i'm working on facial recognition project dlib, , managed return me list of facial keypoints in addition formed image:
relevant code:
def get_landmarks(im): rects = detector(im, 1) if len(rects) > 1: raise toomanyfaces if len(rects) == 0: raise nofaces return numpy.matrix([[p.x, p.y] p in predictor(im, rects[0]).parts()]) f in glob.glob(os.path.join(faces_folder_path, "*")): print("processing file: {}".format(f)) img = io.imread(f) win.clear_overlay() win.set_image(img) dets = detector(img, 1) print("number of faces detected: {}".format(len(dets))) k, d in enumerate(dets): # landmarks/parts face in box d. shape = predictor(img, d) lms = get_landmarks(img) print ("detection {}: left: {} top: {} right: {} bottom: {}".format(k, d.left(), d.top(), d.right(), d.bottom())) print ("part 0: {}, part 1: {} ...".format(shape.part(0), shape.part(1))) newsection() print ("keypoints:" + (str(lms))) # draw face landmarks on screen. win.add_overlay(shape) result:
now, need overlay them image, , that's ran problem. overlay code got matthew earl on github:
def annotate_landmarks(im, landmarks): im = im.copy() idx, point in enumerate(landmarks): pos = (point[0, 0], point[0, 1]) cv2.puttext(im, str(idx), pos, fontface=cv2.font_hershey_script_simplex, fontscale=0.4, color=(0, 0, 255)) cv2.circle(im, pos, 3, color=(0, 255, 255)) return im isn't integrating right rest of code:
win.add_overlay(dets) iwl = annotate_landmarks(img, lms) cv2.imshow("landmarks", iwl) dlib.hit_enter_to_continue() and when try display it, gives me tiny gray window nothing in it:
imb = im.copy() idx, point in enumerate(lms): pos = (point[0, 0], point[0, 1]) cv2.puttext(imb, str(idx), pos, fontface=cv2.font_hershey_script_simplex, fontscale=0.4, color=(0, 0, 255)) cv2.circle(im, pos, 3, color=(0, 255, 255)) width = 1000 height = 1000 cv2.namedwindow('image', cv2.window_normal) cv2.imshow('image', img) cv2.resizewindow('image', width, height) can show me i'm doing wrong here? need display points on image, this
edit: rest of code:
import sys import os import dlib import cv2 import glob import numpy skimage import io 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() 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() def newsection(): def terminal_size(): import fcntl, termios, struct h, w, hp, wp = struct.unpack('hhhh', fcntl.ioctl(0, termios.tiocgwinsz, struct.pack('hhhh', 0, 0, 0, 0))) return w ter_int = terminal_size() print ("\n" + ("_" * (int(ter_int))) + "\n\n") def get_landmarks(im): rects = detector(im, 1) if len(rects) > 1: raise toomanyfaces if len(rects) == 0: raise nofaces return numpy.matrix([[p.x, p.y] p in predictor(im, rects[0]).parts()]) f in glob.glob(os.path.join(faces_folder_path, "*")): print("processing file: {}".format(f)) img = io.imread(f) win.clear_overlay() # win.set_image(img) dets = detector(img, 1) print("number of faces detected: {}".format(len(dets))) k, d in enumerate(dets): # landmarks/parts face in box d. shape = predictor(img, d) lms = get_landmarks(img) print ("detection {}: left: {} top: {} right: {} bottom: {}".format(k, d.left(), d.top(), d.right(), d.bottom())) print ("part 0: {}, part 1: {} ...".format(shape.part(0), shape.part(1))) newsection() print ("keypoints:" + (str(lms))) # draw face landmarks on screen. # win.add_overlay(shape) win.add_overlay(dets) # iwl = annotate_landmarks(img, lms) # cv2.imshow("landmarks", iwl) dlib.hit_enter_to_continue() imb = im.copy() idx, point in enumerate(lms): pos = (point[0, 0], point[0, 1]) cv2.puttext(imb, str(idx), pos, fontface=cv2.font_hershey_script_simplex, fontscale=0.4, color=(0, 0, 255)) cv2.circle(im, pos, 3, color=(0, 255, 255)) width = 1000 height = 1000 cv2.namedwindow('image', cv2.window_normal) cv2.imshow('image', imb) cv2.resizewindow('image', width, height)
