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## Copyright (c) 2020 The WebM project authors. All Rights Reserved.
##
## Use of this source code is governed by a BSD-style license
## that can be found in the LICENSE file in the root of the source
## tree. An additional intellectual property rights grant can be found
## in the file PATENTS. All contributing project authors may
## be found in the AUTHORS file in the root of the source tree.
##
#coding : utf - 8
import numpy as np
import numpy.linalg as LA
import matplotlib.pyplot as plt
from Util import drawMF, MSE
"""The Base Class of Estimators"""
class MotionEST(object):
"""
constructor:
cur_f: current frame
ref_f: reference frame
blk_sz: block size
"""
def __init__(self, cur_f, ref_f, blk_sz):
self.cur_f = cur_f
self.ref_f = ref_f
self.blk_sz = blk_sz
#convert RGB to YUV
self.cur_yuv = np.array(self.cur_f.convert('YCbCr'), dtype=int)
self.ref_yuv = np.array(self.ref_f.convert('YCbCr'), dtype=int)
#frame size
self.width = self.cur_f.size[0]
self.height = self.cur_f.size[1]
#motion field size
self.num_row = self.height // self.blk_sz
self.num_col = self.width // self.blk_sz
#initialize motion field
self.mf = np.zeros((self.num_row, self.num_col, 2))
"""estimation function Override by child classes"""
def motion_field_estimation(self):
pass
"""
distortion of a block:
cur_r: current row
cur_c: current column
mv: motion vector
metric: distortion metric
"""
def block_dist(self, cur_r, cur_c, mv, metric=MSE):
cur_x = cur_c * self.blk_sz
cur_y = cur_r * self.blk_sz
h = min(self.blk_sz, self.height - cur_y)
w = min(self.blk_sz, self.width - cur_x)
cur_blk = self.cur_yuv[cur_y:cur_y + h, cur_x:cur_x + w, :]
ref_x = int(cur_x + mv[1])
ref_y = int(cur_y + mv[0])
if 0 <= ref_x < self.width - w and 0 <= ref_y < self.height - h:
ref_blk = self.ref_yuv[ref_y:ref_y + h, ref_x:ref_x + w, :]
else:
ref_blk = np.zeros((h, w, 3))
return metric(cur_blk, ref_blk)
"""
distortion of motion field
"""
def distortion(self, mask=None, metric=MSE):
loss = 0
count = 0
for i in xrange(self.num_row):
for j in xrange(self.num_col):
if mask is not None and mask[i, j]:
continue
loss += self.block_dist(i, j, self.mf[i, j], metric)
count += 1
return loss / count
"""evaluation compare the difference with ground truth"""
def motion_field_evaluation(self, ground_truth):
loss = 0
count = 0
gt = ground_truth.mf
mask = ground_truth.mask
for i in xrange(self.num_row):
for j in xrange(self.num_col):
if mask is not None and mask[i][j]:
continue
loss += LA.norm(gt[i, j] - self.mf[i, j])
count += 1
return loss / count
"""render the motion field"""
def show(self, ground_truth=None, size=10):
cur_mf = drawMF(self.cur_f, self.blk_sz, self.mf)
if ground_truth is None:
n_row = 1
else:
gt_mf = drawMF(self.cur_f, self.blk_sz, ground_truth)
n_row = 2
plt.figure(figsize=(n_row * size, size * self.height / self.width))
plt.subplot(1, n_row, 1)
plt.imshow(cur_mf)
plt.title('Estimated Motion Field')
if ground_truth is not None:
plt.subplot(1, n_row, 2)
plt.imshow(gt_mf)
plt.title('Ground Truth')
plt.tight_layout()
plt.show()
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