230 lines
8.0 KiB
Python
230 lines
8.0 KiB
Python
"""
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作者：太一
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微信：taiyi1224
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邮箱：shuobo1224@qq.com
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"""
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import cv2
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import numpy as np
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from PIL import Image, ImageDraw, ImageOps
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class ImageManager:
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"""图像管理工具类，处理图像加载、变换和保存"""
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@staticmethod
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def load_image(file_path):
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"""加载图像并转换为RGBA格式"""
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try:
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return Image.open(file_path).convert("RGBA")
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except Exception as e:
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print(f"加载图像失败: {e}")
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return None
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@staticmethod
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def apply_mask(image, shape):
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"""应用遮罩到图像"""
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if shape == "rect":
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return image # 矩形不需要遮罩
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# 创建与图像相同大小的透明遮罩
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mask = Image.new('L', image.size, 0)
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draw = ImageDraw.Draw(mask)
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# 根据形状绘制遮罩
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if shape == "round":
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# 圆形遮罩
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draw.ellipse((0, 0, image.size[0], image.size[1]), fill=255)
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elif shape == "heart":
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# 心形遮罩（简化版）
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x, y = image.size
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points = [
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(x // 2, y // 5),
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(x // 5, y // 2),
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(x // 5, y * 3 // 4),
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(x // 2, y * 4 // 5),
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(x * 4 // 5, y * 3 // 4),
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(x * 4 // 5, y // 2),
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(x // 2, y // 5)
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]
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draw.polygon(points, fill=255)
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elif shape == "star":
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# 星形遮罩（简化版）
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x, y = image.size
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center_x, center_y = x // 2, y // 2
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radius = min(center_x, center_y)
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points = []
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for i in range(10):
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angle = 0.1 * i * 3.14159
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r = radius if i % 2 == 0 else radius * 0.4
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points.append((
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center_x + r * (1 if i % 4 < 2 else -1) * abs(angle % (2 * 3.14159) - 3.14159 / 2) ** 0.5,
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center_y + r * (1 if i < 5 else -1) * abs(angle % (2 * 3.14159) - 3.14159) ** 0.5
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))
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draw.polygon(points, fill=255)
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# 应用遮罩
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return Image.composite(image, Image.new('RGBA', image.size, (0, 0, 0, 0)), mask)
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@staticmethod
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def transform_image(image, x, y, width, height, angle):
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"""应用缩放、旋转和位置变换"""
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import math
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# 确保宽度和高度大于0
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width = max(1, width)
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height = max(1, height)
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# 缩放
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scaled = image.resize((int(width), int(height)), Image.Resampling.LANCZOS)
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# 旋转
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if angle != 0:
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# 创建一个更大的画布以容纳旋转后的图像
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rotated_size = int(math.sqrt(width**2 + height**2)) * 2
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temp_canvas = Image.new('RGBA', (rotated_size, rotated_size), (0, 0, 0, 0))
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# 将缩放后的图像居中放置在临时画布上
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temp_x = (rotated_size - scaled.width) // 2
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temp_y = (rotated_size - scaled.height) // 2
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temp_canvas.paste(scaled, (temp_x, temp_y))
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# 旋转
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rotated = temp_canvas.rotate(angle, expand=True, resample=Image.Resampling.BILINEAR)
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# 计算新的偏移量
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offset_x = x - (rotated_size - scaled.width) // 2
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offset_y = y - (rotated_size - scaled.height) // 2
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return rotated, (offset_x, offset_y)
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else:
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# 如果没有旋转，直接返回缩放后的图像和位置
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return scaled, (x, y)
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@staticmethod
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def perspective_transform(image, vertices, output_size):
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"""应用透视变换，将图像映射到指定的四边形顶点"""
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try:
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import numpy as np
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import cv2
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# 获取图像尺寸
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img_width, img_height = image.size
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# 源坐标：图像的四个角
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src_points = np.float32([
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[0, 0],
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[img_width, 0],
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[0, img_height],
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[img_width, img_height]
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])
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# 目标坐标：指定的四个顶点
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# 确保顶点坐标是列表而不是元组
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dst_points = np.float32([list(v) for v in vertices])
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# 计算透视变换矩阵
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matrix = cv2.getPerspectiveTransform(src_points, dst_points)
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# 计算输出图像的尺寸
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output_width, output_height = output_size
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# 应用透视变换
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result = cv2.warpPerspective(
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np.array(image),
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matrix,
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(output_width, output_height),
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borderMode=cv2.BORDER_CONSTANT,
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borderValue=(0, 0, 0, 0) # 透明背景
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)
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# 转换回PIL图像
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return Image.fromarray(result)
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except ImportError:
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# 如果没有安装opencv，返回原始图像
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return image
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@staticmethod
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def transform_with_vertices(image, vertices):
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"""根据顶点坐标对图像进行变形"""
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try:
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import numpy as np
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import cv2
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# 获取图像尺寸
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img_width, img_height = image.size
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# 源坐标：图像的四个角
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src_points = np.float32([
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[0, 0],
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[img_width, 0],
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[0, img_height],
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[img_width, img_height]
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])
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# 目标坐标：指定的四个顶点
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dst_points = np.float32([list(v) for v in vertices])
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# 计算包围盒
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min_x = min(v[0] for v in dst_points)
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min_y = min(v[1] for v in dst_points)
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max_x = max(v[0] for v in dst_points)
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max_y = max(v[1] for v in dst_points)
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# 调整目标坐标为相对于包围盒的坐标
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adjusted_dst_points = dst_points - np.array([min_x, min_y])
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# 计算输出尺寸
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output_width = int(max_x - min_x)
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output_height = int(max_y - min_y)
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# 确保输出尺寸大于0
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output_width = max(1, output_width)
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output_height = max(1, output_height)
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# 计算透视变换矩阵
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matrix = cv2.getPerspectiveTransform(src_points, adjusted_dst_points)
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# 应用透视变换，使用透明背景
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result = cv2.warpPerspective(
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np.array(image),
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matrix,
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(output_width, output_height),
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borderMode=cv2.BORDER_CONSTANT,
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borderValue=(0, 0, 0, 0) # 透明背景而不是黑色背景
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)
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# 转换回PIL图像
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if len(result.shape) == 3 and result.shape[2] == 4: # 如果有alpha通道
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return Image.fromarray(result), (min_x, min_y)
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else: # 如果没有alpha通道
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return Image.fromarray(result).convert('RGBA'), (min_x, min_y)
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except ImportError:
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# 如果没有安装opencv，使用简单的变换
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min_x = min(v[0] for v in vertices)
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min_y = min(v[1] for v in vertices)
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# 确保返回的图像具有RGBA模式
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if image.mode != 'RGBA':
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image = image.convert('RGBA')
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return image, (min_x, min_y)
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@staticmethod
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def save_image(image, file_path, format='png', quality=95, keep_exif=False):
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"""保存图像到文件"""
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try:
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# 如果是JPEG格式，转换为RGB
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if format.lower() == 'jpeg':
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image = image.convert('RGB')
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# 保存图像
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image.save(
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file_path,
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format=format.upper(),
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quality=quality,
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exif=image.info.get('exif') if keep_exif else None
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)
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return True
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except Exception as e:
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print(f"保存图像失败: {e}")
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return False
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