From 990994e9cd6fd334a48f0b3223256dd24d0d5687 Mon Sep 17 00:00:00 2001 From: linyq Date: Wed, 25 Sep 2024 18:32:38 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BC=98=E5=8C=96=20webui=20task=20=E9=80=BB?= =?UTF-8?q?=E8=BE=9130%=EF=BC=9B=E6=96=B0=E5=A2=9E=E6=A3=80=E6=9F=A5/?= =?UTF-8?q?=E4=BF=AE=E5=A4=8D=E8=84=9A=E6=9C=AC=E6=96=B9=E6=B3=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/models/schema.py | 65 ++++++------- app/services/llm.py | 3 +- app/services/task.py | 13 ++- app/utils/check_script.py | 198 ++++++++++++++++++++++++++++++++++++++ requirements.txt | 1 + webui.py | 113 ++++++---------------- 6 files changed, 269 insertions(+), 124 deletions(-) create mode 100644 app/utils/check_script.py diff --git a/app/models/schema.py b/app/models/schema.py index b90a4c1..f20657a 100644 --- a/app/models/schema.py +++ b/app/models/schema.py @@ -3,7 +3,7 @@ from enum import Enum from typing import Any, List, Optional import pydantic -from pydantic import BaseModel +from pydantic import BaseModel, Field # 忽略 Pydantic 的特定警告 warnings.filterwarnings( @@ -330,42 +330,39 @@ class BgmUploadResponse(BaseResponse): class VideoClipParams(BaseModel): - video_subject: Optional[str] = "春天的花海让人心旷神怡" + """ + NarratoAI 数据模型 + """ + video_clip_json: Optional[list] = Field(default=[], description="LLM 生成的视频剪辑脚本内容") + video_clip_json_path: Optional[str] = Field(default="", description="LLM 生成的视频剪辑脚本路径") + video_origin_path: Optional[str] = Field(default="", description="原视频路径") + video_aspect: Optional[VideoAspect] = Field(default=VideoAspect.portrait.value, description="视频比例") + video_language: Optional[str] = Field(default="zh-CN", description="视频语言") - video_clip_json: Optional[str] = "" # 视频剪辑脚本 - video_origin_path: Optional[str] = "" # 原视频路径 - video_aspect: Optional[VideoAspect] = VideoAspect.portrait.value # 视频比例 - video_clip_duration: Optional[int] = 5 # 视频片段时长 - video_count: Optional[int] = 1 # 视频片段数量 - video_source: Optional[str] = "local" - video_language: Optional[str] = "" # 自动检测 + # video_clip_duration: Optional[int] = 5 # 视频片段时长 + # video_count: Optional[int] = 1 # 视频片段数量 + # video_source: Optional[str] = "local" # video_concat_mode: Optional[VideoConcatMode] = VideoConcatMode.random.value - # # 女性 - # "zh-CN-XiaoxiaoNeural", - # "zh-CN-XiaoyiNeural", - # # 男性 - # "zh-CN-YunjianNeural" 男声 - # "zh-CN-YunyangNeural", - # "zh-CN-YunxiNeural", - voice_name: Optional[str] = "zh-CN-YunjianNeural" # 语音名称 指定选择： - voice_volume: Optional[float] = 1.0 # 语音音量 - voice_rate: Optional[float] = 1.0 # 语速 + voice_name: Optional[str] = Field(default="zh-CN-YunjianNeural", description="语音名称") + voice_volume: Optional[float] = Field(default=1.0, description="语音音量") + voice_rate: Optional[float] = Field(default=1.0, description="语速") - bgm_name: Optional[str] = "random" # 背景音乐名称 - bgm_type: Optional[str] = "random" # 背景音乐类型 - bgm_file: Optional[str] = "" # 背景音乐文件 - bgm_volume: Optional[float] = 0.2 + bgm_name: Optional[str] = Field(default="random", description="背景音乐名称") + bgm_type: Optional[str] = Field(default="random", description="背景音乐类型") + bgm_file: Optional[str] = Field(default="", description="背景音乐文件") + bgm_volume: Optional[float] = Field(default=0.2, description="背景音乐音量") - subtitle_enabled: Optional[bool] = True # 是否启用字幕 - subtitle_position: Optional[str] = "bottom" # top, bottom, center - font_name: Optional[str] = "STHeitiMedium.ttc" # 字体名称 - text_fore_color: Optional[str] = "#FFFFFF" # 文字前景色 - text_background_color: Optional[str] = "transparent" # 文字背景色 + subtitle_enabled: Optional[bool] = Field(default=True, description="是否启用字幕") + subtitle_position: