python ubuntu dlib 6- 人臉檢測並畫出輪廓
阿新 • • 發佈:2018-12-02
對輸入圖片進行人臉檢測,畫出人臉輪廓
import sys import os import dlib import glob if len(sys.argv) != 3: print( "Give the path to the trained shape predictor model as the first " "argument and then the directory containing the facial images.\n" "For example, if you are in the python_examples folder then " "execute this program by running:\n" " ./face_landmark_detection.py shape_predictor_68_face_landmarks.dat ../examples/faces\n" "You can download a trained facial shape predictor from:\n" " http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2") exit() predictor_path = sys.argv[1] faces_folder_path = sys.argv[2] detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor(predictor_path) win = dlib.image_window() for f in glob.glob(os.path.join(faces_folder_path, "*.jpg")): print("Processing file: {}".format(f)) img = dlib.load_rgb_image(f) win.clear_overlay() win.set_image(img) # 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) print("Number of faces detected: {}".format(len(dets))) for k, d in enumerate(dets): print("Detection {}: Left: {} Top: {} Right: {} Bottom: {}".format( k, d.left(), d.top(), d.right(), d.bottom())) # Get the landmarks/parts for the face in box d. shape = predictor(img, d) print("Part 0: {}, Part 1: {} ...".format(shape.part(0), shape.part(1))) # Draw the face landmarks on the screen. win.add_overlay(shape) win.add_overlay(dets) dlib.hit_enter_to_continue()