Question

我创建了一个面部识别和识别程序。它根据我给它的训练文件夹来识别面孔。但是，它还会显示未知面孔的名称（不在训练文件夹中的面孔）。我应该进行哪些更改，以使未知面孔不会显示错误的名称？

这是面部训练代码：导入操作系统导入cv2 将numpy导入为np 从PIL导入图片进口泡菜

BASE_DIR = os.path.dirname(os.path.abspath(__file__ ))
image_dir = os.path.join(BASE_DIR, "images")

face_cascade = cv2.CascadeClassifier("D:\\Python\\Pycharm Projects\\face\\haarcascade_frontalface_default.xml")

recognizer = cv2.face.LBPHFaceRecognizer_create()


current_id = 0
label_ids ={}
x_train = []
y_labels = []
for root, dirs, files, in os.walk(image_dir):
    for file in files:
        if file.endswith("png") or file.endswith("jpg"):
            path = os.path.join(root, file)
            label = os.path.basename(os.path.dirname(path))
            print(label, path)
            if label in label_ids:
                pass
            else:
                label_ids[label] = current_id
                current_id +=1

            id_= label_ids[label]
            print(label_ids)
            pil_image = Image.open(path).convert("L")
            size = (550, 550)
            final_image = pil_image.resize(size, Image.ANTIALIAS)
            image_array = np.array(final_image, "uint8" )
            print(image_array)
            faces = face_cascade.detectMultiScale(image_array, scaleFactor=1.27, minNeighbors=5)

            for (x, y, w, h) in faces:
                roi = image_array[y:y+h, x:x+w]
                x_train.append(roi)
                y_labels.append(id_)


print(y_labels)
print(x_train)

with open("labels.pickle", 'wb') as f:
    pickle.dump(label_ids, f)

recognizer.train(x_train, np.array(y_labels))
recognizer.save("trainer.yml ")

这是面部识别代码：导入cv2 将numpy导入为np 进口泡菜

face_cascade = cv2.CascadeClassifier("D:\\Python\\Pycharm Projects\\face\\haarcascade_frontalface_default.xml")
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainer.yml")

labels = {"person_name": 1}
with open("labels.pickle", 'rb') as f:
   og_labels =  pickle.load(f)
   labels = {v:k for k, v in og_labels.items()}

cap = cv2.VideoCapture(0)

while True:
    rect, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.27, minNeighbors=5)
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
        roi_gray = gray[y:y + h, x:x + h]
        roi_color = frame[y:y + h, x:x + h]

        id_, conf = recognizer.predict(roi_gray)
        if conf>=10:
           # print(labels[id_])
            font = cv2.FONT_HERSHEY_SIMPLEX
            name = labels[id_]
            color = (255, 255, 255)
            stroke = 2
            cv2.putText(frame, name, (x, y), font, 1, color, stroke, cv2.LINE_AA)

        img_item = "myImage.png"
        cv2.imwrite(img_item, roi_gray)

    cv2.imshow("frame", frame)
    if cv2.waitKey(20) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

面部识别程序甚至在未知的面孔上也显示姓名

0 个答案: