from utils.paths import PROJECTS_DIR,get_project_paths from utils.helpers import get_media_duration,get_media_info from pathlib import Path from typing import List, Dict, Optional import streamlit as st # 為了存取 secrets from scripts import step1_notion_sync, step2_translate_ipa import json from notion_client import Client from google.cloud import translate_v2 as translate import eng_to_ipa from google.cloud import texttospeech from pydub import AudioSegment from google.api_core.exceptions import GoogleAPICallError import re # 用於正規表示式匹配檔案名稱 import pysubs2 # 專業字幕處理函式庫 import librosa # 專業音訊分析函式庫 import subprocess import logging import math import os # 設定日誌 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') class Project: """ 代表一個獨立的影片專案，封裝其檔案結構和資料。 """ def __init__(self, project_name: str, page_id: str | None = None): """ 初始化一個 Project 實例。注意：這不會在磁碟上建立檔案。 若要建立新專案，請使用 Project.create_new()。 Args: project_name (str): 專案的名稱，對應其目錄名稱。 """ if not project_name or not isinstance(project_name, str): raise ValueError("專案名稱必須是一個非空的字串。") self.name = project_name self.root_path: Path = PROJECTS_DIR / self.name self.paths: dict[str, Path] = get_project_paths(self.name) self.data = self._load_data() if page_id: self.page_id = page_id elif self.data and 'id' in self.data: self.page_id = self.data['id'] else: self.page_id = None def _load_data(self) -> dict | None: """嘗試從 data.json 載入資料，若失敗則回傳 None。""" data_path = self.paths.get('data') if data_path and data_path.exists(): try: return json.loads(data_path.read_text(encoding="utf-8")) except (json.JSONDecodeError, FileNotFoundError): return None return None def create_directories(self): """ 確保專案所需的所有目錄都存在。 這個方法是「冪等」的，即使目錄已存在，重複呼叫也不會出錯。 """ print(f"正在為專案 '{self.name}' 檢查並建立目錄結構...") # 根據 get_project_paths 的定義，我們知道 'audio' 和 'output' 是需要建立的目錄 # 將需要建立的目錄鍵名放入一個列表中，方便管理 required_dirs = ['root','audio', 'output'] for dir_key in required_dirs: directory_path = self.paths.get(dir_key) if directory_path: # 使用 exist_ok=True 避免在目錄已存在時拋出錯誤 # 使用 parents=True 確保即使未來路徑變為巢狀結構也能成功建立 directory_path.mkdir(parents=True, exist_ok=True) print(f" - 目錄 '{directory_path}' 已確認存在。") else: print(f" - 警告：在路徑設定中找不到鍵名 '{dir_key}'。") @classmethod def create_new(cls, project_name: str, notion_page_id: str) -> 'Project': """ 在檔案系統上建立一個新的專案目錄結構。 Args: project_name (str): 新專案的名稱。 Returns: Project: 新建立專案的實例。 Raises: FileExistsError: 如果同名專案已存在。 """ project = cls(project_name, page_id=notion_page_id) project.create_directories() return project def __repr__(self) -> str: return f"" def __str__(self) -> str: return self.name def sync_from_notion(self) -> bool: """ 從 Notion 同步更新專案的 data.json 檔案。 這個方法是自給自足的，它知道自己的 page_id 和如何獲取 API Key。 """ if not self.page_id: st.session_state.operation_status = { "type": "error", "message": "內部錯誤：此專案沒有關聯的 Notion 頁面 ID。" } return False target_page_id = self.page_id api_key = st.secrets.get("NOTION_API_KEY") if not api_key: st.session_state.operation_status = { "type": "error", "message": "錯誤：找不到 Notion API Key。" } return False try: client = Client(auth=api_key) print(f"正在從 Notion 更新頁面 ID: {target_page_id}") page_data = client.pages.retrieve(page_id=target_page_id) # 這裡可以重用 step1 中的 extract_property_value 邏輯 # 最好是將該函式也移入 Project 