How To Map Rectangle Image To Quadrilateral With Pil?

Python PIL library allows me to map any quadrilateral in an image to rectangle using im.transform(size, QUAD, data) What I need is a function that does the opposite, i.e. map a re

Solution 1:

So I solved the issue with a simple forward mapping, rather than inverse mapping, which is usually better, but in my application I only ever map the rectangle to a quad that is smaller than the rectangle, so there are usually no holes in the transformed image. The code is as follows:

def reverse_quad_transform(image, quad_to_map_to, alpha):
  # forward mapping, for simplicity

  result = Image.new("RGBA",image.size)
  result_pixels = result.load()

  width, height = result.size

  for y in range(height):
    for x in range(width):
      result_pixels[x,y] = (0,0,0,0)

  p1 = (quad_to_map_to[0],quad_to_map_to[1])
  p2 = (quad_to_map_to[2],quad_to_map_to[3])
  p3 = (quad_to_map_to[4],quad_to_map_to[5])
  p4 = (quad_to_map_to[6],quad_to_map_to[7])

  p1_p2_vec = (p2[0] - p1[0],p2[1] - p1[1])
  p4_p3_vec = (p3[0] - p4[0],p3[1] - p4[1])

  for y in range(height):
    for x in range(width):
      pixel = image.getpixel((x,y))

      y_percentage = y / float(height)
      x_percentage = x / float(width)

      # interpolate vertically
      pa = (p1[0] + p1_p2_vec[0] * y_percentage, p1[1] + p1_p2_vec[1] * y_percentage) 
      pb = (p4[0] + p4_p3_vec[0] * y_percentage, p4[1] + p4_p3_vec[1] * y_percentage)

      pa_to_pb_vec = (pb[0] - pa[0],pb[1] - pa[1])

      # interpolate horizontally
      p = (pa[0] + pa_to_pb_vec[0] * x_percentage, pa[1] + pa_to_pb_vec[1] * x_percentage)

      try:
        result_pixels[p[0],p[1]] = (pixel[0],pixel[1],pixel[2],min(int(alpha * 255),pixel[3]))
      except Exception:
        pass

  return result