110 lines
3.0 KiB
Python
Executable File
110 lines
3.0 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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人脸裁剪处理脚本
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从单张图像中检测人脸，裁剪并调整大小到指定尺寸
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"""
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import os
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from PIL import Image
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import numpy as np
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from .cpu_face_handler import CPUFaceHandler
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def get_scaled_bbox(
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bbox, img_w, img_h, ratio: float = 1.0, face_image: Image.Image = None
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):
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"""
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根据人脸边界框计算缩放后的裁剪区域
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Args:
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bbox: 人脸边界框 [x1, y1, x2, y2]
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img_w: 图像宽度
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img_h: 图像高度
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ratio: 缩放比例，数值越大，人脸在画面中的比例越小（周围留白越多）
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face_image: PIL Image 对象
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Returns:
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裁剪后的人脸图像
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"""
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x1, y1, x2, y2 = bbox
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# Calculate center point
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center_x = (x1 + x2) / 2
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center_y = (y1 + y2) / 2
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# Calculate width and height
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width = x2 - x1
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# Scale width and height
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new_width = width * ratio
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new_height = new_width
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# tile pix
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dis_x_left = new_width * 0.5
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dis_x_right = new_width - dis_x_left # 0.5new_width
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dis_y_up = new_height * 0.55
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dis_y_down = new_height - dis_y_up # 0.45new_height
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# Calculate new coordinates
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new_x1 = int(max(0, center_x - dis_x_left))
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new_y1 = int(max(0, center_y - dis_y_up))
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new_x2 = int(min(img_w, center_x + dis_x_right))
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new_y2 = int(min(img_h, center_y + dis_y_down))
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scaled_bbox = [new_x1, new_y1, new_x2, new_y2]
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crop_face = face_image.crop(scaled_bbox)
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return crop_face
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def process_image(
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input_path,
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face_ratio=2.0,
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target_size=(512, 512),
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):
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"""
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处理单张图像，进行人脸检测和裁剪
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Args:
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input_path: 输入图像路径
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face_ratio: 人脸缩放比例，建议范围：1.5-3.0，默认2.0
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target_size: 输出图像尺寸，默认(512, 512)
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Returns:
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imgae: 处理后的图像
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"""
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# 初始化人脸检测器
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face_detector = CPUFaceHandler()
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# 验证输入文件
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if not os.path.isfile(input_path):
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raise ValueError(f"File not found: {input_path}")
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try:
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# 读取图像
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image = Image.open(input_path)
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image = image.convert("RGB")
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image_rgb = np.array(image)
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img_h, img_w = image_rgb.shape[:2]
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# 检测人脸
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boxes, scores = face_detector(image_rgb)
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if len(boxes) == 0:
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raise ValueError("No face detected")
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# 转换边界框坐标（从相对坐标转为绝对坐标）
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boxes_abs = [
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boxes[0][0] * img_w,
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boxes[0][1] * img_h,
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boxes[0][2] * img_w,
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boxes[0][3] * img_h
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]
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# 裁剪人脸
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crop_face = get_scaled_bbox(boxes_abs, img_w, img_h, face_ratio, image)
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# 调整大小
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crop_face = crop_face.resize(target_size)
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return crop_face
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except Exception as e:
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raise ValueError(f"Error processing {input_path}: {e}") |