類別作為一個私有方法 _extract_property_value properties = page_data['properties'] updated_entry = {"id": page_data['id']} for prop_name, prop_data in properties.items(): updated_entry[prop_name] = self._extract_property_value(prop_data) # 更新 data.json 檔案 with open(self.paths['data'], 'w', encoding='utf-8') as f: json.dump(updated_entry, f, ensure_ascii=False, indent=2) # 同時更新記憶體中的資料，保持同步 self.data = updated_entry self.data = self._load_data() st.session_state.operation_status = { "type": "success", "message": f"專案 '{self.name}' 已成功從 Notion 同步更新。" } return True except Exception as e: st.session_state.operation_status = { "type": "error", "message": f"更新專案 '{self.name}' 時發生錯誤: {e}" } return False def _extract_property_value(self,property_data): """從 Notion 頁面屬性中提取純文字值。""" prop_type = property_data.get('type') if prop_type == 'title': return property_data['title'][0]['plain_text'] if property_data.get('title') else "" elif prop_type == 'rich_text': return "\n".join([text['plain_text'] for text in property_data.get('rich_text', [])]) elif prop_type == 'select' and property_data.get('select'): return property_data['select']['name'] elif prop_type == 'date' and property_data.get('date'): return property_data['date']['start'] return None @classmethod def create_from_notion(cls, page_id: str, page_title: str): """ 工廠方法：從一個 Notion 頁面完整建立一個新專案。 """ api_key = st.secrets.get("NOTION_API_KEY") if not api_key: raise ValueError("無法建立專案，缺少 Notion API Key。") # 1. 先使用既有的 create_new 建立專案實體和目錄結構 project = cls.create_new(project_name=page_title) # 2. 執行從 Notion 抓取資料並寫入 data.json 的邏輯 try: client = Client(auth=api_key) page_data = client.pages.retrieve(page_id=page_id) properties = page_data['properties'] # 使用 _extract_property_value 來解析資料 page_entry = {"id": page_data['id']} for prop_name, prop_data in properties.items(): page_entry[prop_name] = project._extract_property_value(prop_data) # 將資料寫入檔案並更新物件狀態 with open(project.paths['data'], 'w', encoding='utf-8') as f: json.dump(page_entry, f, ensure_ascii=False, indent=2) project.data = page_entry return project # 回傳完整初始化的專案物件 except Exception as e: # 如果出錯，可能需要考慮刪除已建立的空資料夾，以保持系統乾淨 # (這部分屬於錯誤處理的細化) raise IOError(f"從 Notion 頁面 (ID: {page_id}) 抓取資料時失敗: {e}") _translate_client = None @property def translate_client(self): """ 延遲初始化 (Lazy Initialization) Google Translate 客戶端。 只有在第一次真正需要翻譯時，才會建立客戶端實例， 並將其儲存起來以供後續重複使用，避免重複認證。 """ if self._translate_client is None: creds_path = st.secrets.get("GOOGLE_CREDS_TRANSLATE_PATH") if not creds_path: raise ValueError("未在 secrets 中設定 Google Cloud 翻譯認證檔案路徑。") print("正在初始化 Google Translate 客戶端...") self._translate_client = translate.Client.from_service_account_json(creds_path) return self._translate_client def add_translation_and_ipa(self) -> bool: """ 為專案資料添加翻譯和 IPA 音標。 這是協調器，負責整個流程的控制。 """ # 1. 檢查前置條件：確保核心資料已存在 if not self.data or "en" not in self.data: st.session_state.operation_status = { "type": "error", "message": "錯誤：專案資料不完整或缺少英文原文 ('en')。" } return False # 2. 準備處理資料 # 從 `data.json` 讀取英文句子列表[1] english_sentences = self.data["en"].strip().split('\n') translated_sentences = [] ipa_sentences = [] # 3. 