Question regarding mobile app and object detection about ultralytics HOT 3 CLOSED

Hello! Thanks for sharing your innovative idea for the hackathon! It's great to see how you plan to use YOLO for helping people with visual impairment. Incorporating distance estimation and feedback mechanisms like vibration or natural language processing sounds like a promising approach.

For estimating distance, one common method is to use the known dimensions of an object and the size of its bounding box in the image. However, this requires a calibrated setup because distance perception can vary significantly depending on the camera specs (like focal length) and the actual size of the object.

Here’s a simplified pseudocode snippet to get you started with a distance estimation approach based on the size of the bounding box. Keep in mind this is quite basic and may need calibration for practical accuracy:

def estimate_distance(box_width, focal_length, known_width):
    # Simple distance formula: D = (W * F) / P
    distance = (known_width * focal_length) / box_width
    return distance

To integrate this, you would need the focal length of your camera (which you can calibrate manually or find in the camera specs), and the actual width of the object in some consistent unit.

To warn the user as they approach an object, you could set a threshold distance and use a TTS library when the threshold is crossed:

import pyttsx3  # Text-to-Speech conversion library

def warn_user(distance, threshold):
    if distance < threshold:
        engine = pyttsx3.init()
        engine.say("Caution, object nearby!")
        engine.runAndWait()

You would call warn_user(distance, threshold) inside your loop where bounding boxes are processed.

These samples are basic and may require modification to fit the exact needs of your application, such as dynamic adjustment according to different object sizes or different feedback mechanisms based on user preferences.

Good luck with your project at the hackathon, and feel free to reach back out if you need further assistance! 🚀

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@anishka07 great to hear that you’ve resolved it! If you have any more questions or need further assistance in the future, just let us know. Happy coding! 😊🚀

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