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代码实现了基于面部特征点的人脸动画生成，包括眨眼和张嘴动作。它使用dlib进行人脸检测和特征点定位，然后通过图像变形技术创建动画效果。请注意，这需要预先下载dlib的68点人脸特征点模型文件。

import cv2
import dlib
import numpy as np
from scipy.spatial import Delaunay
from skimage.transform import PiecewiseAffineTransform, warp

初始化dlib的人脸检测器和特征点预测器

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

def load_image(image_path):
img = cv2.imread(image_path)
if img is None:
raise ValueError(f"无法加载图像: {image_path}")
return cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

def get_landmarks(image):
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
rects = detector(gray, 1)
if len(rects) == 0:
raise ValueError("未检测到人脸")
shape = predictor(gray, rects[0])
return np.array([(shape.part(i).x, shape.part(i).y) for i in range(68)])

def create_blink_animation(image, landmarks, frames=10):

# 眼睛特征点索引（dlib 68点模型）
left_eye = landmarks[36:42]
right_eye = landmarks[42:48]

# 计算眼睛中心
left_eye_center = left_eye.mean(axis=0)
right_eye_center = right_eye.mean(axis=0)

# 创建动画帧
animation_frames = []
for i in range(frames):
    # 计算当前帧的闭合程度 (0=完全睁开, 1=完全闭合)
    if i < frames//2:
        close_ratio = i / (frames//2)
    else:
        close_ratio = (frames - i) / (frames//2)

    # 创建变形后的特征点
    deformed_landmarks = landmarks.copy()

    # 变形左眼
    for j in range(36, 42):
        original = landmarks[j]
        direction = left_eye_center - original
        deformed_landmarks[j] = original + direction * close_ratio * 0.7

    # 变形右眼
    for j in range(42, 48):
        original = landmarks[j]
        direction = right_eye_center - original
        deformed_landmarks[j] = original + direction * close_ratio * 0.7

    # 应用变形
    warped_img = warp_image(image, landmarks, deformed_landmarks)
    animation_frames.append(warped_img)

return animation_frames

def create_mouth_animation(image, landmarks, frames=10):

# 嘴巴特征点索引
mouth = landmarks[48:68]
mouth_center = mouth.mean(axis=0)

# 创建动画帧
animation_frames = []
for i in range(frames):
    # 计算张嘴程度 (0=闭合, 1=完全张开)
    if i < frames//2:
        open_ratio = i / (frames//2)
    else:
        open_ratio = (frames - i) / (frames//2)

    # 创建变形后的特征点
    deformed_landmarks = landmarks.copy()

    # 变形嘴巴
    for j in range(48, 68):
        original = landmarks[j]
        if j in [48, 54]:  # 嘴巴角落
            direction = np.array([0, -1]) * 10 * open_ratio
        else:
            direction = mouth_center - original
            direction = direction * 0.5 * open_ratio

        deformed_landmarks[j] = original + direction

    # 应用变形
    warped_img = warp_image(image, landmarks, deformed_landmarks)
    animation_frames.append(warped_img)

return animation_frames

def warp_image(image, src_points, dst_points):

# 创建三角剖分
tri = Delaunay(src_points)

# 创建PiecewiseAffineTransform对象
tform = PiecewiseAffineTransform()
tform.estimate(src_points[tri.simplices], dst_points[tri.simplices])

# 应用变形
warped = warp(image, tform, output_shape=image.shape[:2])
return (warped * 255).astype(np.uint8)

def save_animation(frames, output_path, fps=10):
height, width = frames[0].shape[:2]
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))

for frame in frames:
    out.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))

out.release()

def main():

# 加载图像
image_path = "input_face.jpg"
image = load_image(image_path)

# 获取特征点
landmarks = get_landmarks(image)

# 创建眨眼动画
blink_frames = create_blink_animation(image, landmarks)

# 创建张嘴动画
mouth_frames = create_mouth_animation(image, landmarks)

# 合并动画
combined_frames = blink_frames + mouth_frames

# 保存结果
save_animation(combined_frames, "output_animation.mp4")

print("动画生成完成!")

if name == "main":
main()