Individual assignment for course Autonomous Flight of Micro Air Vehicles 2020/2021
Requirements: OpenCV, PyTorch, Jupyter Notebook
Put the dataset WashingtonOBRace under the repo. Download saved models: https://drive.google.com/drive/folders/1_L6Vzn01lf_hUjFGckGz6qNewVFDrCHq?usp=sharing. Then put them in the folder learned_weights/ in the repo root directory.
The codes is with the same structure of the report. For only checking the proposed method(report section 3), just run gate_detection.ipynb.
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Report section 2.1
gate_detection_orb.ipynb: explore the ORB features extraction method(if it works, filter good matches, visualize, etc)gate_detection_orb_test.ipynb: finally test the ORB features method(computational effort, ROC curve)
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Report section 2.2
gate_detection_cnn.ipynb: explore the binary classification method. Skip the node for training the model, and later in the code 'learned_weights/gate_det_cnn.pt' is loaded for testing. Actually for avoiding accidentally starting training I have commented them.
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Report section 2.3
gate_detection_maskrcnn.ipynb: explore the Mask R-CNN method. Skip the node for training the model, and later in the code 'learned_weights/gate_det_maskrcnn' is loaded for testing
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Report section 3
gate_detection.ipynb: test the final proposed method. Run the notebook step by step