Python 获取错误识别器.train（x_train，np.array（y_labels））类型错误：src不是numpy数组，也不是标量数组

下面是我的代码。当我运行它时，我得到以下错误：

识别器序列（x_序列，np.数组（y_标签）） TypeError:src不是numpy数组，也不是标量

我尝试过使用

recognizer.train（x\u-train，y\u标签）

而不是

recognizer.train（x\u-train，np.array（y\u标签））

，但还是出现了一些错误

import cv2
import os
from PIL import Image, ImageEnhance
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('haarcascade_frontalface_default.xml') 

path = 'images'
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("png") or file.endswith("jpg"):

           path = os.path.join(root, file)
           label = os.path.basename(os.path.dirname(path)).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).convert("L")
           #contrast_enhancer = ImageEnhance.Contrast(pil_image)
           #pil_enhanced_image = contrast_enhancer.enhance(2)
           #enhanced_image = np.asarray(pil_enhanced_image)

           size = (550, 550)
           final_image = pil_image.resize(size, Image.ANTIALIAS)

           image_array = np.array(final_image)
           #print(image_array)
           faces = face_cascade.detectMultiScale(image_array , scaleFactor=1.3, 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)
#x_train = np.asarray(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")

---

你可以试试这个，它对我有用：

recognizer.train(x_train, y_labels)

或

---

可能重复感谢，但我尝试在asarray返回数组（a，dtype，copy=False，order=order）值501行中使用x_train=np.asarray（x_train）文件“/usr/lib/python2.7/dist packages/numpy/core/numeric.py”，错误：使用sequence设置数组元素

recognizer.update(x_train, y_labels)