Robustly crop rotated bounding box on photos

Question

I\'m trying to extract the rotated bounding box of contours robustly. I would like to take an image, find the largest contour, get its rotated bounding box, rotate the image

Answer 1

After some research, this is what I get:

This is how I get it:

• pad the original image on each side (500 pixels in my case)
• find the four corner points of the shoe (the four points should form a polygon enclosing the shoe, but do not need to be exact rectangle)
• employing the code here to crop the shoe:

img = cv2.imread("padded_shoe.jpg")
# four corner points for padded shoe
cnt = np.array([
    [[313, 794]],
    [[727, 384]],
    [[1604, 1022]],
    [[1304, 1444]]
])
print("shape of cnt: {}".format(cnt.shape))
rect = cv2.minAreaRect(cnt)
print("rect: {}".format(rect))

box = cv2.boxPoints(rect)
box = np.int0(box)
width = int(rect[1][0])
height = int(rect[1][1])

src_pts = box.astype("float32")
dst_pts = np.array([[0, height-1],
                    [0, 0],
                    [width-1, 0],
                    [width-1, height-1]], dtype="float32")
M = cv2.getPerspectiveTransform(src_pts, dst_pts)
warped = cv2.warpPerspective(img, M, (width, height))

Cheers, hope it helps.