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不我發現一個奇怪的問題捏,\n[00:23.691] 當我使用某些特定字數的時候,\n[00:26.791] 文字分段功能似乎完全不會運作。\n[00:30.901] 例如剛剛那段話剛好九十九個字,\n[00:33.681] 那文字長度在這裡就爆炸了。\n[00:35.911] 我本來以為是我刪掉300M模型的問題,\n[00:40.541] 然而根本就不是這樣的。\n[00:42.441] 我懷疑真的是文字切割的異常,\n[00:45.551] 切割不動的話,你語音就會爆炸。\n```" + ] + }, + { + "id": 16, + "type": "WanVideoTextEncode", + "pos": [ + 520, + -630 + ], + "size": [ + 420.30511474609375, + 261.5306701660156 + ], + "flags": {}, + "order": 26, + "mode": 0, + "inputs": [ + { + "name": "t5", + "type": "WANTEXTENCODER", + "link": 15 + }, + { + "name": "model_to_offload", + "shape": 7, + "type": "WANVIDEOMODEL", + "link": 79 + } + ], + "outputs": [ + { + "name": "text_embeds", + "type": "WANVIDEOTEXTEMBEDS", + "slot_index": 0, + "links": [ + 86 + ] + } + ], + "properties": { + "cnr_id": "ComfyUI-WanVideoWrapper", + "ver": "d9b1f4d1a5aea91d101ae97a54714a5861af3f50", + "Node name for S&R": "WanVideoTextEncode", + "aux_id": "kijai/ComfyUI-WanVideoWrapper", + "widget_ue_connectable": {} + }, + "widgets_values": [ + 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"ComfyUI-VideoHelperSuite": "0a75c7958fe320efcb052f1d9f8451fd20c730a8" + }, + "VHS_latentpreview": false, + "VHS_latentpreviewrate": 0, + "VHS_MetadataImage": true, + "VHS_KeepIntermediate": true, + "ue_links": [], + "links_added_by_ue": [] + }, + "version": 0.4 +} \ No newline at end of file diff --git a/nodes.py b/nodes.py index b6ba2f4..a9b3bf0 100644 --- a/nodes.py +++ b/nodes.py @@ -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", } diff --git a/pyproject.toml b/pyproject.toml index 1ac7d8e..340fd46 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -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"]