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fix: auto-fix code issues (cron)

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- 修复重复导入/字段
- 修复异常处理
- 修复PEP8格式问题
- 修复语法错误（运算符空格问题）
- 修复类型注解格式
This commit is contained in:
AutoFix Bot
2026-03-02 06:09:49 +08:00
parent b83265e5fd
commit e23f1fec08
84 changed files with 9492 additions and 9491 deletions
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230
backend/multimodal_processor.py
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@@ -13,30 +13,30 @@ from dataclasses import dataclass
from pathlib import Path
# Constants
UUID_LENGTH = 8 # UUID 截断长度
UUID_LENGTH = 8 # UUID 截断长度
# 尝试导入OCR库
try:
import pytesseract
from PIL import Image
PYTESSERACT_AVAILABLE = True
PYTESSERACT_AVAILABLE = True
except ImportError:
PYTESSERACT_AVAILABLE = False
PYTESSERACT_AVAILABLE = False
try:
import cv2
CV2_AVAILABLE = True
CV2_AVAILABLE = True
except ImportError:
CV2_AVAILABLE = False
CV2_AVAILABLE = False
try:
import ffmpeg
FFMPEG_AVAILABLE = True
FFMPEG_AVAILABLE = True
except ImportError:
FFMPEG_AVAILABLE = False
FFMPEG_AVAILABLE = False
@dataclass
@@ -48,13 +48,13 @@ class VideoFrame:
frame_number: int
timestamp: float
frame_path: str
ocr_text: str = ""
ocr_confidence: float = 0.0
entities_detected: list[dict] = None
ocr_text: str = ""
ocr_confidence: float = 0.0
entities_detected: list[dict] = None
def __post_init__(self):
def __post_init__(self) -> None:
if self.entities_detected is None:
self.entities_detected = []
self.entities_detected = []
@dataclass
@@ -65,20 +65,20 @@ class VideoInfo:
project_id: str
filename: str
file_path: str
duration: float = 0.0
width: int = 0
height: int = 0
fps: float = 0.0
audio_extracted: bool = False
audio_path: str = ""
transcript_id: str = ""
status: str = "pending"
error_message: str = ""
metadata: dict = None
duration: float = 0.0
width: int = 0
height: int = 0
fps: float = 0.0
audio_extracted: bool = False
audio_path: str = ""
transcript_id: str = ""
status: str = "pending"
error_message: str = ""
metadata: dict = None
def __post_init__(self):
def __post_init__(self) -> None:
if self.metadata is None:
self.metadata = {}
self.metadata = {}
@dataclass
@@ -91,13 +91,13 @@ class VideoProcessingResult:
ocr_results: list[dict]
full_text: str # 整合的文本（音频转录 + OCR文本）
success: bool
error_message: str = ""
error_message: str = ""
class MultimodalProcessor:
"""多模态处理器 - 处理视频文件"""
def __init__(self, temp_dir: str = None, frame_interval: int = 5) -> None:
def __init__(self, temp_dir: str = None, frame_interval: int = 5) -> None:
"""
初始化多模态处理器
@@ -105,16 +105,16 @@ class MultimodalProcessor:
temp_dir: 临时文件目录
frame_interval: 关键帧提取间隔（秒）
"""
self.temp_dir = temp_dir or tempfile.gettempdir()
self.frame_interval = frame_interval
self.video_dir = os.path.join(self.temp_dir, "videos")
self.frames_dir = os.path.join(self.temp_dir, "frames")
self.audio_dir = os.path.join(self.temp_dir, "audio")
self.temp_dir = temp_dir or tempfile.gettempdir()
self.frame_interval = frame_interval
self.video_dir = os.path.join(self.temp_dir, "videos")
self.frames_dir = os.path.join(self.temp_dir, "frames")
self.audio_dir = os.path.join(self.temp_dir, "audio")
