Python如何对图片中的头像进行抠图(四种方法)

pip install opencv-python

import cv2
# 加载图片
image_path = "input.jpg"
image = cv2.imread(image_path)
# 加载 Haar 级联模型，用于人脸检测
haar_cascade_path = cv2.data.haarcascades + "haarcascade_frontalface_default.xml"
face_cascade = cv2.CascadeClassifier(haar_cascade_path)
# 转换为灰度图（检测需要用灰度图）
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# 检测人脸区域
faces = face_cascade.detectMultiScale(gray_image, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
if len(faces) == 0:
    print("没有检测到人脸")
else:
    for (x, y, w, h) in faces:
        # 提取人脸区域
        face_region = image[y:y+h, x:x+w]
        # 保存裁剪后的头像
        cv2.imwrite(f"face_{x}_{y}.png", face_region)
        print(f"保存裁剪的人脸区域到：face_{x}_{y}.png")
print("头像裁剪完成")

pip install dlib
pip install opencv-python

import dlib
import cv2
# 加载图片
image_path = "input.jpg"
image = cv2.imread(image_path)
# 加载 Dlib 的人脸检测器
detector = dlib.get_frontal_face_detector()
# 转换为灰度图（Dlib 人脸检测需要灰度图）
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# 检测人脸区域
faces = detector(gray_image)
if len(faces) == 0:
    print("没有检测到人脸")
else:
    # 遍历所有检测到的人脸
    for i, face in enumerate(faces):
        x, y, w, h = face.left(), face.top(), face.width(), face.height()
        # 提取头像区域
        face_region = image[y:y+h, x:x+w]
        # 保存裁剪后的头像
        cv2.imwrite(f"face_{i}.png", face_region)
        print(f"保存裁剪的人脸区域到：face_{i}.png")
print("头像裁剪完成")

pip install mtcnn
pip install opencv-python

import cv2
from mtcnn.mtcnn import MTCNN
# 加载图片
image_path = "input.jpg"
image = cv2.imread(image_path)
# 初始化 MTCNN 检测器
detector = MTCNN()
# 检测人脸区域
faces = detector.detect_faces(image)
if len(faces) == 0:
    print("没有检测到人脸")
else:
    for i, face in enumerate(faces):
        # 提取边界框
        x, y, w, h = face['box']
        # 裁剪头像区域
        face_region = image[y:y+h, x:x+w]
        # 保存裁剪后的头像
        cv2.imwrite(f"face_{i}.png", face_region)
        print(f"保存裁剪的人脸区域到：face_{i}.png")
print("头像裁剪完成")

pip install tensorflow keras opencv-python

from keras_facenet import FaceNet
import cv2
# 初始化 FaceNet 人脸检测器
detector = FaceNet()
# 加载图片
image_path = "input.jpg"
image = cv2.imread(image_path)
# 检测人脸
detections = detector.extract(image, threshold=0.95)
if len(detections) == 0:
    print("没有检测到人脸")
else:
    for i, detection in enumerate(detections):
        # 提取边界框
        x, y, w, h = detection['box']
        # 裁剪头像区域
        face_region = image[y:y+h, x:x+w]
        # 保存裁剪后的头像
        cv2.imwrite(f"face_{i}.png", face_region)
        print(f"保存裁剪的人脸区域到：face_{i}.png")
print("头像裁剪完成")