change nodes
This commit is contained in:
dseditor
File diff suppressed because it is too large
Load Diff
@@ -917,177 +917,144 @@ class SaveVideoPath:
|
||||
metadata=saved_metadata
|
||||
)
|
||||
|
||||
return (full_path,)
|
||||
|
||||
class TimestampToLrcNode:
|
||||
return (full_path,)
|
||||
|
||||
class FrameMatch:
|
||||
"""
|
||||
ComfyUI節點：將時間戳格式轉換為LRC歌詞格式
|
||||
調整圖像序列到指定幀數的節點
|
||||
如果目標幀數大於輸入幀數，會重複最後一幀來補齊
|
||||
如果目標幀數小於輸入幀數，會截取前面的幀
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"input_text": ("STRING", {
|
||||
"multiline": True,
|
||||
"default": ""
|
||||
"images": ("IMAGE",), # 輸入圖像序列
|
||||
"target_frames": ("INT", {
|
||||
"default": 100,
|
||||
"min": 1,
|
||||
"max": 10000,
|
||||
"step": 1,
|
||||
"tooltip": "目標幀數"
|
||||
}),
|
||||
},
|
||||
"optional": {
|
||||
"fill_mode": (["repeat_last", "loop", "bounce"], {
|
||||
"default": "repeat_last",
|
||||
"tooltip": "填充模式：repeat_last=重複最後一幀，loop=循環播放，bounce=來回播放"
|
||||
}),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("lrc_output",)
|
||||
FUNCTION = "convert_to_lrc"
|
||||
CATEGORY = "text/processing"
|
||||
RETURN_TYPES = ("IMAGE",)
|
||||
RETURN_NAMES = ("images",)
|
||||
FUNCTION = "match_frames"
|
||||
CATEGORY = "ListHelper"
|
||||
|
||||
def convert_to_lrc(self, input_text):
|
||||
def match_frames(self, images, target_frames, fill_mode="repeat_last"):
|
||||
"""
|
||||
將時間戳格式轉換為LRC格式
|
||||
輸入格式: >> 0:00-0:04\n>> 文本內容
|
||||
輸出格式: [00:00.00]文本內容
|
||||
"""
|
||||
|
||||
lines = input_text.strip().split('\n')
|
||||
lrc_lines = []
|
||||
current_time = None
|
||||
current_text = ""
|
||||
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
|
||||
# 檢查是否為時間戳行 (格式: >> 0:00-0:04)
|
||||
time_match = re.match(r'^>>\s*(\d+):(\d+)-(\d+):(\d+)$', line)
|
||||
if time_match:
|
||||
# 如果之前有累積的文本，先處理它
|
||||
if current_time is not None and current_text.strip():
|
||||
lrc_lines.append(f"[{current_time}]{current_text.strip()}")
|
||||
|
||||
# 解析開始時間
|
||||
start_min = int(time_match.group(1))
|
||||
start_sec = int(time_match.group(2))
|
||||
current_time = f"{start_min:02d}:{start_sec:02d}.00"
|
||||
current_text = ""
|
||||
|
||||
# 檢查是否為文本行 (格式: >> 文本內容)
|
||||
elif line.startswith('>> '):
|
||||
text_content = line[3:].strip() # 移除 ">> " 前綴
|
||||
if text_content: # 只添加非空文本
|
||||
if current_text:
|
||||
current_text += " " + text_content
|
||||
else:
|
||||
current_text = text_content
|
||||
|
||||
# 處理空行或其他格式
|
||||
elif line == '' or line == '>>':
|
||||
# 空行保持當前狀態，不做處理
|
||||
continue
|
||||
else:
|
||||
# 其他格式的行，嘗試作為文本處理
|
||||
if line and current_time is not None:
|
||||
if current_text:
|
||||
current_text += " " + line
|
||||
else:
|
||||
current_text = line
|
||||
|
||||
# 處理最後一段文本
|
||||
if current_time is not None and current_text.strip():
|
||||
lrc_lines.append(f"[{current_time}]{current_text.strip()}")
|
||||
|
||||
# 合併結果
|
||||
lrc_output = '\n'.join(lrc_lines)
|
||||
|
||||
return (lrc_output,)
|
||||
|
||||
try:
|
||||
import opencc
|
||||
except ImportError:
|
||||
print("請安裝opencc庫: pip install opencc-python-reimplemented")
|
||||
opencc = None
|
||||
|
||||
class ChineseConverterNode:
|
||||
"""
|
||||
ComfyUI節點：中文簡繁轉換
|
||||
使用opencc庫進行高質量轉換
|
||||
布林開關控制：True=簡體轉繁體，False=繁體轉簡體