遍歷每一句，呼叫輔助方法進行處理 for sentence in english_sentences: if not sentence: continue # 呼叫封裝好的翻譯方法 translated = self._call_google_translate(sentence) translated_sentences.append(translated if translated is not None else "[翻譯失敗]") # 呼叫封裝好的 IPA 轉換方法 ipa = self._get_ipa_for_text(sentence) ipa_sentences.append(ipa if ipa is not None else "[轉換失敗]") # 4. 將處理結果更新回 self.data self.data['zh'] = "\n".join(translated_sentences) self.data['ipa'] = "\n".join(ipa_sentences) try: # 首先，將更新後的資料寫回本地 data.json with open(self.paths['data'], 'w', encoding='utf-8') as f: json.dump(self.data, f, ensure_ascii=False, indent=2) # 然後，呼叫新方法將結果同步回 Notion if self._update_single_notion_page(): st.session_state.operation_status = { "type": "success", "message": "AI 加註完成，並已成功寫回 Notion！🚀" } return True else: st.session_state.operation_status = { "type": "warning", "message": "AI 加註已完成，但寫回 Notion 時失敗。請稍後手動同步。" } return False except IOError as e: st.session_state.operation_status = { "type": "error", "message": f"寫入本地 data.json 時發生錯誤: {e}" } return False def _update_single_notion_page(self) -> bool: """ (私有方法) 將 self.data 中的 'zh' 和 'ipa' 欄位更新回對應的 Notion 頁面。 """ if not self.page_id: st.session_state.operation_status = { "type": "error", "message": "無法更新 Notion：專案缺少 page_id。" } return False api_key = st.secrets.get("NOTION_API_KEY") if not api_key: st.session_state.operation_status = { "type": "error", "message": "無法更新 Notion：缺少 API Key。" } return False try: client = Client(auth=api_key) # 準備要更新的屬性 # 注意：這裡的 "中文翻譯" 和 "IPA音標" 必須與您 Notion Database 中的欄位名稱完全一致！ properties_to_update = { # 假設您在 Notion 中的欄位名稱就是 "zh" # 如果不是，請修改 "zh" 為您實際的欄位名稱，例如 "中文翻譯" "zh": { "rich_text": [ { "type": "text", "text": { "content": self.data.get('zh', '') } } ] }, # 假設您在 Notion 中的欄位名稱就是 "ipa" # 如果不是，請修改 "ipa" 為您實際的欄位名稱，例如 "IPA" "ipa": { "rich_text": [ { "type": "text", "text": { "content": self.data.get('ipa', '') } } ] } } print(f"正在將 AI 加註結果寫回 Notion 頁面: {self.page_id}") client.pages.update(page_id=self.page_id, properties=properties_to_update) return True except Exception as e: st.session_state.operation_status = { "type": "error", "message": f"更新 Notion 頁面時發生 API 錯誤: {e}" } return False def _call_google_translate(self, text: str) -> str | None: """ (輔助) 呼叫 Google Translate API。 成功時返回翻譯字串，失敗時在後台記錄錯誤並返回 None。 """ try: result = self.translate_client.translate(text, target_language="zh-TW") return result.get('translatedText') except GoogleAPICallError as e: # 不直接顯示 UI 警告，改為在後台記錄，讓呼叫者決定如何處理 print(f"警告：Google API 呼叫失敗 - {e.message}") return None except Exception as e: # 同上，記錄詳細錯誤 print(f"錯誤：翻譯 '{text[:20]}...' 時發生未預期的錯誤: {e}") return None def _get_ipa_for_text(self, text: str) -> str | None: """ 為給定的英文文字獲取 IPA 音標。 失敗時在後台記錄錯誤並返回 None。 """ if not text: return "" try: # ... (您原有的 IPA 轉換邏輯保持不變) ... ipa_word_list = eng_to_ipa.convert(text, keep_punct=True) if not isinstance(ipa_word_list, list): return str(ipa_word_list) final_ipa_string = ' '.join(ipa_word_list) final_ipa_string = final_ipa_string.replace('*', '') final_ipa_string = final_ipa_string.replace(' ,', ',').replace(' .', '.').replace(' ?', '?').replace(' !', '!') return final_ipa_string except Exception as e: print(f"警告：無法為 '{text[:20]}...' 