- Convert image to HSV plate and apply yellow mask.
#convert HSV plate f_hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV) #add litle bit blur img_gausblur = cv.GaussianBlur(f_hsv, (3, 3), 0) # yellow hsv color range lower_blue = np.array([28, 255, 255]) upper_blue = np.array([30, 255, 255]) # treshhold on yellow yellow_mask = cv.inRange(img_gausblur, lower_blue, upper_blue)
- Find center of the image and draw circle.
center = (round(w / 2), round(h / 2)) center_top = (round((w/2)+1), round(h/7)) f_dots = cv.circle(yellow_mask, center, 5, (255,255,0), -1)
- Find coordinate and assign the values.
- coordinate of the reference point.
contours, _ = cv.findContours(yellow_mask, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE) contours = sorted(contours, key=lambda x: cv.contourArea(x), reverse=True) for i in contours: M = cv.moments(i) cX = int(M["m10"] / M["m00"]) cY = int(M["m01"] / M["m00"]) (x, y, w, h) = cv.boundingRect(i) c_ref = (cX, cY) break
- coordinate of the center of image.
- coordinate of the where you want to rotation.
- Find slop of the line that from center to reference point.
x1 = center[0] y1 = center[1] x3 = cX y3 = cY m2 = float((y3-y1) / (x3 - x1)) print('slope m2: ', m2)
- Convert slope to degree.
xtan = math.atan(m2) #radyan sonucu m2_deg = math.degrees(xtan) # dereye cevrildi
- Split image four area and detect which area the point and Rotate image by degree.
# Noktanın hangi bölgede olduğunu bul if x <w / 2 and y < h / 2: # Görüntü matrisini bir açı derecesinde döndür print("Sol üst köşe") angle = round(270 + m2_deg) rotation_image(angle) elif x < w / 2 and y >= h / 2: print("Sol alt köşe") angle = round(180 + (90 + m2_deg)) rotation_image(angle) elif x >= w / 2 and y < h / 2: print("Sağ üst köşe") angle = round(90 + m2_deg ) rotation_image(angle) else: print("Sağ alt köşe") angle = round(90 + m2_deg ) rotation_image(angle)
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Rotate the image relative to the reference point .