Week 4

WEEK 4

Color Filter Exercise

With Ros Node

• I have managed to get a version of this exercise using a ros node to capture the image.
• I have tested the operation with an object tracking to see the performance. The code used is:

    from GUI import GUI
    import cv2
    import numpy as np
    # Enter sequential code!
      
    while True:
        frame = WebrtcFrame.getImage()
        image_blur = cv2.GaussianBlur(frame, (21, 21), sigmaX=0)
        image_hsv = cv2.cvtColor(image_blur, cv2.COLOR_BGR2HSV)
        lower_color = np.array([29,43,126], dtype='uint8')
        upper_color = np.array([88, 255, 255], dtype='uint8')
        mask = cv2.inRange(image_hsv, lower_color, upper_color)
          
        kernel = np.ones((3, 3), np.uint8)
        erosion = cv2.erode(mask, kernel, iterations=2)
        dilation = cv2.dilate(erosion, kernel, iterations=2)
      
        contours, hierarchy = cv2.findContours(dilation, cv2.RETR_LIST , cv2.CHAIN_APPROX_SIMPLE)
      
      
        areas = [cv2.contourArea(c) for c in contours]
          
        if len(areas) > 0:
            ind_area_max = np.argmax(areas)  # indice del contorno con mayor area
          
            # Coordenadas del circulo que engloba a el objetivo
            (x, y), radius = cv2.minEnclosingCircle(contours[ind_area_max])
            radius = int(radius)
            center = (int(x), int(y))
            cv2.circle(frame, center, radius, (0, 0, 255), 2)
      
        GUI.showImage(frame)
  

• You can see how you get a lower delay in the image compared to WebRtc.

• Exercise Color-Filter with Ros Node