YoloV2 Inference Engine

Projects for CS492 Systems for Machine Learning course, Spring 2020, KAIST

About

This repository includes implementations of essential layers to infer YOLOv2 model. Layers has been implemented in using only python numpy API as well as using CPU and GPU parallelization techniques.

Table of Contents:

• data
  • input for the model
• src
  • Contains implementation of projects
  • The skeleton for yolov2tiny.py and __init__.py was provided from the course.
• models
  • pickle file that contains pretrained YOLOv2 model's weights
• docs
  • Includes project details and project reports

Projects

proj1

Runs inference of yolov2tiny model using existing library (tensorflow API).

proj2

Implementation of YoloV2 Inference Engine using only python numpy API.

proj3

Implementation of YoloV2 Inference Engine using various parallelization techniques.

• CPU parallelization
  • High level library: OpenBLAS
  • Manual: AVX, pthread
• GPU parallelization
  • High level library: cuBLAS
  • Manual: CUDA