Optional[str] = Field(default="bottom", description="字幕位置") # top, bottom, center + font_name: Optional[str] = Field(default="STHeitiMedium.ttc", description="字体名称") + text_fore_color: Optional[str] = Field(default="#FFFFFF", description="文字前景色") + text_background_color: Optional[str] = Field(default="transparent", description="文字背景色") - font_size: int = 60 # 文字大小 - stroke_color: Optional[str] = "#000000" # 文字描边颜色 - stroke_width: float = 1.5 # 文字描边宽度 - custom_position: float = 70.0 # 自定义位置 - n_threads: Optional[int] = 2 # 线程数 - paragraph_number: Optional[int] = 1 # 段落数量 + font_size: int = Field(default=60, description="文字大小") + stroke_color: Optional[str] = Field(default="#000000", description="文字描边颜色") + stroke_width: float = Field(default=1.5, description="文字描边宽度") + custom_position: float = Field(default=70.0, description="自定义位置") + + # n_threads: Optional[int] = 2 # 线程数 + # paragraph_number: Optional[int] = 1 # 段落数量 diff --git a/app/services/llm.py b/app/services/llm.py index bafb925..6aa818e 100644 --- a/app/services/llm.py +++ b/app/services/llm.py @@ -352,7 +352,8 @@ def compress_video(input_path: str, output_path: str): input_path: 输入视频文件路径 output_path: 输出压缩后的视频文件路径 """ - ffmpeg_path = "E:\\projects\\NarratoAI_v0.1.2\\lib\\ffmpeg\\ffmpeg-7.0-essentials_build\\ffmpeg.exe" # 指定 ffmpeg 的完整路径 + # 指定 ffmpeg 的完整路径 + ffmpeg_path = os.getenv("FFMPEG_PATH") or config.app.get("ffmpeg_path") # 如果压缩后的视频文件已经存在，则直接使用 if os.path.exists(output_path): diff --git a/app/services/task.py b/app/services/task.py index c768e6a..0c544c2 100644 --- a/app/services/task.py +++ b/app/services/task.py @@ -326,17 +326,20 @@ def start(task_id, params: VideoParams, stop_at: str = "video"): def start_subclip(task_id, params: VideoClipParams, subclip_path_videos): """ 后台任务（自动剪辑视频进行剪辑） + + task_id: 任务ID + params: 剪辑参数 + subclip_path_videos: 视频文件路径 + """ logger.info(f"\n\n## 开始任务: {task_id}") sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=5) + # tts 角色名称 voice_name = voice.parse_voice_name(params.voice_name) - paragraph_number = params.paragraph_number - n_threads = params.n_threads - max_clip_duration = params.video_clip_duration logger.info("\n\n## 1. 读取视频json脚本") - video_script_path = path.join(params.video_clip_json) + video_script_path = path.join(params.video_clip_json_path) # 判断json文件是否存在 if path.exists(video_script_path): try: @@ -430,7 +433,7 @@ def start_subclip(task_id, params: VideoClipParams, subclip_path_videos): video_ost_list=video_ost, list_script=list_script, video_aspect=params.video_aspect, - threads=n_threads + threads=1 # 暂时只支持单线程 ) _progress += 50 / params.video_count / 2 diff --git a/app/utils/check_script.py b/app/utils/check_script.py new file mode 100644 index 0000000..e10bd3f --- /dev/null +++ b/app/utils/check_script.py @@ -0,0 +1,198 @@ +import json +from loguru import logger +import os +from datetime import datetime, timedelta +import re + + +def time_to_seconds(time_str): + time_obj = datetime.strptime(time_str, "%M:%S") + return timedelta(minutes=time_obj.minute, seconds=time_obj.second).total_seconds() + + +def seconds_to_time_str(seconds): + minutes, seconds = divmod(int(seconds), 60) + return f"{minutes:02d}:{seconds:02d}" + + +def check_script(file_path, total_duration): + with open(file_path, 'r', encoding='utf-8') as f: + data = json.load(f) + + errors = [] + ost_narrations = set() + last_end_time = 0 + + logger.info(f"开始检查文件: {file_path}") + logger.info(f"视频总时长: {total_duration:.2f} 秒") + logger.info("=" * 50) + + for i, item in enumerate(data, 1): + logger.info(f"\n检查第 {i} 项:") + + # 检查所有必需字段是否存在 + required_fields = ['picture', 'timestamp', 'narration', 'OST', 'new_timestamp'] + for field in required_fields: + if field not in item: + errors.append(f"第 {i} 项缺少 {field} 字段") + logger.info(f" - 错误: 缺少 {field} 字段") + else: + logger.info(f" - {field}: {item[field]}") + + # 检查 OST 为 false 的情况 + if item.get('OST') == False: + if not item.get('narration'): + errors.append(f"第 {i} 项 OST 为 false，但 narration 为空") + logger.info(" - 错误: OST 为 false，但 narration 为空") + elif len(item['narration']) > 30: + errors.append(f"第 {i} 项 OST 为 false，但 narration 超过 30 字") + logger.info(f" - 错误: OST 为 false，但 narration 超过 30 字 (当前: {len(item['narration'])} 字)") + else: + logger.info(" - OST 为 false，narration 检查通过") + + # 检查 OST 为 true 的情况 + if item.get('OST') == True: + if not item.get('narration').startswith('原声播放_'): + errors.append(f"第 {i} 项 OST 为 true，但 narration 不是 '原声播放_xxx' 格式") + logger.info(" - 错误: OST 为 true，但 narration 不是 '原声播放_xxx' 格式") + elif item['narration'] in ost_narrations: + errors.append(f"第 {i} 项 OST 为 true，但 narration '{item['narration']}' 不是唯一值") + logger.info(f" - 错误: OST 为 true，但 narration '{item['narration']}' 不是唯一值") + else: + logger.info(" - OST 为 true，narration 检查通过") + ost_narrations.add(item['narration']) + + # 检查 timestamp 是否重叠 + if 'timestamp' in item: + start, end = map(time_to_seconds, item['timestamp'].split('-')) + if start < last_end_time: + errors.append(f"第 {i} 项 timestamp '{item['timestamp']}' 与前一项重叠") + logger.info(f" - 错误: timestamp '{item['timestamp']}' 与前一项重叠") + else: + logger.info(f" - timestamp '{item['timestamp']}' 检查通过") + last_end_time = end + + # 检查 timestamp 是否超过总时长 + if end > total_duration: + errors.append(f"第 {i} 项 timestamp '{item['timestamp']}' 超过总时长 {total_duration:.2f} 秒") + logger.info(f" - 错误: timestamp '{item['timestamp']}' 超过总时长 {total_duration:.2f} 秒") + else: + logger.info(f" - timestamp 在总时长范围内") + + # 检查 new_timestamp 是否连续 + logger.info("\n检查 new_timestamp 连续性:") + last_end_time = 0 + for i, item in enumerate(data, 1): + if 'new_timestamp' in item: + start, end = map(time_to_seconds, item['new_timestamp'].split('-')) + if start != last_end_time: + errors.append(f"第 {i} 项 new_timestamp '{item['new_timestamp']}' 与前一项不连续") + logger.info(f" - 错误: 第 {i} 项 new_timestamp '{item['new_timestamp']}' 与前一项不连续") + else: + logger.info(f" - 第 {i} 项 new_timestamp '{item['new_timestamp']}' 连续性检查通过") + last_end_time = end + + if errors: + logger.info("检查结果：不通过") + logger.info("发现以下错误：") + for error in errors: + logger.info(f"- {error}") + fix_script(file_path, data, errors) + else: + logger.info("检查结果：通过") + logger.info("所有项目均符合规则要求。") + + +def fix_script(file_path, data, errors): + logger.info("\n开始修复脚本...") + fixed_data = [] + for i, item in enumerate(data, 1): + if item['OST'] == False and (not item['narration'] or len(item['narration']) > 30): + if not item['narration']: + logger.info(f"第 {i} 项 narration 为空，需要人工参与修复。") + fixed_data.append(item) + else: + logger.info(f"修复第 {i} 项 narration 超过 30 字的问题...") + fixed_items = split_narration(item) + fixed_data.extend(fixed_items) + else: + fixed_data.append(item) + + for error in errors: + if not error.startswith("第") or "OST 为 false" not in error: + logger.info(f"需要人工参与修复: {error}") + + # 生成新的文件名 + file_name, file_ext = os.path.splitext(file_path) + new_file_path = f"{file_name}_revise{file_ext}" + + # 保存修复后的数据到新文件 + with open(new_file_path, 'w', encoding='utf-8') as f: + json.dump(fixed_data, f, ensure_ascii=False, indent=4) + + logger.info(f"\n脚本修复完成，已保存到新文件: {new_file_path}") + + +def split_narration(item): + narration = item['narration'] + chunks = smart_split(narration) + + start_time, end_time = map(time_to_seconds, item['timestamp'].split('-')) + new_start_time, new_end_time = map(time_to_seconds, item['new_timestamp'].split('-')) + + total_duration = end_time - start_time + new_total_duration = new_end_time - new_start_time + chunk_duration = total_duration / len(chunks) + new_chunk_duration = new_total_duration / len(chunks) + + fixed_items = [] + for i, chunk in enumerate(chunks): + new_item = item.copy() + new_item['narration'] = chunk + + chunk_start = start_time + i * chunk_duration + chunk_end = chunk_start + chunk_duration + new_item['timestamp'] = f"{seconds_to_time_str(chunk_start)}-{seconds_to_time_str(chunk_end)}" + + new_chunk_start = new_start_time + i * new_chunk_duration + new_chunk_end = new_chunk_start + new_chunk_duration + new_item['new_timestamp'] = f"{seconds_to_time_str(new_chunk_start)}-{seconds_to_time_str(new_chunk_end)}" + + fixed_items.append(new_item) + + return fixed_items + + +def smart_split(text, target_length=30): + # 使用正则表达式分割文本，保留标点符号 + segments = re.findall(r'[^，。！？,!?]+[，。！？,!?]?', text) + result = [] + current_chunk = "" + + for segment in segments: + if len(current_chunk) + len(segment) <= target_length: + current_chunk += segment + else: + if current_chunk: + result.append(current_chunk.strip()) + current_chunk = segment + + if current_chunk: + result.append(current_chunk.strip()) + + # 如果有任何chunk超过了目标长度，进行进一步的分割 + final_result = [] + for chunk in result: + if len(chunk) > target_length: + sub_chunks = [chunk[i:i + target_length] for i in range(0, len(chunk), target_length)] + final_result.extend(sub_chunks) + else: + final_result.append(chunk) + + return final_result + + +if __name__ == "__main__": + file_path = "/Users/apple/Desktop/home/NarratoAI/resource/scripts/2024-0923-085036.json" + total_duration = 280 + check_script(file_path, total_duration) diff --git a/requirements.txt b/requirements.txt index cfe7295..a562dcb 100644 --- a/requirements.txt +++ b/requirements.txt @@ -24,3 +24,4 @@ opencv-python~=4.9.0.80 # https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/9-more-realistic-ai-voices-for-conversations-now-generally/ba-p/4099471 azure-cognitiveservices-speech~=1.37.0 git-changelog~=2.5.2 +watchdog==5.0.2 diff --git a/webui.py b/webui.py index 02fceb1..49d52f6 100644 --- a/webui.py +++ b/webui.py @@ -1,29 +1,5 @@ -import sys -import os -import glob -import json -import time -import datetime -import traceback import streamlit as st -from uuid import uuid4 -import platform -import streamlit.components.v1 as components -from loguru import logger - from app.config import config -from app.models.const import FILE_TYPE_VIDEOS -from app.models.schema import VideoClipParams, VideoAspect, VideoConcatMode -from app.services import task as tm, llm, voice, material -from app.utils import utils - -# # 将项目的根目录添加到系统路径中，以允许从项目导入模块 -root_dir = os.path.dirname(os.path.realpath(__file__)) -if root_dir not in sys.path: - sys.path.append(root_dir) - print("******** sys.path ********") - print(sys.path) - print("*" * 20) st.set_page_config( page_title="NarratoAI", @@ -37,6 +13,31 @@ st.set_page_config( }, ) +import sys +import os +import glob +import json +import time +import datetime +import traceback +from uuid import uuid4 +import platform +import streamlit.components.v1 as components +from loguru import logger + +from app.models.const import FILE_TYPE_VIDEOS +from app.models.schema import VideoClipParams, VideoAspect, VideoConcatMode +from app.services import task as tm, llm, voice, material +from app.utils import utils + +# # 将项目的根目录添加到系统路径中，以允许从项目导入模块 +root_dir = os.path.dirname(os.path.realpath(__file__)) +if root_dir not in