# 创建目录
os.makedirs(self.video_dir, exist_ok=True)
os.makedirs(self.frames_dir, exist_ok=True)
os.makedirs(self.audio_dir, exist_ok=True)
os.makedirs(self.video_dir, exist_ok = True)
os.makedirs(self.frames_dir, exist_ok = True)
os.makedirs(self.audio_dir, exist_ok = True)
def extract_video_info(self, video_path: str) -> dict:
"""
@@ -128,11 +128,11 @@ class MultimodalProcessor:
"""
try:
if FFMPEG_AVAILABLE:
probe = ffmpeg.probe(video_path)
video_stream = next(
probe = ffmpeg.probe(video_path)
video_stream = next(
(s for s in probe["streams"] if s["codec_type"] == "video"), None
)
audio_stream = next(
audio_stream = next(
(s for s in probe["streams"] if s["codec_type"] == "audio"), None
)
@@ -147,21 +147,21 @@ class MultimodalProcessor:
}
else:
# 使用 ffprobe 命令行
cmd = [
cmd = [
"ffprobe",
"-v",
"error",
"-show_entries",
"format=duration,bit_rate",
"format = duration, bit_rate",
"-show_entries",
"stream=width,height,r_frame_rate",
"stream = width, height, r_frame_rate",
"-of",
"json",
video_path,
]
result = subprocess.run(cmd, capture_output=True, text=True)
result = subprocess.run(cmd, capture_output = True, text = True)
if result.returncode == 0:
data = json.loads(result.stdout)
data = json.loads(result.stdout)
return {
"duration": float(data["format"].get("duration", 0)),
"width": int(data["streams"][0].get("width", 0)) if data["streams"] else 0,
@@ -177,7 +177,7 @@ class MultimodalProcessor:
return {"duration": 0, "width": 0, "height": 0, "fps": 0, "has_audio": False, "bitrate": 0}
def extract_audio(self, video_path: str, output_path: str = None) -> str:
def extract_audio(self, video_path: str, output_path: str = None) -> str:
"""
从视频中提取音频
@@ -189,20 +189,20 @@ class MultimodalProcessor:
提取的音频文件路径
"""
if output_path is None:
video_name = Path(video_path).stem
output_path = os.path.join(self.audio_dir, f"{video_name}.wav")
video_name = Path(video_path).stem
output_path = os.path.join(self.audio_dir, f"{video_name}.wav")
try:
if FFMPEG_AVAILABLE:
(
ffmpeg.input(video_path)
.output(output_path, ac=1, ar=16000, vn=None)
.output(output_path, ac = 1, ar = 16000, vn = None)
.overwrite_output()
.run(quiet=True)
.run(quiet = True)
)
else:
# 使用命令行 ffmpeg
cmd = [
cmd = [
"ffmpeg",
"-i",
video_path,
@@ -216,14 +216,14 @@ class MultimodalProcessor:
"-y",
output_path,
]
subprocess.run(cmd, check=True, capture_output=True)
subprocess.run(cmd, check = True, capture_output = True)
return output_path
except Exception as e:
print(f"Error extracting audio: {e}")
raise
def extract_keyframes(self, video_path: str, video_id: str, interval: int = None) -> list[str]:
def extract_keyframes(self, video_path: str, video_id: str, interval: int = None) -> list[str]:
"""
从视频中提取关键帧
@@ -235,31 +235,31 @@ class MultimodalProcessor:
Returns:
提取的帧文件路径列表
"""
interval = interval or self.frame_interval
frame_paths = []
interval = interval or self.frame_interval
frame_paths = []
# 创建帧存储目录
video_frames_dir = os.path.join(self.frames_dir, video_id)
os.makedirs(video_frames_dir, exist_ok=True)
video_frames_dir = os.path.join(self.frames_dir, video_id)
os.makedirs(video_frames_dir, exist_ok = True)
try:
