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import numpy as np
import mediapipe as mp
from mediapipe.tasks.python import vision, BaseOptions
class Landmark478:
def __init__(self, task_path):
base_options = BaseOptions(model_asset_path=task_path)
options = vision.FaceLandmarkerOptions(
base_options=base_options,
output_face_blendshapes=True,
output_facial_transformation_matrixes=True,
num_faces=1,
)
detector = vision.FaceLandmarker.create_from_options(options)
self.detector = detector
def detect_from_imp(self, imp):
image = mp.Image.create_from_file(imp)
detection_result = self.detector.detect(image)
return detection_result
def detect_from_npimage(self, img):
image = mp.Image(image_format=mp.ImageFormat.SRGB, data=img)
detection_result = self.detector.detect(image)
return detection_result
@staticmethod
def mplmk_to_nplmk(results):
face_landmarks_list = results.face_landmarks
np_lms = []
for face_lms in face_landmarks_list:
lms = [[lm.x, lm.y, lm.z] for lm in face_lms]
np_lms.append(lms)
return np.array(np_lms).astype(np.float32)
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