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from __future__ import annotations
from typing import TYPE_CHECKING, Dict, List
import numpy as np
from ...data.clip.clip_process import find_idx_by_time, reset_clipseq_id
from ...data.clip.clip_fusion import fuse_clips
from ...utils.util import merge_list_continuous_same_element
if TYPE_CHECKING:
from .music_clip import MusicClip, MusicClipSeq
from .music_map import MusicMap, MusicMapSeq
# TODO: 待和clip操作做整合
def music_clip_is_short(clip: MusicClip, th: float = 3) -> bool:
"""判断音乐片段是否过短
Args:
clip (MusicClip): 待判断的音乐片段
th (float, optional): 短篇的参数. Defaults to 3.
Returns:
bool: 是或不是 短片段
"""
if clip.duration < th:
return False
else:
return True
def music_clip_timepoint_is_target(clip: MusicClip, target: list = [-1, 1, 0]) -> bool:
"""音乐片段的关键点类型是否是目标关键点
关键点类型暂时参考：VideoMashup/videomashup/data_structure/music_data_structure.py
Args:
clip (MusicClip): 待判断的音乐片段
target (list, optional): 目标关键点类别. Defaults to [-1, 1, 0].
Returns:
bool: 是还是不是
"""
timepoint = clip.timepoint_type
if isinstance(timepoint, int):
timepoint = {timepoint}
else:
timepoint = {int(x) for x in timepoint.split("_")}
if timepoint & set(target):
return True
else:
return False
def filter_clipseq_target_point(
clipseq: MusicClipSeq, target: list = [-1, 1, 0]
) -> MusicClipSeq:
"""删除目标关键点之外的点，对相应的片段做融合
Args:
clipseq (MusicClipSeq): 待处理的音乐片段序列
target (list, optional): 保留的目标关键点. Defaults to [-1, 1, 0].
Returns:
MusicClipSeq: 处理后的音乐片段序列
"""
n_clipseq = len(clipseq)
if n_clipseq == 1:
return clipseq
newclipseq = []
start_clip = clipseq[0]
if music_clip_timepoint_is_target(start_clip, target=target):
has_start_clip = True
else:
has_start_clip = False
i = 1
while i <= n_clipseq - 1:
clip = clipseq[i]
start_clip_is_target = music_clip_timepoint_is_target(start_clip, target=target)
next_clip_is_target = music_clip_timepoint_is_target(clip, target=target)
# logger.debug("filter_clipseq_target_point: i={},start={}, clip={}".format(i, start_clip["timepoint_type"], clip["timepoint_type"]))
# logger.debug("start_clip_is_target: {}, next_clip_is_target {}".format(start_clip_is_target, next_clip_is_target))
if not has_start_clip:
start_clip = clip
has_start_clip = next_clip_is_target
else:
if start_clip_is_target:
has_start_clip = True
if next_clip_is_target:
newclipseq.append(start_clip)
start_clip = clip
if i == n_clipseq - 1:
newclipseq.append(clip)
else:
start_clip = fuse_clips(start_clip, clip)
if i == n_clipseq - 1:
newclipseq.append(start_clip)
# logger.debug("filter_clipseq_target_point: fuse {}, {}".format(i, clip["timepoint_type"]))
else:
start_clip = clip
i += 1
newclipseq = reset_clipseq_id(newclipseq)
return newclipseq
def merge_musicclip_into_clipseq(
clip: MusicClipSeq, clipseq: MusicClip, th: float = 1
) -> MusicClipSeq:
"""给clipseq插入一个新的音乐片段，会根据插入后片段是否过短来判断。
Args:
clip (MusicClipSeq): 要插入的音乐片段
clipseq (MusicClip): 待插入的音乐片段序列
th (float, optional): 插入后如果受影响的片段长度过短，则放弃插入. Defaults to 1.
Returns:
MusicClipSeq: _description_
"""
n_clipseq = len(clipseq)
clip_time = clip.time_start
idx = find_idx_by_time(clipseq, clip_time)
last_clip_time_start = clipseq[idx].time_start
next_clip_time_start = clipseq[idx].time_start + clipseq[idx].duration
last_clip_time_delta = clip_time - last_clip_time_start
clip_duration = next_clip_time_start - clip_time
# TODO: 副歌片段改变th参数来提升音符密度，暂不使用，等待音游谱面
# TODO: 待抽离独立的业务逻辑为单独的函数
# 只针对副歌片段插入关键点
if clipseq[idx].text is None or (
clipseq[idx].text is not None
and clipseq[idx].stage is not None
and "C" in clipseq[idx].stage
):
if (last_clip_time_delta > th) and (clip_duration > th):
clip.duration = clip_duration
clipseq[idx].duration = last_clip_time_delta
clipseq.insert(idx + 1, clip)
clipseq = reset_clipseq_id(clipseq)
return clipseq
def merge_music_clipseq(clipseq1: MusicClipSeq, clipseq2: MusicClipSeq) -> MusicClipSeq:
"""将片段序列clipseq2融合到音乐片段序列clipseq1中。融合过程也会判断新片段长度。
Args:
clipseq1 (MusicClipSeq): 要融合的目标音乐片段序列
clipseq2 (MusicClipSeq): 待融合的音乐片段序列
Returns:
MusicClipSeq: 融合后的音乐片段序列
"""
while len(clipseq2) > 0:
clip = clipseq2[0]
clipseq1 = merge_musicclip_into_clipseq(clip, clipseq1)
del clipseq2[0]
return clipseq1
def merge_lyricseq_beatseq(
lyric_clipseq: MusicClipSeq, beat_clipseq: MusicClipSeq
) -> MusicClipSeq:
"""将beat序列融合到歌词序列中
Args:
lyric_clipseq (MusicClipSeq): 歌词序列
beat_clipseq (MusicClipSeq): beat序列
Returns:
MusicClipSeq: 融合后的音乐片段序列
"""
newclipseq = merge_music_clipseq(lyric_clipseq, beat_clipseq)
# for i, clip in enumerate(newclipseq):
# logger.debug("i={}, time_start={}, duration={}".format(i, clip.time_start, clip.duration))
return newclipseq
def get_stageseq_from_clipseq(clipseq: MusicClipSeq) -> List[Dict]:
"""对clip.stage做近邻融合，返回总时间
Returns:
List[Dict]: 根据音乐结构进行分割的片段序列
"""
stages = [clip.stage for clip in clipseq]
merge_stages_idx = merge_list_continuous_same_element(stages)
merge_stages = []
for n, stages_idx in enumerate(merge_stages_idx):
dct = {
"clipid": n,
"time_start": clipseq[stages_idx["start"]].time_start,
"time_end": clipseq[stages_idx["end"]].time_end,
"stage": stages_idx["element"],
"original_clipid": list(
range(stages_idx["start"], stages_idx["end"] + 1)
), # mss都是左闭、 右闭的方式
}
dct["duration"] = dct["time_end"] - dct["time_start"]
merge_stages.append(dct)
return merge_stages
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