Based Class of Motion Field Estimators

Change-Id: Id01ce15273c0cab0cd61d064099d200708360265

tools/3D-Reconstruction/MotionEST/Util.py

@@ -0,0 +1,37 @@
+#!/usr/bin/env python
+# coding: utf-8
+import numpy as np
+import numpy.linalg as LA
+import matplotlib.pyplot as plt
+from scipy.ndimage import filters
+from PIL import Image, ImageDraw
+
+
+def MSE(blk1, blk2):
+  return np.mean(
+      LA.norm(
+          np.array(blk1, dtype=np.int) - np.array(blk2, dtype=np.int), axis=2))
+
+
+def drawMF(img, blk_sz, mf):
+  img_rgba = img.convert('RGBA')
+  mf_layer = Image.new(mode='RGBA', size=img_rgba.size, color=(0, 0, 0, 0))
+  draw = ImageDraw.Draw(mf_layer)
+  width = img_rgba.size[0]
+  height = img_rgba.size[1]
+  num_row = height // blk_sz
+  num_col = width // blk_sz
+  for i in xrange(num_row):
+    left = (0, i * blk_sz)
+    right = (width, i * blk_sz)
+    draw.line([left, right], fill=(0, 0, 255, 255))
+  for j in xrange(num_col):
+    up = (j * blk_sz, 0)
+    down = (j * blk_sz, height)
+    draw.line([up, down], fill=(0, 0, 255, 255))
+  for i in xrange(num_row):
+    for j in xrange(num_col):
+      center = (j * blk_sz + 0.5 * blk_sz, i * blk_sz + 0.5 * blk_sz)
+      head = (center[0] + mf[i, j][1], center[1] + mf[i, j][0])
+      draw.line([center, head], fill=(255, 0, 0, 255))
+  return Image.alpha_composite(img_rgba, mf_layer)