# LS-SSDD-v1.0-ShipDetectionComputerVision

**Repository Path**: deepbluethinker/LS-SSDD-v1.0-ShipDetectionComputerVision

## Basic Information

- **Project Name**: LS-SSDD-v1.0-ShipDetectionComputerVision
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-03-05
- **Last Updated**: 2025-03-05

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# LS-SSDD-v1.0-ShipDetectionComputerVision
 
This is the code repository for the paper _Small Vessel Detection from Synthetic Aperture Radar (SAR) Imagery using Deep Learning_ .

This project was done as part of Stanford's CS 230, Deep Learning course.  <br/>
Please see this link: https://cs230.stanford.edu/past-projects/#outstanding-projects for our posting. <br/>

Given the numerous models under consideration and the modular data downloading process, we present our code through interactive Jupyter notebooks.
Note that model weights, model output, and the dataset are *not* in this repo. <br/>  <br/>
The original dataset can be found at: https://github.com/TianwenZhang0825/LS-SSDD-v1.0-OPEN <br/>
We make heavy use of Detectron2 which can be found at: https://github.com/facebookresearch/detectron2  <br/>
![offshorepreds](https://user-images.githubusercontent.com/43712099/111099393-a8010500-8502-11eb-9473-5e796a318688.png)
## Overview
The root directory features two notebooks training our best model and also performing inference. <br/>
`final_model.ipynb` is where we train the Improved model <br/>
`final_evaluation.ipynb` is where we perform inference on the Improved model

### class documents
Contains our papers as part of the CS230 Deep Learning.

### papers
Collection of papers that we used in the course of this project

### train
All of our training notebooks (which include baselines, experiments, and our final models presented in our paper)

### data 
Notebooks for preprocessing data and converting into `Detectron2` format

### util
Notebooks for generating plots for the writeup and developing the sea-land mask for copy-paste augmentation using Otsu's method

### eval
Notebooks for evaluating our models