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"input_text": ("STRING", {
|
||||
"multiline": True,
|
||||
"default": ""
|
||||
}),
|
||||
"simp_to_trad": ("BOOLEAN", {
|
||||
"default": True,
|
||||
"label_on": "簡體→繁體",
|
||||
"label_off": "繁體→簡體"
|
||||
}),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("converted_text",)
|
||||
FUNCTION = "convert_chinese"
|
||||
CATEGORY = "text/processing"
|
||||
|
||||
def __init__(self):
|
||||
"""初始化轉換器"""
|
||||
if opencc is None:
|
||||
self.s2t_converter = None
|
||||
self.t2s_converter = None
|
||||
print("錯誤：opencc庫未安裝，請執行: pip install opencc-python-reimplemented")
|
||||
else:
|
||||
try:
|
||||
# 簡體轉繁體轉換器
|
||||
self.s2t_converter = opencc.OpenCC('s2t.json')
|
||||
# 繁體轉簡體轉換器
|
||||
self.t2s_converter = opencc.OpenCC('t2s.json')
|
||||
except Exception as e:
|
||||
print(f"opencc初始化失敗: {e}")
|
||||
self.s2t_converter = None
|
||||
self.t2s_converter = None
|
||||
|
||||
def convert_chinese(self, input_text, simp_to_trad):
|
||||
"""
|
||||
轉換中文文本
|
||||
調整圖像序列到目標幀數
|
||||
|
||||
Args:
|
||||
input_text: 輸入文本
|
||||
simp_to_trad: True=簡體轉繁體，False=繁體轉簡體
|
||||
images: 輸入圖像張量 [N, H, W, C]
|
||||
target_frames: 目標幀數
|
||||
fill_mode: 填充模式
|
||||
|
||||
Returns:
|
||||
轉換後的文本
|
||||
調整後的圖像序列
|
||||
"""
|
||||
import torch
|
||||
|
||||
if not input_text.strip():
|
||||
return ("",)
|
||||
if images is None or images.shape[0] == 0:
|
||||
raise ValueError("輸入圖像序列不能為空")
|
||||
|
||||
# 檢查opencc是否可用
|
||||
if opencc is None:
|
||||
error_msg = "錯誤：請先安裝opencc庫\n執行命令: pip install opencc-python-reimplemented"
|
||||
print(error_msg)
|
||||
return (error_msg,)
|
||||
current_frames = images.shape[0]
|
||||
|
||||
try:
|
||||
if simp_to_trad:
|
||||
# 簡體轉繁體
|
||||
if self.s2t_converter is None:
|
||||
self.s2t_converter = opencc.OpenCC('s2t.json')
|
||||
converted_text = self.s2t_converter.convert(input_text)
|
||||
print(f"FrameMatch: 當前幀數 {current_frames} -> 目標幀數 {target_frames}")
|
||||
|
||||
# 如果當前幀數等於目標幀數，直接返回
|
||||
if current_frames == target_frames:
|
||||
return (images,)
|
||||
|
||||
# 如果目標幀數小於當前幀數，截取前面的幀
|
||||
elif target_frames < current_frames:
|
||||
matched_images = images[:target_frames]
|
||||
print(f"FrameMatch: 截取前 {target_frames} 幀")
|
||||
|
||||
# 如果目標幀數大於當前幀數，需要填充
|
||||
else:
|
||||
additional_frames_needed = target_frames - current_frames
|
||||
|
||||
if fill_mode == "repeat_last":
|
||||
# 重複最後一幀
|
||||
last_frame = images[-1:].clone() # 保持維度 [1, H, W, C]
|
||||
repeated_frames = last_frame.repeat(additional_frames_needed, 1, 1, 1)
|
||||
matched_images = torch.cat([images, repeated_frames], dim=0)
|
||||
print(f"FrameMatch: 重複最後一幀 {additional_frames_needed} 次")
|
||||
|
||||
elif fill_mode == "loop":
|
||||
# 循環播放整個序列
|
||||
loops_needed = (additional_frames_needed + current_frames - 1) // current_frames
|
||||
looped_images = images.repeat(loops_needed + 1, 1, 1, 1)
|
||||
matched_images = looped_images[:target_frames]
|
||||
print(f"FrameMatch: 循環播放 {loops_needed} 次")
|
||||
|
||||
elif fill_mode == "bounce":
|
||||
# 來回播放（正向 -> 反向 -> 正向...）
|
||||
additional_images = []
|
||||
remaining_frames = additional_frames_needed
|
||||
forward = True
|
||||
|
||||
while remaining_frames > 0:
|
||||
if forward:
|
||||
# 正向播放（跳過第一幀以避免重複）
|
||||
