python ubuntu dlib人臉識別3-人臉對齊
阿新 • • 發佈:2018-12-02
人臉對齊主要用於提特徵。其他作用可以自行研究。
import sys import dlib if len(sys.argv) != 3: print( "Call this program like this:\n" " ./face_alignment.py shape_predictor_5_face_landmarks.dat ../examples/faces/bald_guys.jpg\n" "You can download a trained facial shape predictor from:\n" " http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2\n") exit() predictor_path = sys.argv[1] face_file_path = sys.argv[2] # Load all the models we need: a detector to find the faces, a shape predictor # to find face landmarks so we can precisely localize the face detector = dlib.get_frontal_face_detector() sp = dlib.shape_predictor(predictor_path) # Load the image using Dlib img = dlib.load_rgb_image(face_file_path) # Ask the detector to find the bounding boxes of each face. The 1 in the # second argument indicates that we should upsample the image 1 time. This # will make everything bigger and allow us to detect more faces. dets = detector(img, 1) num_faces = len(dets) if num_faces == 0: print("Sorry, there were no faces found in '{}'".format(face_file_path)) exit() # Find the 5 face landmarks we need to do the alignment. faces = dlib.full_object_detections() for detection in dets: faces.append(sp(img, detection)) window = dlib.image_window() # Get the aligned face images # Optionally: # images = dlib.get_face_chips(img, faces, size=160, padding=0.25) images = dlib.get_face_chips(img, faces, size=320) for image in images: window.set_image(image) dlib.hit_enter_to_continue() # It is also possible to get a single chip image = dlib.get_face_chip(img, faces[0]) window.set_image(image) dlib.hit_enter_to_continue()