134 lines
5.4 KiB
Python
134 lines
5.4 KiB
Python
from pathlib import Path
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from PIL import Image as PILImage, ImageSequence
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from typing import Optional, Union
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import base64
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import io
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import numpy as np
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from src.common.logger import get_logger
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logger = get_logger("image_utils")
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class ImageUtils:
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@staticmethod
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def gif_2_static_image(gif_bytes: bytes, similarity_threshold: float = 1000.0, max_frames: int = 15) -> bytes:
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"""
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将GIF图片水平拼接为静态图像，跳过相似帧
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Args:
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gif_bytes (bytes): 输入的GIF图片字节数据
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similarity_threshold (float): 判定帧相似的阈值 (MSE)，越小表示要求差异越大才算不同帧，默认1000.0
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max_frames (int): 最大抽取的帧数，默认15
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Returns:
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bytes: 拼接后的静态图像字节数据，格式为JPEG
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Raises:
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ValueError: 如果输入的GIF无效或无法处理
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MemoryError: 如果处理过程中内存不足
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Exception: 其他异常
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"""
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with PILImage.open(io.BytesIO(gif_bytes)) as gif_image:
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if not gif_image.format or gif_image.format.lower() != "gif":
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logger.error("输入的图片不是有效的GIF格式")
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raise ValueError("输入的图片不是有效的GIF格式")
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# --- 流式迭代并选择帧（避免一次性加载所有帧） ---
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selected_frames: list[PILImage.Image] = []
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last_selected_frame_np = None
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frame_index = 0
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for frame in ImageSequence.Iterator(gif_image):
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# 确保是RGB格式方便比较
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frame_rgb = frame.convert("RGB")
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frame_np = np.array(frame_rgb)
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if frame_index == 0:
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selected_frames.append(frame_rgb.copy())
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last_selected_frame_np = frame_np
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else:
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# 计算和上一张选中帧的差异（均方误差 MSE）
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mse = np.mean((frame_np - last_selected_frame_np) ** 2)
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# logger.debug(f"帧 {frame_index} 与上一选中帧的 MSE: {mse}")
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if mse > similarity_threshold:
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selected_frames.append(frame_rgb.copy())
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last_selected_frame_np = frame_np
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if len(selected_frames) >= max_frames:
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break
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frame_index += 1
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if not selected_frames:
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logger.error("未能抽取到任何有效帧")
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raise ValueError("未能抽取到任何有效帧")
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# 获取选中的第一帧的尺寸（假设所有帧尺寸一致）
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frame_width, frame_height = selected_frames[0].size
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# 防止除以零
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if frame_height == 0:
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raise ValueError("帧高度为0，无法计算缩放尺寸")
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# 计算目标尺寸，保持宽高比
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target_height = 200 # 固定高度
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target_width = int((target_height / frame_height) * frame_width)
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# 宽度也不能是0
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if target_width == 0:
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logger.warning(f"计算出的目标宽度为0 (原始尺寸 {frame_width}x{frame_height})，调整为1")
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target_width = 1
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# 调整所有选中帧的大小
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resized_frames = [
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frame.resize((target_width, target_height), PILImage.Resampling.LANCZOS) for frame in selected_frames
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]
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# 创建拼接图像
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total_width = target_width * len(resized_frames)
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combined_image = PILImage.new("RGB", (total_width, target_height))
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# 水平拼接图像
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for idx, frame in enumerate(resized_frames):
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combined_image.paste(frame, (idx * target_width, 0))
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buffer = io.BytesIO()
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combined_image.save(buffer, format="JPEG", quality=85) # 保存为JPEG
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return buffer.getvalue()
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@staticmethod
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def image_bytes_to_base64(image_bytes: bytes) -> str:
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"""
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将图片字节数据转换为Base64编码字符串
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Args:
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image_bytes (bytes): 输入的图片字节数据
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Returns:
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str: Base64编码的图片字符串
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Raises:
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ValueError: 如果输入的图片字节数据无效
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"""
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if not image_bytes:
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logger.error("输入的图片字节数据无效")
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raise ValueError("输入的图片字节数据无效")
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return base64.b64encode(image_bytes).decode("utf-8")
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@staticmethod
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def image_path_to_base64(image_path: Union[str, Path]) -> Optional[str]:
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"""读取图片文件并转换为 Base64 编码字符串"""
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try:
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path = Path(image_path)
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if not path.exists():
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logger.error(f"图片文件不存在: {path}")
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return None
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image_bytes = path.read_bytes()
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return base64.b64encode(image_bytes).decode("utf-8")
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except Exception as e:
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logger.error(f"读取图片文件失败: {e}")
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return None
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@staticmethod
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def base64_to_image(base64_str: str, save_path: Union[str, Path]) -> bool:
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"""将 Base64 编码字符串解码并保存为图片文件"""
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try:
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image_bytes = base64.b64decode(base64_str)
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path = Path(save_path)
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_bytes(image_bytes)
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return True
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except Exception as e:
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logger.error(f"保存图片文件失败: {e}")
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return False
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