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Copy pathFaceMeshModule.py
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103 lines (88 loc) · 3.93 KB
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import cv2
import mediapipe as mp
import time
import numpy as np
def correct_face_angle_2d(offset_angle, coords): # Angles in degrees, coords is a 2D np array
rotation_matrix = np.array(
[[np.cos(offset_angle), np.sin(offset_angle)], [np.sin(offset_angle) * (-1), np.cos(offset_angle)]])
transformed_coords = []
for coord in coords:
transformed_coords.append(np.matmul(coord, rotation_matrix))
return transformed_coords
def normalize_angle_and_size(mesh_coord, source_key_coord): # 1, 168 are key lms
mesh_coord, source_key_coord = np.array(mesh_coord), np.array(source_key_coord)
n_vector = source_key_coord[1] - source_key_coord[0]
target_n_vector = mesh_coord[168]-source_key_coord[1]
target_angle = np.arctan(target_n_vector[1]/target_n_vector[0])
target_length = np.sum(target_n_vector**2, axis=0)**0.5
source_length = np.sum(n_vector**2, axis=0)**0.5
scale_factor = source_length/target_length
angle = np.arctan(n_vector[1]/n_vector[0])
n_mesh_coord = mesh_coord - mesh_coord[1]
return correct_face_angle_2d(angle-target_angle, n_mesh_coord) + source_key_coord[0]
class FaceMeshDetector():
def __init__(self, staticMode=False, maxFaces=2, minDetectionCon=0.5, minTrackCon=0.5):
self.staticMode = staticMode
self.maxFaces = maxFaces
self.minDetectionCon = minDetectionCon
self.minTrackCon = minTrackCon
self.mpDraw = mp.solutions.drawing_utils
self.mpFaceMesh = mp.solutions.face_mesh
self.faceMesh = self.mpFaceMesh.FaceMesh(self.staticMode, self.maxFaces, False,
self.minDetectionCon, self.minTrackCon)
self.drawSpec = self.mpDraw.DrawingSpec(thickness=1, circle_radius=2)
def findFaceMesh(self, img, draw=True):
self.imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
self.results = self.faceMesh.process(self.imgRGB)
faces = []
if self.results.multi_face_landmarks:
for faceLms in self.results.multi_face_landmarks:
if draw:
self.mpDraw.draw_landmarks(img, faceLms, self.mpFaceMesh.FACEMESH_CONTOURS,
self.drawSpec, self.drawSpec)
print(self.mpFaceMesh.FACEMESH_LIPS)
face = []
for id,lm in enumerate(faceLms.landmark):
#print(lm)
ih, iw, ic = img.shape
x,y = int(lm.x*iw), int(lm.y*ih)
#print(id,x,y)
face.append([x,y])
faces.append(face)
return img, faces
def return_key_lms(self, img, draw=True):
self.imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
self.results = self.faceMesh.process(self.imgRGB)
faces = []
if self.results.multi_face_landmarks:
for faceLms in self.results.multi_face_landmarks:
if draw:
self.mpDraw.draw_landmarks(img, faceLms, self.mpFaceMesh.FACEMESH_CONTOURS,
self.drawSpec, self.drawSpec)
face = []
for id, lm in enumerate(faceLms.landmark):
# print(lm)
ih, iw, ic = img.shape
x, y = int(lm.x * iw), int(lm.y * ih)
# print(id,x,y)
face.append([x, y])
faces.append(face)
return img, faces
def main():
cap = cv2.VideoCapture(0)
pTime = 0
detector = FaceMeshDetector(maxFaces=2)
while True:
success, img = cap.read()
img, faces = detector.findFaceMesh(img)
if len(faces)!= 0:
print(type(faces[0]))
cTime = time.time()
fps = 1 / (cTime-pTime)
pTime = cTime
cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN,
3, (0, 255, 0), 3)
cv2.imshow("Image", img)
cv2.waitKey(1)
if __name__ == "__main__":
main()