchCV (Hooke-Jeeves), with multi-fidelity data growth for faster tuning on large datasets

ai-zipper offers numerous AI model compression methods, also it is easy to embed into your own source code

Professional bash script for launching and managing Ollama AI models with parameter profile suggestions, system monitoring, and automated configuration. Not an automatic optimizer - provides suggested /set commands for manual application.

An OpenCL-based AI optimizer that accelerates machine learning computations using parallel processing on GPUs and heterogeneous devices. It improves model performance and efficiency by optimizing heavy computational workloads.

ONNX post-training quantization (PTQ) and TensorRT deployment helpers for YOLO-style detectors

This sample shows how to convert TensorFlow model to OpenVINO IR model and how to quantize OpenVINO model.

autooptimizer is a python package for optimize machine learning algorithms.

AI based image classification inspired MobileNet V2 architecture by implementing changes in base architecture and details about using it as a quick response model (proposition) for rapid application as well as comparing it with other models for the same application.

Serving Face Detection and Recognition Based on arc-face

Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.

Dockerfile for converting a frozen Tensorflow model to OpenVINO™ Intermediate Representation (IR) using Model Optimizer (MO)

Explore the OpenVINO toolkit, focusing on components like model zoo, inference engine, and model optimizer, and how they can be used to perform deep learning and computer vision tasks.

Dockerfile to build Intel® Distribution of OpenVINO™ Toolkit docker image for Raspberry Pi

Set up and run OpenVINO in Docker Ubuntu Environment on Intel CPU with Integrated Graphics

Latest YOLO models inferencing using Intel Openvino toolkit

YOLOv5 inferencing using Intel Openvino toolkit

Keras to Tensorflow test for Neural Compute Stick 2

Model optimizer used in Adlik.