Car snippet / Speed estimation

[AbdullahHabib-github]

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Question

Hey!
I'm trying to get the snippets of cars that cross a certain speed, how do i do that?
(I tried a few resources but all in vain, i'm getting overwhelmed and any help is appreciated)
Thank you so much for helping.

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[github-actions]

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[glenn-jocher]

Hey! 👋

To tackle extracting car snippets based on speed estimation with YOLOv8, you'd typically first need to detect the cars and then estimate their speed. Here's a simplified approach:

1. Detect cars using YOLOv8. Ensure your model is trained for car detection or use a pre-trained model that can detect cars.

2. Estimate Speed: This can be complex, requiring additional steps like:

   • Establishing a frame of reference in your videos.
   • Calculating the pixel distance traveled by cars between frames.
   • Converting this to real-world speed (you might need camera calibration and frame rate data for this).

3. Extract snippets: Once cars exceeding a certain speed are identified, extract these video snippets for further use or analysis.

Here’s a basic snippet for detecting cars with YOLOv8:

from ultralytics import YOLO

# Load the pretrained model
model = YOLO('yolov8n.pt') 

# Run detection
results = model('traffic_video.mp4') 

# Processing the results
for frame in results:
    for *xyxy, conf, cls in frame.pred:
        if model.names[int(cls)] == 'car' and meets_speed_criteria(xyxy):
            save_frame(frame)  # Define your function to check speed and save frames

You'd need to develop the meets_speed_criteria function based on how you compute speed.

Since specific implementations can vary greatly, further reading on motion analysis and possibly consulting with a computer vision expert could be very beneficial. Always here to help if you need more info! 🚗💨

[github-actions]

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