Shipper

ML

Object Detection API for identifying Ships from Satellite Imagery.

Traffic Management System for Coastal Regions. Developed for ASEAN-India Hackathon 2021 - PS7 and won Encouragement Award.

Uses OpenCV, Darknet and YOLO v3 for detection and segmentation. Pillow for Image handling, and Flask for API Requests.

Demo

Shipper-ML

Getting Started

Open the application in your web browser on http://localhost:3000

Upload an Image and the model will identify ships from the image, then the result will be displayed. You can use the sample image Shipper_ML_Sample.jpg. The output will be displayed like below.

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Local Development

Prerequisites

• Python 3.6+
• OpenCV

Install Dependencies

pip install -r requirements.txt

Download the Pre-trained Model

wget "https://www.dropbox.com/s/ngy6qx4hxfj6wru/yolov3-ship_1200.weights?dl=1" -O model/yolov3-ship_1200.weights

If on Windows, Copy the link and paste in browser. Download the Model and paste it in the model directory.

Start Development Server

flask run
or 
python app.py

This will start a develoment server on http://localhost:5000

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LICENSE

Eclipse Public License (EPL)

You are free to modify the code. Redistributions are not allowed without prior request from the original author. You are obligated to include the full license and the copyrights.