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testeFaceMesh.py
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import cv2
import mediapipe as mp
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_face_mesh = mp.solutions.face_mesh
# For static images:
IMAGE_FILES = ['selfie.jpeg']
drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
with mp_face_mesh.FaceMesh(
static_image_mode=True,
max_num_faces=1,
refine_landmarks=True,
min_detection_confidence=0.5) as face_mesh:
for idx, file in enumerate(IMAGE_FILES):
image = cv2.imread(file)
# Convert the BGR image to RGB before processing.
results = face_mesh.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
# Print and draw face mesh landmarks on the image.
if not results.multi_face_landmarks:
continue
annotated_image = image.copy()
annotated_image1 = image.copy()
for face_landmarks in results.multi_face_landmarks:
print('face_landmarks:', face_landmarks)
mp_drawing.draw_landmarks(
image=annotated_image,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_TESSELATION,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles
.get_default_face_mesh_tesselation_style())
mp_drawing.draw_landmarks(
image=annotated_image,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_CONTOURS,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles
.get_default_face_mesh_contours_style())
mp_drawing.draw_landmarks(
image=annotated_image,
landmark_list=face_landmarks,
connections=mp_face_mesh.FACEMESH_IRISES,
landmark_drawing_spec=None,
connection_drawing_spec=mp_drawing_styles
.get_default_face_mesh_iris_connections_style())
cv2.imwrite('/tmp/annotated_image' + str(idx) + '.png', annotated_image)
#Tentando fazer apenas os pontos desejados
for face_landmarks in results.multi_face_landmarks:
##########################################
for landmarks in face_landmarks.landmark:
x = landmarks.x
y = landmarks.y
shape = annotated_image1.shape
relative_x = int(x*shape[1])
relative_y = int(y*shape[0])
cv2.circle(annotated_image1, (relative_x, relative_y), radius=1, color=(255,0,100), thickness=1)
##########################################
# print('face_landmarks:', face_landmarks)
# mp_drawing.draw_landmarks(
# image=annotated_image1,
# landmark_list=face_landmarks,
# connections=mp_face_mesh.FACEMESH_TESSELATION, #essa parte faz o tecido
# landmark_drawing_spec=None,
# connection_drawing_spec=mp_drawing_styles
# .get_default_face_mesh_tesselation_style())
# mp_drawing.draw_landmarks(
# image=annotated_image1,
# landmark_list=face_landmarks,
# connections=mp_face_mesh.FACEMESH_CONTOURS, #essa parte faz o contorno da face apenas
# landmark_drawing_spec=None,
# connection_drawing_spec=mp_drawing_styles
# .get_default_face_mesh_contours_style())
# mp_drawing.draw_landmarks(
# image=annotated_image1,
# landmark_list=face_landmarks,
# connections=mp_face_mesh.FACEMESH_IRISES, #essa parte faz o contorno da iris
# landmark_drawing_spec=None,
# connection_drawing_spec=mp_drawing_styles
# .get_default_face_mesh_iris_connections_style())
cv2.imwrite('/tmp/annotated_image' + str(idx) + '.png', annotated_image1)
cv2.imshow('Press q to kill', annotated_image)
cv2.imshow('Press q to kill1', annotated_image1)
print(len(face_landmarks.landmark))
# cv2.imshow('2',results)
while True:
if cv2.waitKey(1) == ord('q'):
break
cv2.waitKey(3000)
cv2.destroyAllWindows()
# # For webcam input:
# drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
# cap = cv2.VideoCapture(0)
# with mp_face_mesh.FaceMesh(
# max_num_faces=1,
# refine_landmarks=True,
# min_detection_confidence=0.5,
# min_tracking_confidence=0.5) as face_mesh:
# while cap.isOpened():
# success, image = cap.read()
# if not success:
# print("Ignoring empty camera frame.")
# # If loading a video, use 'break' instead of 'continue'.
# continue
# # To improve performance, optionally mark the image as not writeable to
# # pass by reference.
# image.flags.writeable = False
# image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# results = face_mesh.process(image)
# # Draw the face mesh annotations on the image.
# image.flags.writeable = True
# image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# if results.multi_face_landmarks:
# for face_landmarks in results.multi_face_landmarks:
# mp_drawing.draw_landmarks(
# image=image,
# landmark_list=face_landmarks,
# connections=mp_face_mesh.FACEMESH_TESSELATION,
# landmark_drawing_spec=None,
# connection_drawing_spec=mp_drawing_styles
# .get_default_face_mesh_tesselation_style())
# mp_drawing.draw_landmarks(
# image=image,
# landmark_list=face_landmarks,
# connections=mp_face_mesh.FACEMESH_CONTOURS,
# landmark_drawing_spec=None,
# connection_drawing_spec=mp_drawing_styles
# .get_default_face_mesh_contours_style())
# mp_drawing.draw_landmarks(
# image=image,
# landmark_list=face_landmarks,
# connections=mp_face_mesh.FACEMESH_IRISES,
# landmark_drawing_spec=None,
# connection_drawing_spec=mp_drawing_styles
# .get_default_face_mesh_iris_connections_style())
# # Flip the image horizontally for a selfie-view display.
# cv2.imshow('MediaPipe Face Mesh', cv2.flip(image, 1))
# if cv2.waitKey(5) & 0xFF == 27:
# break
# cap.release()