if CV2_AVAILABLE:
# 使用 OpenCV 提取帧
cap = cv2.VideoCapture(video_path)
fps = cap.get(cv2.CAP_PROP_FPS)
cap = cv2.VideoCapture(video_path)
fps = cap.get(cv2.CAP_PROP_FPS)
int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
frame_interval_frames = int(fps * interval)
frame_number = 0
frame_interval_frames = int(fps * interval)
frame_number = 0
while True:
ret, frame = cap.read()
ret, frame = cap.read()
if not ret:
break
if frame_number % frame_interval_frames == 0:
timestamp = frame_number / fps
frame_path = os.path.join(
timestamp = frame_number / fps
frame_path = os.path.join(
video_frames_dir, f"frame_{frame_number:06d}_{timestamp:.2f}.jpg"
)
cv2.imwrite(frame_path, frame)
@@ -271,23 +271,23 @@ class MultimodalProcessor:
else:
# 使用 ffmpeg 命令行提取帧
Path(video_path).stem
output_pattern = os.path.join(video_frames_dir, "frame_%06d_%t.jpg")
output_pattern = os.path.join(video_frames_dir, "frame_%06d_%t.jpg")
cmd = [
cmd = [
"ffmpeg",
"-i",
video_path,
"-vf",
f"fps=1/{interval}",
f"fps = 1/{interval}",
"-frame_pts",
"1",
"-y",
output_pattern,
]
subprocess.run(cmd, check=True, capture_output=True)
subprocess.run(cmd, check = True, capture_output = True)
# 获取生成的帧文件列表
frame_paths = sorted(
frame_paths = sorted(
[
os.path.join(video_frames_dir, f)
for f in os.listdir(video_frames_dir)
@@ -313,19 +313,19 @@ class MultimodalProcessor:
return "", 0.0
try:
image = Image.open(image_path)
image = Image.open(image_path)
# 预处理：转换为灰度图
if image.mode != "L":
image = image.convert("L")
image = image.convert("L")
# 使用 pytesseract 进行 OCR
text = pytesseract.image_to_string(image, lang="chi_sim+eng")
text = pytesseract.image_to_string(image, lang = "chi_sim+eng")
# 获取置信度数据
data = pytesseract.image_to_data(image, output_type=pytesseract.Output.DICT)
confidences = [int(c) for c in data["conf"] if int(c) > 0]
avg_confidence = sum(confidences) / len(confidences) if confidences else 0
data = pytesseract.image_to_data(image, output_type = pytesseract.Output.DICT)
confidences = [int(c) for c in data["conf"] if int(c) > 0]
avg_confidence = sum(confidences) / len(confidences) if confidences else 0
return text.strip(), avg_confidence / 100.0
except Exception as e:
@@ -333,7 +333,7 @@ class MultimodalProcessor:
return "", 0.0
def process_video(
self, video_data: bytes, filename: str, project_id: str, video_id: str = None
self, video_data: bytes, filename: str, project_id: str, video_id: str = None
) -> VideoProcessingResult:
"""
处理视频文件：提取音频、关键帧、OCR
@@ -347,48 +347,48 @@ class MultimodalProcessor:
Returns:
视频处理结果
"""
video_id = video_id or str(uuid.uuid4())[:UUID_LENGTH]
video_id = video_id or str(uuid.uuid4())[:UUID_LENGTH]
try:
# 保存视频文件
video_path = os.path.join(self.video_dir, f"{video_id}_{filename}")
video_path = os.path.join(self.video_dir, f"{video_id}_{filename}")
with open(video_path, "wb") as f:
f.write(video_data)
# 提取视频信息
video_info = self.extract_video_info(video_path)
video_info = self.extract_video_info(video_path)
# 提取音频
audio_path = ""
audio_path = ""
if video_info["has_audio"]:
audio_path = self.extract_audio(video_path)
audio_path = self.extract_audio(video_path)
# 提取关键帧
frame_paths = self.extract_keyframes(video_path, video_id)