獲取 IPA 音標: {e}") return None _tts_client = None # 為 TTS Client 新增一個儲存屬性 @property def tts_client(self): """延遲初始化 Google Text-to-Speech 客戶端，高效且僅在需要時執行一次。""" if self._tts_client is None: creds_path = st.secrets.get("GOOGLE_CREDS_TTS_PATH") if not creds_path: raise ValueError("未在 secrets 中設定 Google Cloud TTS 認證檔案路徑。") self._tts_client = texttospeech.TextToSpeechClient.from_service_account_json(creds_path) return self._tts_client def generate_sentence_audio(self) -> bool: """ 為專案中每一對中英文句子，生成一個包含多種聲音的「教學音訊片段」。 """ # 1. 檢查前置條件 if not self.data or "en" not in self.data or "zh" not in self.data: st.session_state.operation_status = { "type": "error", "message": "錯誤：專案資料不完整，必須同時包含 'en' 和 'zh' 欄位。" } return False # 2. 讀取並配對中英文句子 english_sentences = [line for line in self.data["en"].strip().split('\n') if line] chinese_sentences = [line for line in self.data["zh"].strip().split('\n') if line] if len(english_sentences) != len(chinese_sentences): st.session_state.operation_status = { "type": "error", "message": "en zh數量不符合。" } return False # 3. 從 data.json 讀取 voice 設定，如果沒有則使用預設值 voice_config = { 'english_voice_1': self.data.get("english_voice_1", "en-US-Wavenet-I"), 'english_voice_2': self.data.get("english_voice_2", "en-US-Wavenet-F"), 'chinese_voice': self.data.get("chinese_voice", "cmn-TW-Wavenet-B") } print("使用的語音設定：", voice_config) # 提供除錯資訊 audio_dir = self.paths['audio'] audio_dir.mkdir(parents=True, exist_ok=True) success_count = 0 total_count = min(len(english_sentences), len(chinese_sentences)) if total_count == 0: print("沒有找到任何可處理的句子對。") return False progress_bar = st.progress(0, text="正在生成教學音訊片段...") for i in range(total_count): item_en = english_sentences[i] item_zh = chinese_sentences[i] output_path = audio_dir / f"{i:03d}.wav" # 4. 呼叫新的 SSML 生成器 ssml_content = self._generate_ssml(item_en, item_zh, voice_config) # 5. 呼叫 TTS API (無需修改) if self._call_google_tts(ssml_content, output_path,default_voice_name=voice_config['english_voice_1']): success_count += 1 progress_bar.progress((i + 1) / total_count, text=f"正在生成教學音訊... ({i+1}/{total_count})") progress_bar.empty() if success_count > 0: st.session_state.operation_status = { "type": "success", "message": "音訊生成成功！。" } return True else: st.session_state.operation_status = { "type": "error", "message": "音訊生成失敗！。" } return False def _generate_ssml(self, item_en: str, item_zh: str, voice_config: dict) -> str: """ (新輔助方法) 根據模板，生成包含多種聲音的教學 SSML。 """ # 對文本進行 XML 轉義，防止特殊字元破壞 SSML 結構 safe_en = item_en.replace('&', '&').replace('<', '<').replace('>', '>') safe_zh = item_zh.replace('&', '&').replace('<', '<').replace('>', '>') return f""" {safe_en} {safe_en} {safe_zh} {safe_en} """ def _call_google_tts(self, ssml_content: str, output_path: Path, default_voice_name: str) -> bool: """ (輔助方法已更新) 現在只接收 SSML 內容，不再需要 voice_name 參數。 """ try: synthesis_input = texttospeech.SynthesisInput(ssml=ssml_content) voice_params = texttospeech.VoiceSelectionParams( # 從 'en-US-Wavenet-D' 中提取 'en-US' language_code='-'.join(default_voice_name.split('-')[:2]), name=default_voice_name ) audio_config = texttospeech.AudioConfig( audio_encoding=texttospeech.AudioEncoding.LINEAR16, sample_rate_hertz=24000 ) response = self.tts_client.synthesize_speech( input=synthesis_input, voice=voice_params, audio_config=audio_config ) with open(output_path, "wb") as out: out.write(response.audio_content) return True except Exception as e: st.session_state.operation_status = { "type": "error", "message": "音訊生成發生錯誤！" } return False def concatenate_audio(self) -> bool: """ 將 audio 資料夾中所有獨立的 .wav 檔，按檔名順序拼接成一個完整的音訊檔。 """ # 1. 檢查前置條件：使用我們之前建立的狀態檢查方法 if not self.has_sentence_audio(): st.session_state.operation_status = { "type": "error", "message": "錯誤：在 audio 資料夾中找不到任何 .wav 檔案，無法進行組合。" } return False audio_dir = self.paths['audio'] output_path = self.paths['combined_audio'] try: # 2. 獲取所有 .wav 檔案並進行排序 # 使用 sorted() 確保檔案是按字母順序（例如 000.wav, 001.wav, ...）處理的 wav_files = sorted(audio_dir.glob("*.wav")) if not wav_files: st.session_state.operation_status = { "type": "error", "message": " audio 資料夾中找到了目錄，但沒有找到 .wav 檔案。" } return False # 3. 初始化一個空的 AudioSegment 作為拼接的基礎 # 這是比「拿第一個檔案當基礎」更穩健的做法 combined_audio = AudioSegment.empty() # 4. 遍歷所有音訊檔並依次拼接 for wav_file in wav_files: # 讀取單個 .wav 檔案 segment = AudioSegment.from_wav(wav_file) # 使用 `+` 運算子將音訊片段拼接到末尾 combined_audio += segment # 5. 匯出拼接好的完整音訊檔 # format="wav" 明確指定輸出格式 print(f"正在將組合音訊匯出到: {output_path}") combined_audio.export(output_path, format="wav") return True except FileNotFoundError: st.session_state.operation_status = { "type": "error", "message": "FFmpeg 未安裝或未在系統路徑中。Pydub 需要它來處理音訊。" } print("Pydub 錯誤：請確保 FFmpeg 已安裝並在系統的 PATH 環境變數中。") return False except Exception as e: st.session_state.operation_status = { "type": "error", "message": f"組合音訊時發生未預期的錯誤: {e}" } print(f"組合音訊時出錯: {e}") return False def generate_ass_subtitles(self) -> bool: """ 根據 data.json 的內容和 audio/ 目錄中每個音訊檔的時長， 生成一個包含多種樣式和四層字幕的 .ass 檔案。 此版本精確複製了新的 step5_generate_ass.py 的邏輯[1]。 """ # 1. 檢查前置條件 if not self.has_sentence_audio(): st.session_state.operation_status = { "type": "error", "message": "錯誤：找不到單句音訊檔，無法生成字幕。" } return False if not self.data: st.session_state.operation_status = { "type": "error", "message": "錯誤：專案資料未載入。" } return False # 2. 準備路徑和資料 ass_path = self.paths['ass_file'] audio_dir = self.paths['audio'] try: # 從 self.data 讀取各語言的文本行 en_lines = [line.strip() for line in self.data.get("en", "").split('\n') if line.strip()] zh_lines = [line.strip() for line in self.data.get("zh", "").split('\n') if line.strip()] ipa_lines = [line.strip() for line in self.data.get("ipa", "").split('\n') if line.strip()] # 3. 使用正規表示式獲取並排序音訊檔案 file_pattern = r"(\d{3})\.wav" # 根據您的腳本，檔名應為 vocab_00.wav, vocab_01.wav 等 pattern = re.compile(file_pattern) wav_files = sorted( [p for p in audio_dir.iterdir() if p.is_file() and pattern.fullmatch(p.name)], key=lambda p: int(pattern.fullmatch(p.name).group(1)) ) # 4. 嚴格檢查資料數量是否一致 if not (len(wav_files) == len(en_lines) == len(zh_lines) == len(ipa_lines)): msg = f"錯誤：資料數量不一致！音訊({len(wav_files)}), EN({len(en_lines)}), ZH({len(zh_lines)}), IPA({len(ipa_lines)})" st.session_state.operation_status = {"type": "error", "message": msg} return False total_files = len(wav_files) if total_files == 0: st.session_state.operation_status = {"type": "warning", "message": "找不到任何匹配的音訊檔來生成字幕。"} return False # 5. 使用 pysubs2 建立 .ass 檔案物件 subs = pysubs2.SSAFile() subs.info["PlayResX"] = "1920" subs.info["PlayResY"] = "1080" subs.info["Title"] = self.name # 6. 