How do I get the coordinates of detected objects in yolov8 in real time and print? about ultralytics

[github-actions]

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pip install ultralytics

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[glenn-jocher]

Hello,

Thank you for reaching out with your question. It looks like there's a small issue in the way you're trying to access the detection results. In YOLOv8, the results from the model prediction are stored in a Results object, not directly as a list. Here's how you can modify your code to correctly access and print the bounding box coordinates:

from ultralytics import YOLO

# Load a pretrained YOLOv8n model
model = YOLO('best.pt')

# Run prediction
results = model('WEED100151.jpg')

# Loop through detections
for result in results:
    for det in result.boxes:
        x1, y1, x2, y2 = det.xyxy.int().tolist()  # Bounding box coordinates
        print(f"Coordinates: {x1}, {y1}, {x2}, {y2}")

result.show()  # Display the image with bounding boxes

Make sure to iterate over results and then access boxes for each result. This should resolve the AttributeError you're encountering.

If you have any more questions or need further assistance, feel free to ask. Happy coding! 🚀

[jules-cp]

Thank you very much for the help, I tested the code you provided me, but I got the following error:

x1, y1, x2, y2 = det.xyxy.int().tolist()  # Bounding box coordinates

ValueError: not enough values to unpack (expected 4, got 1)

I don't know if it's a problem with the image I'm using for the test or if it's a code problem?

[jules-cp]

I add an example of the object that I am detecting and that I want to obtain its coordinates

[glenn-jocher]

@jules-cp hello,

Thank you for providing the image example! It helps in understanding the context better. The issue you're encountering is likely due to the way the bounding box coordinates are being accessed. Let's refine the code to ensure it works correctly.

Here's an updated version of the code that should correctly extract and print the bounding box coordinates:

from ultralytics import YOLO

# Load a pretrained YOLOv8n model
model = YOLO('best.pt')

# Run prediction
results = model('WEED100151.jpg')

# Loop through detections
for result in results:
    for box in result.boxes:
        x1, y1, x2, y2 = box.xyxy[0].int().tolist()  # Bounding box coordinates
        print(f"Coordinates: {x1}, {y1}, {x2}, {y2}")

result.show()  # Display the image with bounding boxes

In this code, box.xyxy[0].int().tolist() ensures that we are correctly accessing the bounding box coordinates.

If the issue persists, please ensure you are using the latest versions of torch and ultralytics. You can upgrade them using the following commands:

pip install --upgrade torch ultralytics

If you continue to experience issues, could you please provide a minimum reproducible example? This will help us investigate the problem more effectively. You can find guidelines for creating a minimum reproducible example here.

Feel free to reach out if you have any more questions or need further assistance. We're here to help! 😊

[github-actions]

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