frames_to_add = min(remaining_frames, current_frames - 1)
|
||||
if frames_to_add > 0:
|
||||
additional_images.append(images[1:frames_to_add + 1])
|
||||
remaining_frames -= frames_to_add
|
||||
else:
|
||||
# 反向播放（跳過最後一幀以避免重複）
|
||||
frames_to_add = min(remaining_frames, current_frames - 1)
|
||||
if frames_to_add > 0:
|
||||
# 反轉順序，並跳過最後一幀
|
||||
reversed_frames = torch.flip(images[:-1], dims=[0])
|
||||
additional_images.append(reversed_frames[:frames_to_add])
|
||||
remaining_frames -= frames_to_add
|
||||
|
||||
forward = not forward
|
||||
|
||||
if additional_images:
|
||||
bounced_frames = torch.cat(additional_images, dim=0)
|
||||
matched_images = torch.cat([images, bounced_frames], dim=0)
|
||||
else:
|
||||
matched_images = images
|
||||
|
||||
print(f"FrameMatch: 來回播放模式，添加 {additional_frames_needed} 幀")
|
||||
|
||||
else:
|
||||
# 繁體轉簡體
|
||||
if self.t2s_converter is None:
|
||||
self.t2s_converter = opencc.OpenCC('t2s.json')
|
||||
converted_text = self.t2s_converter.convert(input_text)
|
||||
|
||||
return (converted_text,)
|
||||
|
||||
except Exception as e:
|
||||
error_msg = f"轉換失敗: {str(e)}"
|
||||
print(error_msg)
|
||||
return (error_msg,)
|
||||
# 預設使用重複最後一幀
|
||||
last_frame = images[-1:].clone()
|
||||
repeated_frames = last_frame.repeat(additional_frames_needed, 1, 1, 1)
|
||||
matched_images = torch.cat([images, repeated_frames], dim=0)
|
||||
print(f"FrameMatch: 使用預設模式，重複最後一幀 {additional_frames_needed} 次")
|
||||
|
||||
# 確保輸出幀數正確
|
||||
final_frames = matched_images.shape[0]
|
||||
if final_frames != target_frames:
|
||||
# 如果還是不匹配，進行最終調整
|
||||
if final_frames > target_frames:
|
||||
matched_images = matched_images[:target_frames]
|
||||
else:
|
||||
# 補齊差異
|
||||
diff = target_frames - final_frames
|
||||
last_frame = matched_images[-1:].clone()
|
||||
extra_frames = last_frame.repeat(diff, 1, 1, 1)
|
||||
matched_images = torch.cat([matched_images, extra_frames], dim=0)
|
||||
|
||||
print(f"FrameMatch: 完成，最終幀數 {matched_images.shape[0]}")
|
||||
|
||||
return (matched_images,)
|
||||
|
||||
|
||||
|
||||
@@ -1101,8 +1068,7 @@ NODE_CLASS_MAPPINGS = {
|
||||
"CeilDivide": CeilDivide,
|
||||
"LoadVideoPath": LoadVideoPath,
|
||||
"SaveVideoPath": SaveVideoPath,
|
||||
"TimestampToLrcNode": TimestampToLrcNode,
|
||||
"ChineseConverterNode": ChineseConverterNode,
|
||||
"FrameMatch": FrameMatch,
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
@@ -1115,7 +1081,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"CeilDivide": "CeilDivide",
|
||||
"LoadVideoPath": "LoadVideoPath",
|
||||
"SaveVideoPath": "SaveVideoPath",
|
||||
"TimestampToLrcNode": "TimestampToLrcNode",
|
||||
"ChineseConverterNode": "ChineseConverterNode",
|
||||
"FrameMatch": "FrameMatch",
|
||||
}
|
||||
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[project]
|
||||
name = "Listhelper"
|
||||
description = "The ListHelper collection is a comprehensive set of custom nodes for ComfyUI that provides powerful list manipulation capabilities. This collection includes audio processing, text splitting, and number generation tools for enhanced workflow automation."
|
||||
version = "1.0.2"
|
||||
version = "1.0.3"
|
||||
license = {file = "LICENSE"}
|
||||
dependencies = ["regex"]
|
||||
|
||||
|
||||
Reference in New Issue
Block a user