sys.path: + sys.path.append(root_dir) + print("******** sys.path ********") + print(sys.path) + print("*" * 20) + proxy_url_http = config.proxy.get("http", "") or os.getenv("VPN_PROXY_URL", "") proxy_url_https = config.proxy.get("https", "") or os.getenv("VPN_PROXY_URL", "") os.environ["HTTP_PROXY"] = proxy_url_http @@ -59,8 +60,6 @@ i18n_dir = os.path.join(root_dir, "webui", "i18n") config_file = os.path.join(root_dir, "webui", ".streamlit", "webui.toml") system_locale = utils.get_system_locale() -if 'video_subject' not in st.session_state: - st.session_state['video_subject'] = '' if 'video_clip_json' not in st.session_state: st.session_state['video_clip_json'] = '' if 'video_plot' not in st.session_state: @@ -189,16 +188,7 @@ with st.expander(tr("Basic Settings"), expanded=False): if HTTPS_PROXY: config.proxy["https"] = HTTPS_PROXY - with middle_config_panel: - # openai - # moonshot (月之暗面) - # oneapi - # g4f - # azure - # qwen (通义千问) - # gemini - # ollama llm_providers = ['Gemini'] saved_llm_provider = config.app.get("llm_provider", "OpenAI").lower() saved_llm_provider_index = 0 @@ -470,6 +460,7 @@ with left_panel: else: st.error(tr("请先生成视频脚本")) + # 裁剪视频 with button_columns[1]: if st.button(tr("Crop Video"), key="auto_crop_video", use_container_width=True): @@ -479,50 +470,6 @@ with left_panel: with middle_panel: with st.container(border=True): st.write(tr("Video Settings")) - # video_concat_modes = [ - # (tr("Sequential"), "sequential"), - # (tr("Random"), "random"), - # ] - # video_sources = [ - # (tr("Pexels"), "pexels"), - # (tr("Pixabay"), "pixabay"), - # (tr("Local file"), "local"), - # (tr("TikTok"), "douyin"), - # (tr("Bilibili"), "bilibili"), - # (tr("Xiaohongshu"), "xiaohongshu"), - # ] - # - # saved_video_source_name = config.app.get("video_source", "pexels") - # saved_video_source_index = [v[1] for v in video_sources].index( - # saved_video_source_name - # ) - # - # selected_index = st.selectbox( - # tr("Video Source"), - # options=range(len(video_sources)), - # format_func=lambda x: video_sources[x][0], - # index=saved_video_source_index, - # ) - # params.video_source = video_sources[selected_index][1] - # config.app["video_source"] = params.video_source - # - # if params.video_source == "local": - # _supported_types = FILE_TYPE_VIDEOS + FILE_TYPE_IMAGES - # uploaded_files = st.file_uploader( - # "Upload Local Files", - # type=["mp4", "mov", "avi", "flv", "mkv", "jpg", "jpeg", "png"], - # accept_multiple_files=True, - # ) - - # selected_index = st.selectbox( - # tr("Video Concat Mode"), - # index=1, - # options=range(len(video_concat_modes)), # 使用索引作为内部选项值 - # format_func=lambda x: video_concat_modes[x][0], # 显示给用户的是标签 - # ) - # params.video_concat_mode = VideoConcatMode( - # video_concat_modes[selected_index][1] - # ) # 视频比例 video_aspect_ratios = [ @@ -582,8 +529,9 @@ with middle_panel: params.voice_name = voice_name config.ui["voice_name"] = voice_name + # 试听语言合成 if st.button(tr("Play Voice")): - play_content = params.video_subject + play_content = "这是一段试听语言" if not play_content: play_content = params.video_script if not play_content: @@ -779,6 +727,7 @@ with st.expander(tr("Video Check"), expanded=False): caijian() st.rerun() +# 开始按钮 start_button = st.button(tr("Generate Video"), use_container_width=True, type="primary") if start_button: config.save_config() @@ -800,10 +749,6 @@ if start_button: st.error(tr("视频文件不能为空")) scroll_to_bottom() st.stop() - if llm_provider != 'g4f' and not config.app.get(f"{llm_provider}_api_key", ""): - st.error(tr("请输入 LLM API 密钥")) - scroll_to_bottom() - st.stop() log_container = st.empty() log_records = []