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autonomous_vehicle_project_1

https://github.com/harighs/autonomous_vehicle_project_1

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.0%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: Harighs
  • License: agpl-3.0
  • Language: Python
  • Default Branch: main
  • Size: 167 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 2
  • Releases: 0
Created almost 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Contributing License Citation

README.md

Checking the notebooks:

Due to nature of the architecture and inbuilt dependencies of the python script providing one single jupyter notebook is not feasible. so we share our repository so that you can clone and run the code on your local machine.

  1. Clone the repository using the following command git clone https://github.com/Harighs/autonomous_vechicle_project_1.git

  2. Install the required dependencies using the following command pip install -r requirements.txt

  3. Open the notebook called 'Training_Notebook.ipynb' and run the cells to train the model.

  4. Trained using Nvidia 4050ti (12Gb VRAM)

For running the training:

  1. First install the required dependencies using the following command pip install -r requirements.txt

  2. Run the following command to train the model python train.py --data_path <path to the data folder> --model_path <path to save the model> --batch_size <batch size> --epochs <number of epochs> eg: python train.py --data data/dataset/data.yaml --cfg models/yolov5s.yaml --epochs 1 --weights '' --batch-size 32 --name repo_testing

For running the Validation:

  1. First install the required dependencies using the following command pip install -r requirements.txt
  2. Run the following command to validate the model python val.py --data_path <path to the data folder> --model_path <path to the model> --batch_size <batch size> eg: python val.py --data data/dataset/data.yaml --weights runs/train/repo_testing/weights/best.pt --batch-size 32

Owner

  • Name: Hari Shankar
  • Login: Harighs
  • Kind: user
  • Location: Vienna
  • Company: Research Technician

Mechanical Engineer | 3D Printing | Machine Learning | Data Science | Industry 4.0

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Dependencies

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.github/workflows/stale.yml actions
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