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# Copyright (2025) Bytedance Ltd. and/or its affiliates
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
def compute_scale_and_shift(prediction, target, mask, scale_only=False):
if scale_only:
return compute_scale(prediction, target, mask), 0
else:
return compute_scale_and_shift_full(prediction, target, mask)
def compute_scale(prediction, target, mask):
# system matrix: A = [[a_00, a_01], [a_10, a_11]]
prediction = prediction.astype(np.float32)
target = target.astype(np.float32)
mask = mask.astype(np.float32)
a_00 = np.sum(mask * prediction * prediction)
a_01 = np.sum(mask * prediction)
a_11 = np.sum(mask)
# right hand side: b = [b_0, b_1]
b_0 = np.sum(mask * prediction * target)
x_0 = b_0 / (a_00 + 1e-6)
return x_0
def compute_scale_and_shift_full(prediction, target, mask):
# system matrix: A = [[a_00, a_01], [a_10, a_11]]
prediction = prediction.astype(np.float32)
target = target.astype(np.float32)
mask = mask.astype(np.float32)
a_00 = np.sum(mask * prediction * prediction)
a_01 = np.sum(mask * prediction)
a_11 = np.sum(mask)
b_0 = np.sum(mask * prediction * target)
b_1 = np.sum(mask * target)
x_0 = 1
x_1 = 0
det = a_00 * a_11 - a_01 * a_01
if det != 0:
x_0 = (a_11 * b_0 - a_01 * b_1) / det
x_1 = (-a_01 * b_0 + a_00 * b_1) / det
return x_0, x_1
def get_interpolate_frames(frame_list_pre, frame_list_post):
assert len(frame_list_pre) == len(frame_list_post)
min_w = 0.0
max_w = 1.0
step = (max_w - min_w) / (len(frame_list_pre)-1)
post_w_list = [min_w] + [i * step for i in range(1,len(frame_list_pre)-1)] + [max_w]
interpolated_frames = []
for i in range(len(frame_list_pre)):
interpolated_frames.append(frame_list_pre[i] * (1-post_w_list[i]) + frame_list_post[i] * post_w_list[i])
return interpolated_frames |