下载地址：https://www.pan38.com/share.php?code=pvvmX 提取码：8888 【仅供学习】
完整的人脸动画生成系统，包含眨眼、张嘴和头部运动检测功能。以下是完整的项目代码：
代码语言：txt复制
import cv2
import dlib
import numpy as np
from scipy.spatial import distance as dist
from collections import OrderedDict
import time
import os
# 面部特征点索引
FACIAL_LANDMARKS_IDXS = OrderedDict([
("mouth", (48, 68)),
("right_eyebrow", (17, 22)),
("left_eyebrow", (22, 27)),
("right_eye", (36, 42)),
("left_eye", (42, 48)),
("nose", (27, 36)),
("jaw", (0, 17))
])
class FaceAnimator:
def __init__(self):
self.detector = dlib.get_frontal_face_detector()
self.predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
self.ear_thresh = 0.25
self.ear_frames = 3
self.mar_thresh = 0.75
self.mar_frames = 3
self.head_movement_thresh = 15
self.head_movement_frames = 5
self.blink_counter = 0
self.mouth_open_counter = 0
self.head_movement_counter = 0
self.total_blinks = 0
self.total_mouth_opens = 0
self.total_head_movements = 0
self.prev_center = None
self.animation_frames = []
self.animation_delay = 0.1
def eye_aspect_ratio(self, eye):
A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
C = dist.euclidean(eye[0], eye[3])
ear = (A + B) / (2.0 * C)
return ear
def mouth_aspect_ratio(self, mouth):
A = dist.euclidean(mouth[13], mouth[19])
B = dist.euclidean(mouth[14], mouth[18])
C = dist.euclidean(mouth[15], mouth[17])
D = dist.euclidean(mouth[12], mouth[16])
mar = (A + B + C) / (3.0 * D)
return mar
def head_movement_detected(self, current_center):
if self.prev_center is None:
self.prev_center = current_center
return False
movement = dist.euclidean(current_center, self.prev_center)
self.prev_center = current_center
return movement > self.head_movement_thresh
def process_frame(self, frame):
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rects = self.detector(gray, 0)
for rect in rects:
shape = self.predictor(gray, rect)
shape = self.shape_to_np(shape)
left_eye = shape[42:48]
right_eye = shape[36:42]
mouth = shape[48:68]
left_ear = self.eye_aspect_ratio(left_eye)
right_ear = self.eye_aspect_ratio(right_eye)
ear = (left_ear + right_ear) / 2.0
mar = self.mouth_aspect_ratio(mouth)
face_center = np.mean(shape, axis=0)
head_moved = self.head_movement_detected(face_center)
if ear < self.ear_thresh:
self.blink_counter += 1
else:
if self.blink_counter >= self.ear_frames:
self.total_blinks += 1
self.animate_blink(frame, shape)
self.blink_counter = 0
if mar > self.mar_thresh:
self.mouth_open_counter += 1
else:
if self.mouth_open_counter >= self.mar_frames:
self.total_mouth_opens += 1
self.animate_mouth_open(frame, shape)
self.mouth_open_counter = 0
if head_moved:
self.head_movement_counter += 1
else:
if self.head_movement_counter >= self.head_movement_frames:
self.total_head_movements += 1
self.animate_head_movement(frame, shape)
self.head_movement_counter = 0
self.draw_landmarks(frame, shape)
return frame
def animate_blink(self, frame, shape):
left_eye = shape[42:48]
right_eye = shape[36:42]
for i in range(3):
temp_frame = frame.copy()
ratio = (i + 1) / 4.0
left_eye_closed = self.interpolate_eye(left_eye, ratio)
right_eye_closed = self.interpolate_eye(right_eye, ratio)
cv2.polylines(temp_frame, [left_eye_closed], True, (0, 0, 255), 2)
cv2.polylines(temp_frame, [right_eye_closed], True, (0, 0, 255), 2)
self.animation_frames.append(temp_frame)
time.sleep(self.animation_delay)
def animate_mouth_open(self, frame, shape):
mouth = shape[48:68]
for i in range(3):
temp_frame = frame.copy()
ratio = 1 + (i * 0.2)
mouth_open = self.interpolate_mouth(mouth, ratio)
cv2.polylines(temp_frame, [mouth_open], True, (0, 255, 0), 2)
self.animation_frames.append(temp_frame)
time.sleep(self.animation_delay)
def animate_head_movement(self, frame, shape):
for i in range(5):
