-
Notifications
You must be signed in to change notification settings - Fork 262
/
video_pipeline.py
178 lines (157 loc) · 6.95 KB
/
video_pipeline.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
import requests
import json
import os
import time
from typing import Dict, Any
class VideoPipeline:
def __init__(self, base_url: str = "http://127.0.0.1:8080"):
self.base_url = base_url
def download_video(self, url: str, resolution: str = "1080p",
output_format: str = "mp4", rename: str = None) -> Dict[str, Any]:
"""下载视频的第一步"""
endpoint = f"{self.base_url}/api/v2/youtube/download"
payload = {
"url": url,
"resolution": resolution,
"output_format": output_format,
"rename": rename or time.strftime("%Y-%m-%d")
}
response = requests.post(endpoint, json=payload)
response.raise_for_status()
return response.json()
def generate_script(self, video_path: str, skip_seconds: int = 0,
threshold: int = 30, vision_batch_size: int = 10,
vision_llm_provider: str = "gemini") -> Dict[str, Any]:
"""生成脚本的第二步"""
endpoint = f"{self.base_url}/api/v2/scripts/generate"
payload = {
"video_path": video_path,
"skip_seconds": skip_seconds,
"threshold": threshold,
"vision_batch_size": vision_batch_size,
"vision_llm_provider": vision_llm_provider
}
response = requests.post(endpoint, json=payload)
response.raise_for_status()
return response.json()
def crop_video(self, video_path: str, script: list) -> Dict[str, Any]:
"""剪辑视频的第三步"""
endpoint = f"{self.base_url}/api/v2/scripts/crop"
payload = {
"video_origin_path": video_path,
"video_script": script
}
response = requests.post(endpoint, json=payload)
response.raise_for_status()
return response.json()
def generate_final_video(self, task_id: str, video_path: str,
script_path: str, script: list, subclip_videos: Dict[str, str], voice_name: str) -> Dict[str, Any]:
"""生成最终视频的第四步"""
endpoint = f"{self.base_url}/api/v2/scripts/start-subclip"
request_data = {
"video_clip_json": script,
"video_clip_json_path": script_path,
"video_origin_path": video_path,
"video_aspect": "16:9",
"video_language": "zh-CN",
"voice_name": voice_name,
"voice_volume": 1,
"voice_rate": 1.2,
"voice_pitch": 1,
"bgm_name": "random",
"bgm_type": "random",
"bgm_file": "",
"bgm_volume": 0.3,
"subtitle_enabled": True,
"subtitle_position": "bottom",
"font_name": "STHeitiMedium.ttc",
"text_fore_color": "#FFFFFF",
"text_background_color": "transparent",
"font_size": 75,
"stroke_color": "#000000",
"stroke_width": 1.5,
"custom_position": 70,
"n_threads": 8
}
payload = {
"request": request_data,
"subclip_videos": subclip_videos
}
params = {"task_id": task_id}
response = requests.post(endpoint, params=params, json=payload)
response.raise_for_status()
return response.json()
def save_script_to_json(self, script: list, script_path: str) -> str:
"""保存脚本到json文件"""
try:
with open(script_path, 'w', encoding='utf-8') as f:
json.dump(script, f, ensure_ascii=False, indent=2)
print(f"脚本已保存到: {script_path}")
return script_path
except Exception as e:
print(f"保存脚本失败: {str(e)}")
raise
def run_pipeline(self, task_id: str, script_name: str, youtube_url: str, video_name: str="null", skip_seconds: int = 0, threshold: int = 30, vision_batch_size: int = 10, vision_llm_provider: str = "gemini", voice_name: str = "zh-CN-YunjianNeural") -> Dict[str, Any]:
"""运行完整的pipeline"""
try:
current_path = os.path.dirname(os.path.abspath(__file__))
video_path = os.path.join(current_path, "resource", "videos", f"{video_name}.mp4")
# 判断视频是否存在
if not os.path.exists(video_path):
# 1. 下载视频
print(f"视频不存在, 开始下载视频: {video_path}")
download_result = self.download_video(url=youtube_url, resolution="1080p", output_format="mp4", rename=video_name)
video_path = download_result["output_path"]
else:
print(f"视频已存在: {video_path}")
# 2. 判断script_name是否存在
# 2.1.1 拼接脚本路径 NarratoAI/resource/scripts
script_path = os.path.join(current_path, "resource", "scripts", script_name)
if os.path.exists(script_path):
script = json.load(open(script_path, "r", encoding="utf-8"))
else:
# 2.1.2 生成脚本
print("开始生成脚本...")
script_result = self.generate_script(video_path=video_path, skip_seconds=skip_seconds, threshold=threshold, vision_batch_size=vision_batch_size, vision_llm_provider=vision_llm_provider)
script = script_result["script"]
# 2.2 保存脚本到json文件
print("保存脚本到json文件...")
self.save_script_to_json(script=script, script_path=script_path)
# 3. 剪辑视频
print("开始剪辑视频...")
crop_result = self.crop_video(video_path=video_path, script=script)
subclip_videos = crop_result["subclip_videos"]
# 4. 生成最终视频
print("开始生成最终视频...")
self.generate_final_video(
task_id=task_id,
video_path=video_path,
script_path=script_path,
script=script,
subclip_videos=subclip_videos,
voice_name=voice_name
)
return {
"status": "等待异步生成视频",
"path": os.path.join(current_path, "storage", "tasks", task_id)
}
except Exception as e:
return {
"status": "error",
"error": str(e)
}
# 使用示例
if __name__ == "__main__":
pipeline = VideoPipeline()
result = pipeline.run_pipeline(
task_id="test_111901",
script_name="test.json",
youtube_url="https://www.youtube.com/watch?v=vLJ7Yed6FQ4",
video_name="2024-11-19-01",
skip_seconds=50,
threshold=35,
vision_batch_size=10,
vision_llm_provider="gemini",
voice_name="zh-CN-YunjianNeural",
)
print(result)