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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"<Project(name='{self.name}')>"
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''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''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('&', '&amp;').replace('<', '&lt;').replace('>', '&gt;')
safe_zh = item_zh.replace('&', '&amp;').replace('<', '&lt;').replace('>', '&gt;')
return f"""
<speak>
<break time="2s"/>
<voice name="{voice_config['english_voice_1']}">
<prosody rate="medium" pitch="medium">{safe_en}</prosody>
</voice>
<break time="2s"/>
<voice name="{voice_config['english_voice_2']}">
<prosody rate="70%" pitch="medium">{safe_en}</prosody>
</voice>
<break time="2s"/>
<voice name="{voice_config['chinese_voice']}">
<prosody rate="medium" pitch="+2st">{safe_zh}</prosody>
</voice>
<break time="1.5s"/>
<voice name="{voice_config['english_voice_2']}">
<prosody rate="110%" pitch="medium">{safe_en}</prosody>
</voice>
<break time="1s"/>
</speak>
"""
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