///|
/// Verifies if outer ring of sampled grid is predominantly a black border.
pub fn verify_black_border(
  sampled_grid : Image,
  total_cells : Int,
  black_threshold : Int,
) -> Bool {
  let cell_w = sampled_grid.width.to_double() / total_cells.to_double()
  let cell_h = sampled_grid.height.to_double() / total_cells.to_double()

  let mut total_border_pixels = 0
  let mut black_border_pixels = 0

  for row in 0..= 0.75
}

///|
/// Extracts binary grid payload bits from inner cells of sampled grid.
pub fn sample_payload_bits(
  sampled_grid : Image,
  dict : MarkerDictionary,
  binary_threshold : Int,
) -> Int64 {
  let data_size = dict.grid_size
  let total_cells = data_size + 2

  let cell_w = sampled_grid.width.to_double() / total_cells.to_double()
  let cell_h = sampled_grid.height.to_double() / total_cells.to_double()

  let mut payload = 0L

  for r in 0..= binary_threshold { 1L } else { 0L }

      let bit_idx = r * data_size + c
      if bit == 1L {
        payload = payload | (1L << bit_idx)
      }
    }
  }

  payload
}

///|
/// Rotates 4 corners of a quad according to 90-degree rotation index.
pub fn rotate_quad_corners(quad : Quad, rotation_index : Int) -> Quad {
  if quad.corners.length() != 4 {
    return quad
  }

  let rot = (4 - rotation_index % 4) % 4
  let rotated = [
    quad.corners[rot],
    quad.corners[(rot + 1) % 4],
    quad.corners[(rot + 2) % 4],
    quad.corners[(rot + 3) % 4],
  ]

  { corners: rotated }
}

///|
/// Full decoding pipeline for a single candidate quad.
pub fn decode_quad_marker(
  src_img : Image,
  quad : Quad,
  dict : MarkerDictionary,
) -> MarkerDetection? {
  let total_cells = dict.grid_size + 2
  let sample_res = total_cells * 8

  match warp_perspective_grid(src_img, quad, sample_res) {
    Some(sampled) => {
      let otsu_lvl = threshold_otsu(sampled)
      let level = if otsu_lvl < 10 || otsu_lvl > 245 { 128 } else { otsu_lvl }
      let binarized = threshold_global(sampled, level)

      if !verify_black_border(binarized, total_cells, 128) {
        return None
      }

      let payload_bits = sample_payload_bits(binarized, dict, 128)
      match dict.find_best_match(payload_bits) {
        Some((id, rot_idx, hamming_dist)) => {
          let aligned_quad = rotate_quad_corners(quad, rot_idx)
          Some({
            id,
            quad: aligned_quad,
            pose: None,
            rotation_index: rot_idx,
            hamming_distance: hamming_dist,
          })
        }
        None => None
      }
    }
    None => None
  }
}

///|
/// Detects all fiducial markers in an image using dictionary.
pub fn detect_markers(
  img : Image,
  dict : MarkerDictionary,
) -> Array[MarkerDetection] {
  let binarized = threshold_adaptive(img, 31, 7)
  let contours = find_contours(binarized, 20)
  let min_area = (img.width * img.height).to_double() * 0.0005
  let min_perim = (img.width + img.height).to_double() * 0.05

  let quads = extract_quad_candidates(contours, min_area, min_perim)
  let detections = Array::new()

  for i in 0.. detections.push(det)
      None => ()
    }
  }

  detections
}