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Semantic Segmentation with OpenVINO

Dilip Parasu

Dilip Parasu

Coimbatore, Tamil Nadu

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Implemented inference of segmentation network with oneAPI. Compressed the model with NNCF for openVINO. ...learn more

Project status: Published/In Market

oneAPI, Internet of Things, Artificial Intelligence

Intel Technologies
oneAPI, Intel Opt ML/DL Framework, OpenVINO

Code Samples [1]

Overview / Usage

This project lays down a template structure to do any end-to-end deployment for any sort of segmentation task. One of the best cases for this, is to deploy this onto drones, and segment forest areas, or oceans.

Methodology / Approach

Torch - Training of the model. And using torch for initial baseline to start with.
TorchScript - Transitioning to TorchScript enables dynamic Just-In-Time (JIT) compilation, enhancing computational efficiency.
Intel PyTorch Extension (IPEX) - BFFloat - IPEX with BFFloat optimization leverages oneDNN. IPEX applies graph fusion, which is accelerated by oneDNN.
Testing Quantization - Quantization with Callibration data was used then to compress the model to INT8 without compermising on accuracy.
OpenVINO Integration - The optimized model seamlessly converts to OpenVINO's Intermediate Representation (IR) format, delivering fast inference speed.

Technologies Used

  1. Pytorch
  2. OpenCV
  3. Pytorch Segmentation Models
  4. NNCF (Neural Network Compression Framework for enhanced OpenVINO™ inference)
  5. OpenVINO
  6. Intel Extention for Pytorch

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Hardware - Local Laptop

Intel i7 11800H

Nvidia RTX 3060

Repository

https://github.com/SuperSecureHuman/Segmentation_OneAPI

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