CocoPi_All_Files/preset/app/16_faceComparison.py

'''
    Face recognize demo, download model from maixhub first:
            https://maixhub.com/
'''

from maix import nn, display, camera, image
from maix.nn.app import face
from maix.nn.app.face import FaceRecognize
import time
import sys
sys.path.append('/root/')
from CocoPi import BUTTON

key_A = BUTTON(14)
key_B = BUTTON(8)
key_C = BUTTON(13)
key_D = BUTTON(7)
ScreenOrientation = False
class Face_Recognizer:
    def __init__(self, threshold = 0.5, nms = 0.3, max_face_num = 1):
        model = "/root/preset/model/retinaface.mud"
        model_fe = "/root/preset/model/fe_resnet.mud"
        self.input_size = (224, 224, 3)
        input_size_fe = (128, 128, 3)
        self.feature_len = 256
        self.features = []
        print("-- load model:", model)
        m = nn.load(model)
        print("-- load ok")
        print("-- load model:", model_fe)
        m_fe = nn.load(model_fe)
        print("-- load ok")

        self.recognizer = FaceRecognize(m, m_fe, self.feature_len, self.input_size, threshold, nms, max_face_num)
        print("-- init end")

    def get_faces(self, img, std_img = False):
        faces = self.recognizer.get_faces(img, std_img)
        return faces

    def __len__(self):
        return len(self.features)

    def add_user(self, name, feature):
        self.features.append([name, feature])
        return True

    def remove_user(self, name_del):
        rm = None
        for name, feature in self.features:
            if name_del == name:
                rm = [name, feature]
        if rm:
            self.features.remove(rm)
            return True
        return False

    def recognize(self, feature):
        max_score = 0
        uid = -1
        for i, user in enumerate(self.features):
            score = self.recognizer.compare(user[1], feature)
            if score > max_score:
                max_score = score
                uid = i
        if uid >= 0:
            return self.features[uid][0], max_score
        return None, 0


    def get_input_size(self):
        '''
            @return input_size (w, h, c)
        '''
        return self.input_size

    def get_feature_len(self):
        return self.feature_len

    def darw_info(self, img, box, points, disp_str, bg_color=(255, 0, 0, 255), font_color=(255, 255, 255, 255), font_size=32):
        font_wh = image.get_string_size(disp_str)
        for p in points:
            img.draw_rectangle(p[0] - 1, p[1] -1, p[0] + 1, p[1] + 1, color=bg_color)
        img.draw_rectangle(box[0], box[1], box[0] + box[2], box[1] + box[3], color=bg_color, thickness=2)
        if disp_str:
            img.draw_rectangle(box[0], box[1] - font_wh[1], box[0] + font_wh[0], box[1], color=bg_color, thickness = -1)
            img.draw_string(box[0], box[1] - font_wh[1], disp_str, color=font_color)


    def darw_title(self, img, dis_size ,key_l = None, key_r =None):
        if key_C:
            key_l = "| "+ key_l
            img.draw_string( 1, 2 ,key_l , scale = 1, color = (255, 255, 255), thickness = 2)
        if key_D:
            key_r = key_r+" |"
            w = int(dis_size[0] - 4 - image.get_string_size(key_r)[0] * 1)
            img.draw_string( w, 2 ,key_r , scale = 1, color = (255, 255, 255), thickness = 2)



max_face_num = 4
detect_threshold = 0.5
detect_nms = 0.3
score_threshold = 70
names = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"]

face_recognizer = Face_Recognizer(detect_threshold, detect_nms, max_face_num = max_face_num)
camera.config(size=face_recognizer.get_input_size()[:2])

def lcdRotation(inputImg,rotationAngle):
    from maix import image
    imageRotationBuffer = inputImg.crop(0, 0, 240, 320)
    if ScreenOrientation:
        imgRotationAim = image.new(size = (240, 320))
    else:
        imgRotationAim = image.new(size = (320, 240))
    return imgRotationAim.draw_image(imageRotationBuffer.rotate(rotationAngle, adjust=1),0,0,alpha=1)

if ScreenOrientation:
    CAMERAROTATE = +180
else:
    CAMERAROTATE = +90



canvasImg = image.new(size = (240, 320))
while 1:
    canvasImg.clear()
    img = camera.capture().crop(0, 0,224, 224)
    if not img:
        time.sleep(0.02)
        continue
    faces = face_recognizer.get_faces(img)
    face_recognizer.darw_title(img , face_recognizer.get_input_size()[:2] , "rm" ,"add")

    if faces:
        # for prob, box, landmarks, feature, std_img in faces:
        for prob, box, landmarks, feature in faces:
            # [ prob, [x,y,w,h], [[x,y], [x,y], [x,y], [x,y], [x,y]], feature ]
            if key_C.is_pressed():
                if len(face_recognizer) < len(names):
                    while not (key_C.is_pressed() == False):
                        time.sleep(0.1)
                    idx = len(face_recognizer)
                    print("add user: {}, {}".format(idx, names[idx]))
                    face_recognizer.add_user(names[idx], feature)
                else:
                    print("user full")
            name, score = face_recognizer.recognize(feature)
            if name:
                if score > score_threshold:
                    face_recognizer.darw_info(img, box, landmarks, "{}:{:.2f}".format(name, score), font_color=(0, 0, 255, 255), bg_color=(0, 255, 0, 255))
                    print("user: {}, score: {:.2f}".format(name, score))
                else:
                    face_recognizer.darw_info(img, box, landmarks, "{}:{:.2f}".format(name, score), font_color=(255, 255, 255, 255), bg_color=(255, 0, 0, 255))
                    print("maybe user: {}, score: {:.2f}".format(name, score))
            else:
                face_recognizer.darw_info(img, box, landmarks, "", font_color=(255, 255, 255, 255), bg_color=(255, 255, 255, 255))

    if key_D.is_pressed():
        if len(face_recognizer) > 0:
            while not (key_D.is_pressed() == False):
                time.sleep(0.1)
            idx = len(face_recognizer) - 1
            print("remove user:", names[idx])
            face_recognizer.remove_user(names[idx])
        else:
            print("user empty")
    canvasImg.draw_image(img,48,8)
    canvasImg.draw_image((image.open("/root/preset/img/exit_ff0000_24x24.png")).rotate(0, adjust=0),288,216,alpha=1)
    display.show(canvasImg)