定義所有需要的樣式 (從您的腳本中精確複製)[1] subs.styles["EN"] = pysubs2.SSAStyle(fontname="Noto Sans", fontsize=140, primarycolor=pysubs2.Color(255, 248, 231), outlinecolor=pysubs2.Color(255, 248, 231), outline=2, alignment=pysubs2.Alignment.TOP_CENTER, marginv=280) subs.styles["IPA"] = pysubs2.SSAStyle(fontname="Noto Sans", fontsize=110, primarycolor=pysubs2.Color(255, 140, 0), outlinecolor=pysubs2.Color(255, 140, 0), outline=1, alignment=pysubs2.Alignment.TOP_CENTER, marginv=340) subs.styles["ZH"] = pysubs2.SSAStyle(fontname="Noto Sans TC", fontsize=140, primarycolor=pysubs2.Color(102, 128, 153), outlinecolor=pysubs2.Color(102, 128, 153), outline=1, alignment=pysubs2.Alignment.TOP_CENTER, marginv=440) subs.styles["NUMBER"] = pysubs2.SSAStyle(fontname="Segoe UI Symbol", fontsize=120, primarycolor=pysubs2.Color(144, 144, 144), outlinecolor=pysubs2.Color(144, 144, 144), bold=True, outline=1, borderstyle=1,alignment=pysubs2.Alignment.TOP_RIGHT, marginl=0, marginr=260, marginv=160) # 7. 遍歷音訊檔，生成四層字幕事件 st.session_state.operation_status = { "type": "progress", "value": 0, "message": "正在準備生成字幕..." } current_time_ms = 0 for i, wav_path in enumerate(wav_files): # 使用 librosa 獲取精確時長 (秒)，並轉換為毫秒 duration_ms = int(librosa.get_duration(path=str(wav_path)) * 1000) start_time = current_time_ms end_time = current_time_ms + duration_ms # 為每一層字幕建立一個事件 subs.append(pysubs2.SSAEvent(start=start_time, end=end_time, text=en_lines[i], style="EN")) subs.append(pysubs2.SSAEvent(start=start_time, end=end_time, text=f"[{ipa_lines[i]}]", style="IPA")) subs.append(pysubs2.SSAEvent(start=start_time, end=end_time, text=zh_lines[i], style="ZH")) subs.append(pysubs2.SSAEvent(start=start_time, end=end_time, text=i, style="NUMBER")) current_time_ms = end_time st.session_state.operation_status = { "type": "progress", "value": (i + 1) / total_files, "message": f"正在處理字幕... ({i+1}/{total_files})" } # 8. 儲存 .ass 檔案 subs.save(str(ass_path)) st.session_state.operation_status = { "type": "success", "message": f"ASS 字幕檔已成功生成並儲存於 {ass_path.name}！🎉" } return True except Exception as e: st.session_state.operation_status = { "type": "error", "message": f"生成 ASS 字幕時發生未預期的錯誤: {e}" } return False def has_sentence_audio(self) -> bool: """檢查 audio 資料夾是否存在且包含 .wav 檔案。""" audio_dir = self.paths.get('audio') return audio_dir and audio_dir.exists() and any(f.suffix == '.wav' for f in audio_dir.iterdir()) def has_combined_audio(self) -> bool: """檢查組合後的音訊檔是否存在。""" combined_path = self.paths.get('combined_audio') return combined_path and combined_path.exists() def assemble_video(self, logo_video: Path, open_video: Path, end_video: Path): """ 使用 FFmpeg 的 xfade 濾鏡組裝最終影片，並在過程中統一影片屬性與進行色彩校正。 """ # --- 標準化設定 --- TARGET_WIDTH = 1920 TARGET_HEIGHT = 1080 TARGET_FPS = 30 def escape_ffmpeg_path_for_filter(path: Path) -> str: """為在 FFmpeg 濾鏡圖中安全使用而轉義路徑。""" path_str = str(path.resolve()) if os.name == 'nt': return path_str.replace('\\', '\\\\').replace(':', '\\:') else: return path_str.replace("'", "'\\\\\\''") try: # --- 1. 