How can I go about trying to order the items of a picture from top left to bottom right, such as in the image below? Currently receiving this error with the following code .
Error:
a = sorted(keypoints, key=lambda p: (p[0]) + (p1))[0] # find upper left point ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
This question is modelled from this: Ordering coordinates from top left to bottom right
def preprocess(img):
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img_blur = cv2.GaussianBlur(img_gray, (5, 5), 1)
img_canny = cv2.Canny(img_blur, 50, 50)
kernel = np.ones((3, 3))
img_dilate = cv2.dilate(img_canny, kernel, iterations=2)
img_erode = cv2.erode(img_dilate, kernel, iterations=1)
return img_erode
image_final = preprocess(picture_example.png)
keypoints, hierarchy = cv2.findContours(image_final, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
points = []
while len(keypoints) > 0:
a = sorted(keypoints, key=lambda p: (p[0]) + (p[1]))[0] # find upper left point
b = sorted(keypoints, key=lambda p: (p[0]) - (p[1]))[-1] # find upper right point
cv2.line(image_final, (int(a.pt[0]), int(a.pt[1])), (int(b.pt[0]), int(b.pt[1])), (255, 0, 0), 1)
# convert opencv keypoint to numpy 3d point
a = np.array([a.pt[0], a.pt[1], 0])
b = np.array([b.pt[0], b.pt[1], 0])
row_points = []
remaining_points = []
for k in keypoints:
p = np.array([k.pt[0], k.pt[1], 0])
d = k.size # diameter of the keypoint (might be a theshold)
dist = np.linalg.norm(np.cross(np.subtract(p, a), np.subtract(b, a))) / np.linalg.norm(b) # distance between keypoint and line a->b
if d/2 > dist:
row_points.append(k)
else:
remaining_points.append(k)
points.extend(sorted(row_points, key=lambda h: h.pt[0]))
keypoints= remaining_points
New Picture:
Reference Ordering Picture:
Will use center of mass to determine center point ordering.
from Python: Sorting items from top left to bottom right with OpenCV


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