获取错误识别器.train（x_train，np.array（y_标签））类型错误：cv2.error:OpenCV（4.5.1）

Question

我正在写一个面部识别程序，当我试着训练我的识别器时，我不断地遇到这个错误

识别器.train（x\u train，np.array（y\u标签））

cv2.error:OpenCV（4.5.1）C:\Users\appveyor\AppData\Local\Temp\1\pip-req-build-5rb\U 9df3\OpenCV\U contrib\modules\face\src\lbph\U faces.cpp:265:error:（-213：未实现函数/特征）使用原始本地二进制模式进行特征提取仅适用于单通道图像（给定16）。请将图像数据作为灰度图像传递！在函数“cv:：face:：elbp”中

我的代码是

import cv2
import os
from PIL import Image
import numpy as np 
import pickle

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

face_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()

current_id = 0
label_ids = {}
y_labels = []
x_train = []

for root, dirs, files in os.walk(image_dir):
    for file in files:
        if file.endswith("jpg"):
            path = os.path.join(root, file)
            label = os.path.basename(root).replace(" ", "-").lower()
            #print(label,path)
            if not label in label_ids: 
                label_ids[label] = current_id
                current_id += 1
            id_ = label_ids[label]
            #print(label_ids)
            #y_labels.append(label) 
            #x_train.append(path) 
            pil_image = Image.open(path) 
            image_array = np.array(pil_image, "uint8")
            #print(image_array)
            faces = face_cascade.detectMultiScale(image_array, scaleFactor=1.5, 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("trainner.yml") 

Answer 1

您可以使用cv2.cvtColor(whateverimageis, cv2.COLOR_BGR2GRAY)