1 files changed, 69 insertions, 0 deletions
diff --git a/utils/raspberrypi/ctt/ctt_ransac.py b/utils/raspberrypi/ctt/ctt_ransac.py
new file mode 100644
index 00000000..e7c57137
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+++ b/utils/raspberrypi/ctt/ctt_ransac.py
@@ -0,0 +1,69 @@
+# SPDX-License-Identifier: BSD-2-Clause
+#
+# Copyright (C) 2019, Raspberry Pi (Trading) Limited
+#
+# ctt_ransac.py - camera tuning tool RANSAC selector for Macbeth chart locator
+
+import numpy as np
+
+scale = 2
+
+"""
+constructs normalised macbeth chart corners for ransac algorithm
+"""
+def get_square_verts(c_err = 0.05,scale = scale):
+    """
+    define macbeth chart corners
+    """
+    b_bord_x,b_bord_y = scale*8.5,scale*13
+    s_bord = 6*scale
+    side = 41*scale
+    x_max = side*6 + 5*s_bord + 2*b_bord_x
+    y_max = side*4 + 3*s_bord + 2*b_bord_y
+    c1 = (0,0)
+    c2 = (0,y_max)
+    c3 = (x_max,y_max)
+    c4 = (x_max,0)
+    mac_norm = np.array((c1,c2,c3,c4),np.float32)
+    mac_norm = np.array([ mac_norm ])
+
+    square_verts = []
+    square_0 = np.array(((0,0),(0,side),
+                (side,side),(side,0)),np.float32)
+    offset_0 = np.array((b_bord_x,b_bord_y),np.float32)
+    c_off = side * c_err
+    offset_cont = np.array(((c_off,c_off),(c_off,-c_off),
+                (-c_off,-c_off),(-c_off,c_off)),np.float32)
+    square_0 += offset_0
+    square_0 += offset_cont
+    """
+    define macbeth square corners
+    """
+    for i in range(6):
+        shift_i = np.array(((i*side,0),(i*side,0),
+                    (i*side,0),(i*side,0)),np.float32)
+        shift_bord =np.array(((i*s_bord,0),(i*s_bord,0),
+                    (i*s_bord,0),(i*s_bord,0)),np.float32)
+        square_i = square_0 + shift_i + shift_bord
+        for j in range(4):
+            shift_j = np.array(((0,j*side),(0,j*side),
+                    (0,j*side),(0,j*side)),np.float32)
+            shift_bord = np.array(((0,j*s_bord),
+                    (0,j*s_bord),(0,j*s_bord),
+                    (0,j*s_bord)),np.float32)
+            square_j = square_i + shift_j + shift_bord
+            square_verts.append(square_j)
+    # print('square_verts')
+    # print(square_verts)
+    return np.array(square_verts,np.float32),mac_norm
+
+def get_square_centres(c_err = 0.05,scale=scale):
+    """
+    define macbeth square centres
+    """
+    verts,mac_norm = get_square_verts(c_err,scale=scale)
+
+    centres = np.mean(verts,axis = 1)
+    # print('centres')
+    # print(centres)
+    return np.array(centres,np.float32)