temp_frame = frame.copy()
offset = (i - 2) * 5
moved_shape = shape.copy()
moved_shape[:, 0] += offset
self.draw_landmarks(temp_frame, moved_shape)
self.animation_frames.append(temp_frame)
time.sleep(self.animation_delay)
def interpolate_eye(self, eye, ratio):
center = np.mean(eye, axis=0)
interpolated = []
for point in eye:
new_point = center + ratio * (point - center)
interpolated.append(new_point)
return np.array(interpolated, dtype=np.int32)
def interpolate_mouth(self, mouth, ratio):
center = np.mean(mouth, axis=0)
interpolated = []
for point in mouth:
new_point = center + ratio * (point - center)
interpolated.append(new_point)
return np.array(interpolated, dtype=np.int32)
def shape_to_np(self, shape, dtype="int"):
coords = np.zeros((68, 2), dtype=dtype)
for i in range(0, 68):
coords[i] = (shape.part(i).x, shape.part(i).y)
return coords
def draw_landmarks(self, image, shape):
for (name, (i, j)) in FACIAL_LANDMARKS_IDXS.items():
pts = shape[i:j]
if name == "jaw":
for l in range(1, len(pts)):
ptA = tuple(pts[l - 1])
ptB = tuple(pts[l])
cv2.line(image, ptA, ptB, (255, 0, 0), 2)
else:
hull = cv2.convexHull(pts)
cv2.drawContours(image, [hull], -1, (0, 255, 0), 1)
def main():
animator = FaceAnimator()
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
if not ret:
break
frame = animator.process_frame(frame)
cv2.putText(frame, f"Blinks: {animator.total_blinks}", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.putText(frame, f"Mouth Opens: {animator.total_mouth_opens}", (10, 60),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
cv2.putText(frame, f"Head Movements: {animator.total_head_movements}", (10, 90),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0), 2)
cv2.imshow("Face Animator", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
main()
代码语言：txt复制
import cv2
import numpy as np
class AnimationUtils:
@staticmethod
def create_blinking_animation(frames, eye_coords, blink_frames=5):
animations = []
for i in range(blink_frames):
ratio = min(1.0, (i + 1) / blink_frames)
frame_copy = frames[-1].copy()
for eye in eye_coords:
center = np.mean(eye, axis=0)
new_eye = []
for point in eye:
new_point = center + ratio * (point - center)
new_eye.append(new_point)
new_eye = np.array(new_eye, dtype=np.int32)
cv2.polylines(frame_copy, [new_eye], True, (0, 0, 255), 2)
animations.append(frame_copy)
return animations
@staticmethod
def create_mouth_animation(frames, mouth_coords, open_frames=5, max_ratio=1.5):
animations = []
for i in range(open_frames):
ratio = 1.0 + (max_ratio - 1.0) * (i + 1) / open_frames
frame_copy = frames[-1].copy()
center = np.mean(mouth_coords, axis=0)
new_mouth = []
for point in mouth_coords:
new_point = center + ratio * (point - center)
new_mouth.append(new_point)
new_mouth = np.array(new_mouth, dtype=np.int32)
cv2.polylines(frame_copy, [new_mouth], True, (0, 255, 0), 2)
animations.append(frame_copy)
return animations
@staticmethod
def create_head_movement_animation(frames, all_coords, movement_frames=5, max_offset=20):
animations = []
for i in range(movement_frames):
offset = (i - movement_frames//2) * max_offset * 2 // movement_frames
frame_copy = frames[-1].copy()
new_coords = all_coords.copy()
new_coords[:, 0] += offset
for (name, (i, j)) in FACIAL_LANDMARKS_IDXS.items():
pts = new_coords[i:j]
if name == "jaw":
for l in range(1, len(pts)):
ptA = tuple(pts[l - 1])
ptB = tuple(pts[l])
cv2.line(frame_copy, ptA, ptB, (255, 0, 0), 2)
else:
hull = cv2.convexHull(pts)
cv2.drawContours(frame_copy, [hull], -1, (0, 255, 0), 1)
animations.append(frame_copy)
return animations
主程序、依赖文件和动画工具。主程序使用dlib进行人脸检测和特征点定位，实现了眨眼、张嘴和头部运动的检测与动画生成。系统可以实时处理摄像头输入，检测面部动作并生成相应的动画效果。使用时需要先安装列出的依赖项，并下载shape_predictor_68_face_landmarks.dat模型文件。