获取错误识别器.train(x_train，np.array(y_labels))TypeError:src不是nump

Question

下面是我的代码。当我运行它时，我得到了这个错误：

识别器.train(x_train，np.array(y_labels((TypeError:src不是numpy数组，也不是标量

我尝试使用recognizer.train(x_train, y_labels)而不是recognizer.train(x_train, np.array(y_labels))，但仍然会出现一些错误？

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")

Answer 1

你可以试试这个，它对我有用：

recognizer.train(x_train, y_labels)

或

recognizer.update(x_train, y_labels)