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import numpy as np | |
from modelscope.models.cv.cartoon.facelib.config import config as cfg | |
class GroupTrack(): | |
def __init__(self): | |
self.old_frame = None | |
self.previous_landmarks_set = None | |
self.with_landmark = True | |
self.thres = cfg.TRACE.pixel_thres | |
self.alpha = cfg.TRACE.smooth_landmark | |
self.iou_thres = cfg.TRACE.iou_thres | |
def calculate(self, img, current_landmarks_set): | |
if self.previous_landmarks_set is None: | |
self.previous_landmarks_set = current_landmarks_set | |
result = current_landmarks_set | |
else: | |
previous_lm_num = self.previous_landmarks_set.shape[0] | |
if previous_lm_num == 0: | |
self.previous_landmarks_set = current_landmarks_set | |
result = current_landmarks_set | |
return result | |
else: | |
result = [] | |
for i in range(current_landmarks_set.shape[0]): | |
not_in_flag = True | |
for j in range(previous_lm_num): | |
if self.iou(current_landmarks_set[i], | |
self.previous_landmarks_set[j] | |
) > self.iou_thres: | |
result.append( | |
self.smooth(current_landmarks_set[i], | |
self.previous_landmarks_set[j])) | |
not_in_flag = False | |
break | |
if not_in_flag: | |
result.append(current_landmarks_set[i]) | |
result = np.array(result) | |
self.previous_landmarks_set = result | |
return result | |
def iou(self, p_set0, p_set1): | |
rec1 = [ | |
np.min(p_set0[:, 0]), | |
np.min(p_set0[:, 1]), | |
np.max(p_set0[:, 0]), | |
np.max(p_set0[:, 1]) | |
] | |
rec2 = [ | |
np.min(p_set1[:, 0]), | |
np.min(p_set1[:, 1]), | |
np.max(p_set1[:, 0]), | |
np.max(p_set1[:, 1]) | |
] | |
# computing area of each rectangles | |
S_rec1 = (rec1[2] - rec1[0]) * (rec1[3] - rec1[1]) | |
S_rec2 = (rec2[2] - rec2[0]) * (rec2[3] - rec2[1]) | |
# computing the sum_area | |
sum_area = S_rec1 + S_rec2 | |
# find the each edge of intersect rectangle | |
x1 = max(rec1[0], rec2[0]) | |
y1 = max(rec1[1], rec2[1]) | |
x2 = min(rec1[2], rec2[2]) | |
y2 = min(rec1[3], rec2[3]) | |
# judge if there is an intersect | |
intersect = max(0, x2 - x1) * max(0, y2 - y1) | |
iou = intersect / (sum_area - intersect) | |
return iou | |
def smooth(self, now_landmarks, previous_landmarks): | |
result = [] | |
for i in range(now_landmarks.shape[0]): | |
x = now_landmarks[i][0] - previous_landmarks[i][0] | |
y = now_landmarks[i][1] - previous_landmarks[i][1] | |
dis = np.sqrt(np.square(x) + np.square(y)) | |
if dis < self.thres: | |
result.append(previous_landmarks[i]) | |
else: | |
result.append( | |
self.do_moving_average(now_landmarks[i], | |
previous_landmarks[i])) | |
return np.array(result) | |
def do_moving_average(self, p_now, p_previous): | |
p = self.alpha * p_now + (1 - self.alpha) * p_previous | |
return p | |