import os import time import json from typing import List from app.schemas.llm import StoryGenerationRequest from loguru import logger from app.models.const import StoryType, ImageStyle from app.schemas.video import VideoGenerateRequest, StoryScene from app.services.llm import llm_service from app.services.voice import generate_voice from app.utils import utils from moviepy import ( VideoFileClip, ImageClip, AudioFileClip, TextClip, CompositeVideoClip, concatenate_videoclips, afx, ) from moviepy.video.tools import subtitles from moviepy.video.tools.subtitles import SubtitlesClip from PIL import Image, ImageDraw, ImageFont import numpy as np import requests import random def wrap_text(text, max_width, font="Arial", fontsize=60): # Create ImageFont font = ImageFont.truetype(font, fontsize) def get_text_size(inner_text): inner_text = inner_text.strip() left, top, right, bottom = font.getbbox(inner_text) return right - left, bottom - top width, height = get_text_size(text) if width <= max_width: return text, height # logger.warning(f"wrapping text, max_width: {max_width}, text_width: {width}, text: {text}") processed = True _wrapped_lines_ = [] words = text.split(" ") _txt_ = "" for word in words: _before = _txt_ _txt_ += f"{word} " _width, _height = get_text_size(_txt_) if _width <= max_width: continue else: if _txt_.strip() == word.strip(): processed = False break _wrapped_lines_.append(_before) _txt_ = f"{word} " _wrapped_lines_.append(_txt_) if processed: _wrapped_lines_ = [line.strip() for line in _wrapped_lines_] result = "\n".join(_wrapped_lines_).strip() height = len(_wrapped_lines_) * height # logger.warning(f"wrapped text: {result}") return result, height _wrapped_lines_ = [] chars = list(text) _txt_ = "" for word in chars: _txt_ += word _width, _height = get_text_size(_txt_) if _width <= max_width: continue else: _wrapped_lines_.append(_txt_) _txt_ = "" _wrapped_lines_.append(_txt_) result = "\n".join(_wrapped_lines_).strip() height = len(_wrapped_lines_) * height # logger.warning(f"wrapped text: {result}") return result, height async def create_video_with_scenes(task_dir: str, scenes: List[StoryScene], voice_name: str, voice_rate: float, test_mode: bool = False) -> str: """创建带有场景的视频 Args: task_dir (str): 任务目录 scenes (List[StoryScene]): 场景列表 voice_name (str): 语音名称 voice_rate (float): 语音速率 test_mode (bool): 是否为测试模式，如果是则使用已有的图片、音频、字幕文件 """ clips = [] for i, scene in enumerate(scenes, 1): try: # 获取文件路径 image_file = os.path.join(task_dir, f"{i}.png") audio_file = os.path.join(task_dir, f"{i}.mp3") subtitle_file = os.path.join(task_dir, f"{i}.srt") # 测试模式下检查文件是否存在 if test_mode: if not (os.path.exists(image_file) and os.path.exists(audio_file) and os.path.exists(subtitle_file)): logger.warning(f"Test mode: Required files not found for scene {i}") raise FileNotFoundError("Required files not found") else: # 正式模式下生成所需文件 logger.info(f"Processing scene {i}") audio_file, subtitle_file = await generate_voice( scene.text, voice_name, voice_rate, audio_file, subtitle_file ) # 获取字幕的总时长 subs = subtitles.file_to_subtitles(subtitle_file, encoding="utf-8") subtitle_duration = max([tb for ((ta, tb), txt) in subs]) # 创建图片剪辑 image_clip = ImageClip(image_file) origin_image_w, origin_image_h = image_clip.size # 获取放大后的图片尺寸 image_scale = 1.2 image_clip = image_clip.resized((origin_image_w*image_scale,origin_image_h*image_scale)) image_w, image_h = image_clip.size # 获取放大后的图片尺寸 # 确保图片视频时长至少和字幕一样长 image_clip = image_clip.with_duration(subtitle_duration) width_diff = origin_image_w * (image_scale-1) def debug_position(t): # print(f"当前时间 t = {t}", subtitle_duration, width_diff, width_diff/subtitle_duration*t) # 输出当前时间 return (-width_diff/subtitle_duration*t, 'center') image_clip = image_clip.with_position(debug_position) # 创建音频剪辑 audio_clip = AudioFileClip(audio_file) image_clip = image_clip.with_audio(audio_clip) # 使用系统字体 font_path = os.path.join(utils.resource_dir(), "fonts", "STHeitiLight.ttc") if not os.path.exists(font_path): logger.warning("Font file not found, using default font") raise FileNotFoundError("Font file not found: " + font_path) else: logger.info(f"Using font: {font_path}") print(f"Using font: {font_path}") # 添加字幕 if os.path.exists(subtitle_file): logger.info(f"Loading subtitle file: {subtitle_file}") try: def make_textclip(text): return TextClip( text=text, font=font_path, font_size=60, ) def create_text_clip(subtitle_item): phrase = subtitle_item[1] max_width = (origin_image_w * 0.9) wrapped_txt, txt_height = wrap_text( phrase, max_width=max_width, font=font_path, fontsize=60 ) _clip = TextClip( text=wrapped_txt, font=font_path, font_size=60, color="white", stroke_color="black", stroke_width=2, ) duration = subtitle_item[0][1] - subtitle_item[0][0] _clip = _clip.with_start(subtitle_item[0][0]) _clip = _clip.with_end(subtitle_item[0][1]) _clip = _clip.with_duration(duration) _clip = _clip.with_position(("center", origin_image_h * 0.95 - _clip.h - 50)) return _clip sub = SubtitlesClip(subtitle_file, encoding="utf-8", make_textclip=make_textclip) text_clips = [] for item in sub.subtitles: clip = create_text_clip(subtitle_item=item) text_clips.append(clip) video_clip = CompositeVideoClip([image_clip, *text_clips], (origin_image_w, origin_image_h)) clips.append(video_clip) logger.info(f"Added subtitles for scene {i}") except Exception as e: logger.error(f"Failed to add subtitles for scene {i}: {str(e)}") clips.append(image_clip) else: logger.warning(f"Subtitle file not found: {subtitle_file}") clips.append(image_clip) except Exception as e: logger.error(f"Failed to process scene {i}: {str(e)}") raise e if not clips: raise ValueError("No valid clips to combine") # 合并所有片段 logger.info("Merging all clips") final_clip = concatenate_videoclips(clips) video_file = os.path.join(task_dir, "video.mp4") logger.info(f"Writing video to {video_file}") final_clip.write_videofile(video_file, fps=24, codec='libx264', audio_codec='aac') return video_file async def generate_video(request: VideoGenerateRequest): """生成视频 Args: request (VideoGenerateRequest): 视频生成请求 """ try: # 测试模式下，从 story.json 中读取请求参数 if request.test_mode: task_id = request.task_id or str(int(time.time())) task_dir = utils.task_dir(task_id) if not os.path.exists(task_dir): raise ValueError(f"Task directory not found: {task_dir}") # 从 story.json 中读取数据 story_file = os.path.join(task_dir, "story.json") if not os.path.exists(story_file): raise ValueError(f"Story file not found: {story_file}") with open(story_file, "r", encoding="utf-8") as f: story_data = json.load(f) print("story_data", story_data) request = VideoGenerateRequest(**story_data) request.test_mode = True scenes = [StoryScene(**scene) for scene in story_data.get("scenes", [])] else: req = StoryGenerationRequest( resolution=request.resolution, story_prompt=request.story_prompt, language=request.language, segments=request.segments, text_llm_provider=request.text_llm_provider, text_llm_model=request.text_llm_model, image_llm_provider=request.image_llm_provider, image_llm_model=request.image_llm_model ) story_list = await llm_service.generate_story_with_images(request=req) scenes = [StoryScene(text=scene["text"], image_prompt=scene["image_prompt"], url=scene["url"]) for scene in story_list] # 保存 story.json story_data = request.model_dump() story_data["scenes"] = [scene.model_dump() for scene in scenes] task_id = str(int(time.time())) task_dir = utils.task_dir(task_id) os.makedirs(task_dir, exist_ok=True) story_file = os.path.join(task_dir, "story.json") for i, scene in enumerate(story_list, 1): if scene.get("url"): image_path = os.path.join(task_dir, f"{i}.png") try: response = requests.get(scene["url"]) if response.status_code == 200: with open(image_path, "wb") as f: f.write(response.content) logger.info(f"Downloaded image {i} to {image_path}") except Exception as e: logger.error(f"Failed to download image {i}: {e}") with open(story_file, "w", encoding="utf-8") as f: json.dump(story_data, f, ensure_ascii=False, indent=2) # return "" # 生成视频 return await create_video_with_scenes(task_dir, scenes, request.voice_name, request.voice_rate, request.test_mode) except Exception as e: logger.error(f"Failed to generate video: {e}") raise e