ADS-B_Classification

Jet Kwok (2023/10/31)

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📖 Table of Contents

• 📖 Table of Contents
• 📍 Overview
• 📦 Features
• 📂 repository Structure
• ⚙️ Modules
• 🚀 Getting Started
  • 🔧 Installation
  • 🤖 Running ADS-B_Classification
  • 🧪 Tests
• 📄 License
• 👏 Acknowledgments

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📍 Overview

ADS-B Signal Classification Based on Deep Learning.

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📦 Features

The Project contains the following modules:

1. train model
2. test model
3. deploy model

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📂 Repository Structure

└── ADS-B_Classification/
    ├── __asserts__/
    │   └── figs/
    ├── configs/
    │   └── config.yaml
    ├── data_loaders/
    │   └── my_ADSB_dl.py
    ├── deploy/
    │   ├── STEP01_torch2onnx.py
    │   ├── STEP02_onnx_simplify.py
    │   ├── STEP03_onnx_eval.py
    │   └── STEP04_onnx2trt.py
    ├── experiments/
    ├── infers/
    │   └── ADSB_infer.py
    ├── main_test.py
    ├── main_train.py
    ├── models/
    │   ├── ADSB_model.py
    │   ├── base_model/
    │   │   └── resnet1d.py
    │   └── LSTM.py
    ├── trainers/
    │   └── ADSB_trainer.py
    └── utils/
        ├── loss_utils.py
        ├── utils.py
        ├── utils_common.py
        └── utils_visualize.py

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⚙️ Modules

Root

File	Summary
main_test.py	Project test entrance
main_train.py	Project train entrance
config.yaml	Config file
my_ADSB_dl.py	Customized dataloader
STEP01_torch2onnx.py	PyTorch checkpoint to ONNX file
STEP02_onnx_simplify.py	ONNX file simpl;ify
STEP03_onnx_eval.py	ONNX file and PyTorch checkpoint evaluation
STEP04_onnx2trt.py	ONNX file to TensorRT (TODO)
ADSB_infer.py	Main infer
ADSB_model.py	Porject model
ADSB_trainer.py	Main trainer
loss_utils.py	Loss function utils
utils.py	Other utils
utils_common.py	Common utils
utils_visualize.py	Visualize utils

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🚀 Getting Started

Dependencies

Download motion modules and put them under ADS-B_Classification/data/.

• ADS-B Datasets: Google Drive

🔧 Installation

1. Clone the ADS-B_Classification repository:

git clone https://github.com/FMVPJet/ADS-B_Classification.git

2. Change to the project directory:

cd ADS-B_Classification

3. Install the dependencies:

pip install -r requirements.txt

🤖 Running ADS-B_Classification

customize config.yaml

🚀 Train

python main_train.py

🧪 Tests

python main_test.py

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📄 License

This project is protected under the MIT License. For more details, refer to the LICENSE file.

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👏 Acknowledgments

• JetKwok

• README.md file is created by README-AI.

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