路徑與檔案檢查 --- output_dir = self.paths['output'] temp_video_dir = self.paths['temp_video'] audio_path = self.paths['combined_audio'] ass_path = self.paths['ass_file'] final_video_path = self.paths['final_video'] bg_final_path = output_dir / "bg_final.mp4" transition_duration = 1.0 print("111") for file_path in [logo_video, open_video, end_video, audio_path, ass_path]: if not file_path or not file_path.exists(): st.session_state.operation_status = { "type": "error", "message": f"缺少必需的檔案: {e}" } return print("222") base_videos = sorted([p for p in temp_video_dir.iterdir() if p.is_file() and p.suffix.lower() in ['.mp4', '.mov']]) if not base_videos: st.session_state.operation_status = { "type": "error", "message": f"資料夾中沒有影片可供合成。: {e}" } return print("333") p_loop_count, error_msg = self.calculate_loop_count(transition_duration=transition_duration) if error_msg: # 如果計算出錯，拋出一個錯誤讓外層的 except 捕捉 raise ValueError(f"計算循環次數時失敗: {error_msg}") print("444") # --- 2. 一步式生成主要內容影片 (bg_final.mp4) --- if not bg_final_path.exists(): print(f"⚙️ 準備一步式生成主要內容影片 (循環 {p_loop_count} 次)...") looped_video_list = base_videos * p_loop_count inputs_cmd = [] for video_path in looped_video_list: inputs_cmd.extend(["-i", str(video_path)]) inputs_cmd.extend(["-i", str(audio_path)]) ass_path_str = escape_ffmpeg_path_for_filter(ass_path) filter_parts = [] stream_count = len(looped_video_list) # 【核心修改】定義色彩校正濾鏡 color_correction_filter = "eq=brightness=-0.05:contrast=0.95:saturation=0.7" # 將標準化 (尺寸、影格率) 與色彩校正合併 for i in range(stream_count): filter_parts.append( f"[{i}:v]scale={TARGET_WIDTH}:{TARGET_HEIGHT}:force_original_aspect_ratio=decrease,pad={TARGET_WIDTH}:{TARGET_HEIGHT}:(ow-iw)/2:(oh-ih)/2,setsar=1,fps={TARGET_FPS},{color_correction_filter}[v_scaled_{i}]" ) last_v_out = "[v_scaled_0]" for i in range(stream_count - 1): offset = sum(get_media_duration(v) for v in looped_video_list[:i+1]) - (i + 1) * transition_duration v_in_next = f"[v_scaled_{i+1}]" v_out_current = f"[v_out{i+1}]" if i < stream_count - 2 else "[bg_video_stream]" filter_parts.append(f"{last_v_out}{v_in_next}xfade=transition=fade:duration={transition_duration}:offset={offset:.4f}{v_out_current}") last_v_out = v_out_current drawbox_filter = "drawbox=w=iw*0.8:h=ih*0.8:x=(iw-iw*0.8)/2:y=(ih-ih*0.8)/2:color=0x808080@0.7:t=fill" filter_parts.append(f"[bg_video_stream]{drawbox_filter}[v_with_mask]") filter_parts.append(f"[v_with_mask]ass=filename='{ass_path_str}'[final_v]") filter_complex_str = ";".join(filter_parts) ffmpeg_main_content_cmd = [ "ffmpeg", "-y", *inputs_cmd, "-filter_complex", filter_complex_str, "-map", "[final_v]", "-map", f"{stream_count}:a:0", "-c:v", "libx264", "-pix_fmt", "yuv420p", "-preset", "fast", "-c:a", "aac", "-b:a", "192k", "-shortest", str(bg_final_path) ] print("🚀 正在執行 FFmpeg 主要內容合成指令 (含色彩校正)...") result = subprocess.run(ffmpeg_main_content_cmd, check=True, capture_output=True, text=True, encoding='utf-8') if result.returncode != 0: raise subprocess.CalledProcessError(result.returncode, result.args, stderr=result.stderr) print(f"✅ 主要內容影片已生成: {bg_final_path}") # --- 3. 