YOLO_object dectection.py

from ultralytics import YOLO
import pyrealsense2 as rs
import numpy as np
import cv2
import serial

#load the model
model = YOLO('yolov8n.pt')

#for camera feed
# Configure depth and color streams
pipeline = rs.pipeline()
config = rs.config()
#config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)

# Start streaming
pipeline.start(config)

try:
    while True:
        # Wait for a coherent pair of frames: depth and color
        frames = pipeline.wait_for_frames()
        #depth_frame = frames.get_depth_frame()
        color_frame = frames.get_color_frame()
        
        if not color_frame:
            continue
        
        # Convert images to numpy arrays
        #depth_image = np.asanyarray(depth_frame.get_data())
        color_image = np.asanyarray(color_frame.get_data())
        
        # Apply colormap on depth image (optional)
        #depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
        
        #for tracking the object from the frame
        results = model.track(color_image, persist=True)

        #to find coordinate of center of detected object
        for result in results:
            boxes = result.boxes.cpu().numpy()
            xyxys = boxes.xyxy
            class_ids = boxes.cls

            #now lets seperate all the bounding box in one frame
            for class_id, xyxy in zip(class_ids, xyxys):
                if class_id == 67:
                    x1, y1, x2, y2 = xyxy
                    x_center = int(x1 + (abs(x1-x2)) / 2)
                    y_center = int(y1 + (abs(y1-y2)) / 2)
                    print(x_center, y_center, class_id)
                    cv2.circle(color_image, (x_center, y_center), radius=3, color=(0, 0, 0), thickness=-1)

        object_detection_frame = results[0].plot()

        # Show images
        cv2.imshow('RGB Image', color_image)
        #cv2.imshow('object detection', object_detection_frame)
        
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

finally:
    # Stop streaming
    pipeline.stop()
    cv2.destroyAllWindows()