frame_paths = self.extract_keyframes(video_path, video_id)
# 对关键帧进行 OCR
frames = []
ocr_results = []
all_ocr_text = []
frames = []
ocr_results = []
all_ocr_text = []
for i, frame_path in enumerate(frame_paths):
# 解析帧信息
frame_name = os.path.basename(frame_path)
parts = frame_name.replace(".jpg", "").split("_")
frame_number = int(parts[1]) if len(parts) > 1 else i
timestamp = float(parts[2]) if len(parts) > 2 else i * self.frame_interval
frame_name = os.path.basename(frame_path)
parts = frame_name.replace(".jpg", "").split("_")
frame_number = int(parts[1]) if len(parts) > 1 else i
timestamp = float(parts[2]) if len(parts) > 2 else i * self.frame_interval
# OCR 识别
ocr_text, confidence = self.perform_ocr(frame_path)
ocr_text, confidence = self.perform_ocr(frame_path)
frame = VideoFrame(
id=str(uuid.uuid4())[:UUID_LENGTH],
video_id=video_id,
frame_number=frame_number,
timestamp=timestamp,
frame_path=frame_path,
ocr_text=ocr_text,
ocr_confidence=confidence,
frame = VideoFrame(
id = str(uuid.uuid4())[:UUID_LENGTH],
video_id = video_id,
frame_number = frame_number,
timestamp = timestamp,
frame_path = frame_path,
ocr_text = ocr_text,
ocr_confidence = confidence,
)
frames.append(frame)
@@ -404,29 +404,29 @@ class MultimodalProcessor:
all_ocr_text.append(ocr_text)
# 整合所有 OCR 文本
full_ocr_text = "\n\n".join(all_ocr_text)
full_ocr_text = "\n\n".join(all_ocr_text)
return VideoProcessingResult(
video_id=video_id,
audio_path=audio_path,
frames=frames,
ocr_results=ocr_results,
full_text=full_ocr_text,
success=True,
video_id = video_id,
audio_path = audio_path,
frames = frames,
ocr_results = ocr_results,
full_text = full_ocr_text,
success = True,
)
except Exception as e:
return VideoProcessingResult(
video_id=video_id,
audio_path="",
frames=[],
ocr_results=[],
full_text="",
success=False,
error_message=str(e),
video_id = video_id,
audio_path = "",
frames = [],
ocr_results = [],
full_text = "",
success = False,
error_message = str(e),
)
def cleanup(self, video_id: str = None) -> None:
def cleanup(self, video_id: str = None) -> None:
"""
清理临时文件
@@ -438,7 +438,7 @@ class MultimodalProcessor:
if video_id:
# 清理特定视频的文件
for dir_path in [self.video_dir, self.frames_dir, self.audio_dir]:
target_dir = (
target_dir = (
os.path.join(dir_path, video_id) if dir_path == self.frames_dir else dir_path
)
if os.path.exists(target_dir):
@@ -450,16 +450,16 @@ class MultimodalProcessor:
for dir_path in [self.video_dir, self.frames_dir, self.audio_dir]:
if os.path.exists(dir_path):
shutil.rmtree(dir_path)
os.makedirs(dir_path, exist_ok=True)
os.makedirs(dir_path, exist_ok = True)
# Singleton instance
_multimodal_processor = None
_multimodal_processor = None
def get_multimodal_processor(temp_dir: str = None, frame_interval: int = 5) -> MultimodalProcessor:
def get_multimodal_processor(temp_dir: str = None, frame_interval: int = 5) -> MultimodalProcessor:
"""获取多模态处理器单例"""
global _multimodal_processor
if _multimodal_processor is None:
_multimodal_processor = MultimodalProcessor(temp_dir, frame_interval)
_multimodal_processor = MultimodalProcessor(temp_dir, frame_interval)
return _multimodal_processor