def compute_regression_targets(self, gt_list, fg_thresh):
if self.best_iou < fg_thresh:
# background proposals do not need this
return
# find the groundtruth instance with the highest IOU
ious = [temporal_iou((self.start_frame, self.end_frame), (gt.start_frame, gt.end_frame)) for gt in gt_list]
best_gt_id = np.argmax(ious)
best_gt = gt_list[best_gt_id]
prop_center = (self.start_frame + self.end_frame) / 2
gt_center = (best_gt.start_frame + best_gt.end_frame) / 2
prop_size = self.end_frame - self.start_frame + 1
gt_size = best_gt.end_frame - best_gt.start_frame + 1
# get regression target:
# (1). center shift propotional to the proposal duration
# (2). logarithm of the groundtruth duration over proposal duraiton
self.loc_reg = (gt_center - prop_center) / prop_size
try:
self.size_reg = math.log(gt_size / prop_size)
except:
print(gt_size, prop_size, self.start_frame, self.end_frame)
raise
def compute_regression_targets(self, gt_list, fg_thresh):
if self.best_iou < fg_thresh:
# background proposals do not need this
return
# find the groundtruth instance with the highest IOU
ious = [temporal_iou((self.start_frame, self.end_frame), (gt.start_frame, gt.end_frame)) for gt in gt_list]
best_gt_id = np.argmax(ious)
best_gt = gt_list[best_gt_id]
prop_center = (self.start_frame + self.end_frame) / 2
gt_center = (best_gt.start_frame + best_gt.end_frame) / 2
prop_size = self.end_frame - self.start_frame + 1
gt_size = best_gt.end_frame - best_gt.start_frame + 1
# get regression target:
# (1). center shift propotional to the proposal duration
# (2). logarithm of the groundtruth duration over proposal duraiton
self.loc_reg = (gt_center - prop_center) / prop_size
try:
self.size_reg = math.log(gt_size / prop_size)
except:
print(gt_size, prop_size, self.start_frame, self.end_frame)
raise
