opencv - 打开CV错误-MAC上的人脸识别

Question

我有一个面部检测训练代码。它给了我一些问题，我不知道为什么。
我正在使用MAC，似乎缺少了某些东西。你能告诉我该怎么办吗？

先感谢您

OpenCV(3.4.1) Error: Assertion failed (!empty()) in detectMultiScale, file /tmp/opencv-20180426-73279-16a912g/opencv-3.4.1/modules/objdetect/src/cascadedetect.cpp, line 1698
Traceback (most recent call last):
  File "/Users/Desktop/OpenCV-Python-Series-master/src/faces-train.py", line 36, in <module>
    faces = face_cascade.detectMultiScale(image_array, scaleFactor=1.5, minNeighbors=5)
cv2.error: OpenCV(3.4.1) /tmp/opencv-20180426-73279-16a912g/opencv-3.4.1/modules/objdetect/src/cascadedetect.cpp:1698: error: (-215) !empty() in function detectMultiScale

[在0.421秒内完成]

我的代码在下面。

import cv2
import os
import numpy as np
from PIL import Image
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("png") or 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) # some number
            #x_train.append(path) # verify this image, turn into a NUMPY arrray, GRAY
            pil_image = Image.open(path).convert("L") # grayscale
            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=1.5, 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("pickles/face-labels.pickle", 'wb') as f:
    pickle.dump(label_ids, f)

recognizer.train(x_train, np.array(y_labels))
recognizer.save("recognizers/face-trainner.yml")

Answer 1

断言失败表示您的级联未正确加载。您可以通过在构造函数之后调用face_cascade.empty()来验证它。请确保您提供的路径('cascades/data/haarcascade_frontalface_alt2.xml')是正确的。当它指向不存在的文件时，构造函数不会抛出任何异常，因此您可以轻松地将其丢失而无需显式调用empty()。