合成最終的影片序列 (logo -> open -> bg_final -> end) --- if final_video_path.exists(): print(f"✅ 最終影片已存在，跳過組裝: {final_video_path}") return True, f"✅ 影片已存在於 {final_video_path}", final_video_path print("🎬 開始動態生成 xfade 合成指令...") videos_to_concat = [logo_video, open_video, bg_final_path, end_video] final_inputs_cmd, final_filter_parts, video_infos = [], [], [] for video_path in videos_to_concat: final_inputs_cmd.extend(["-i", str(video_path)]) info = get_media_info(video_path) video_infos.append(info) for i, info in enumerate(video_infos): if not info["has_audio"]: duration = info['duration'] final_filter_parts.append(f"anullsrc=r=44100:cl=stereo:d={duration:.4f}[silent_a_{i}]") for i in range(len(videos_to_concat)): # 注意：這裡我們不對 logo/open/end 影片進行調色，以保留它們的原始風格 final_filter_parts.append( f"[{i}:v]scale={TARGET_WIDTH}:{TARGET_HEIGHT}:force_original_aspect_ratio=decrease,pad={TARGET_WIDTH}:{TARGET_HEIGHT}:(ow-iw)/2:(oh-ih)/2,setsar=1,fps={TARGET_FPS}[v_final_scaled_{i}]" ) last_v_out = "[v_final_scaled_0]" last_a_out = "[0:a]" if video_infos[0]["has_audio"] else "[silent_a_0]" for i in range(len(videos_to_concat) - 1): offset = sum(info['duration'] for info in video_infos[:i+1]) - (i + 1) * transition_duration v_in_next = f"[v_final_scaled_{i+1}]" a_in_next = f"[{i+1}:a]" if video_infos[i+1]["has_audio"] else f"[silent_a_{i+1}]" v_out_current = f"[v_out{i+1}]" if i < len(videos_to_concat) - 2 else "[video]" a_out_current = f"[a_out{i+1}]" if i < len(videos_to_concat) - 2 else "[audio]" final_filter_parts.append(f"{last_v_out}{v_in_next}xfade=transition=fade:duration={transition_duration}:offset={offset:.4f}{v_out_current}") final_filter_parts.append(f"{last_a_out}{a_in_next}acrossfade=d={transition_duration}{a_out_current}") last_v_out, last_a_out = v_out_current, a_out_current final_filter_complex_str = ";".join(final_filter_parts) ffmpeg_concat_cmd = [ "ffmpeg", "-y", *final_inputs_cmd, "-filter_complex", final_filter_complex_str, "-map", "[video]", "-map", "[audio]", "-c:v", "libx264", "-pix_fmt", "yuv420p", "-preset", "fast", "-movflags", "+faststart", "-c:a", "aac", "-b:a", "192k", str(final_video_path) ] print("🚀 執行 FFmpeg 最終序列合成指令...") result = subprocess.run(ffmpeg_concat_cmd, check=True, capture_output=True, text=True, encoding='utf-8') if result.returncode != 0: raise subprocess.CalledProcessError(result.returncode, result.args, stderr=result.stderr) print(f"✅ 影片已成功組裝並儲存至 {final_video_path}") return True, f"✅ 影片已成功組裝並儲存至 {final_video_path}", final_video_path except subprocess.CalledProcessError as e: error_output = e.stderr if e.stderr else str(e) return False, f"❌ FFmpeg 執行失敗:\n{error_output}", None except Exception as e: return False, f"❌ 發生未預期錯誤: {e}", None # 【新增】計算循環次數 p 的函式 def calculate_loop_count(self, transition_duration: float) -> tuple[int | None, str | None]: """ 根據音訊長度和一系列影片，計算所需的最小循環次數 p。 成功時回傳 (p, None)，失敗時回傳 (None, error_message)。 """ print("aaa") m_prime = get_media_duration(self.paths['combined_audio']) if m_prime is None: return None, "無法讀取音訊檔案長度。" print("bbb") video_folder=self.paths['temp_video'] video_paths = [p for p in video_folder.iterdir() if p.is_file() and p.suffix.lower() in ['.mp4', '.mov']] video_lengths = [get_media_duration(p) for p in video_paths] video_lengths = [l for l in video_lengths if l is not None and l > 0] print("ccc") if not video_lengths: return None, "在 `test` 資料夾中找不到有效的影片檔案。" print("ddd") n = len(video_lengths) m = sum(video_lengths) tr = transition_duration denominator = m - (n - 1) * tr if denominator <= 0: return None, f"影片的有效長度 ({denominator:.2f}s) 小於或等於零，無法進行循環。請增加影片時長或減少轉場時間。" p = math.ceil(m_prime / denominator) return p, None