real-lixin / deep-learning-for-object-detection-yolov2

Code Files for "Deep Learning for Object Detection" video series

Deep Learning for Object Detection Series

Copyright 2019-2020 The MathWorks, Inc.

Introduction

This repository consists of the code files for the following videos, dataset used for this code can be found here : https://drive.google.com/drive/u/1/folders/1bhohhPoZy03ffbM_rl8ZUPSvJ5py8rM- ;

1. Data Preprocessing for Deep Learning : https://www.mathworks.com/videos/data-preprocessing-for-deep-learning-1578031296056.html
2. Design and Train a YOLOv2 Network in MATLAB : https://www.mathworks.com/videos/design-and-train-a-yolov2-network-in-matlab-1578033233204.html
3. Import Pretrained Deep Learning Networks into MATLAB : https://www.mathworks.com/videos/import-pretrained-deep-learning-networks-into-matlab-1578034627950.html
4. Deploy YOLOv2 to an NVIDIA Jetson : https://www.mathworks.com/videos/deploy-yolov2-to-an-nvidia-jetson-1578035533852.html

Set-Up

1. Clone the repository.
2. Launch Deeplearningforobjectdetection.prj to set-up the project environment.
3. Download the data from this google drive folder : https://drive.google.com/drive/u/1/folders/1bhohhPoZy03ffbM_rl8ZUPSvJ5py8rM-
4. The first time you run this example, edit appropriately and run adjustGroundTruthPaths.m to adjust the ground truth data objects' source path for your computer. Instructions on the edits needed are in the code file.

Folder Structure

1. Codefiles folder consists of matlab code files for each of the videos
2. Utilities folder consists of .mat files required for uplaoding pre trained content

for any questions contact the authors : [e-mail]