🤖 CBR drone landing pad Detector

This repository aims to detect the drone landing pad used in CBR (Brazilian Robtics Competition).

Use the pad_images folder to get the cbr landing pad images to test these samples

1. Detection Model

The weights generated during training are available in the /detect/weights folder. The detect/config folder contains the configuration yamls, in case you wish run this in colab, there is a config for it as well.

1.1. Dependencies

• Ultralytics
• OpenCV (cv2)

You can install the dependencies using:

pip install -U ultralytics opencv-python

1.2. Test the Model

To test the model, run the following command:

python predict_video.py

A generated video will be found in ./videos folder with the detections running. This folder also contains a base video with the cbr_pad appearing. You can use it, or, make your own video and substitute the one using same name and extension "base.mp4" in order to test it.

2. Roboflow Integration

The /roboflow folder contains a sample using the Roboflow API directly. So that, it uses a different model trained by roboflow. If you wish to test it, fllow the steps:

2.1. Dependencies used

• python-dotenv
• Roboflow
• OpenCV (cv2)
• NumPy
• Requests

Install the dependencies using:

pip install python-dotenv roboflow opencv-python numpy requests

2.2. Running Roboflow Prediction

2. Create a .env file in the root and fill in the values:

ROBOFLOW_API_KEY="YOUR_ROBOFLOW_API_KEY"
ROBOFLOW_MODEL="cbr_base_detector_test/version_you_wish"
ROBOFLOW_PROJECT="cbr_base_detector_test"

3. Run the Roboflow prediction script:

python roboflow_predict.py