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我正在尝试使用 numpy 图像列表在 opencv 中训练 SVM，但我不断收到TypeError: samples is not a numpy array, neither a scalar最后一行代码的错误。该错误很可能来自我在samplePrep函数中设置数据的方式。这是我的代码。

import os
import glob
import pandas as pd
import xml.etree.ElementTree as ET
import numpy as np
import cv2

准备数据

class dataPrep:
    def import_from_XML(self, path):
        xml_list = []
        for xml_file in glob.glob(path + '/*.xml'):
            tree = ET.parse(xml_file)
            root = tree.getroot()
            for member in root.findall('object'):
                value = (root.find('filename').text,
                        int(root.find('size')[0].text),
                        int(root.find('size')[1].text),
                        member[0].text,
                        int(member[4][0].text),
                        int(member[4][1].text),
                        int(member[4][2].text),
                        int(member[4][3].text)
                        )
                xml_list.append(value)
        column_name = ['filename', 'width', 'height', 'class', 'xmin', 'ymin', 'xmax', 'ymax']
        xml_df = pd.DataFrame(xml_list, columns=column_name)
        return xml_df

    def samplePrep(self, xml_df, path, yscaling = 36, xscaling = 81):
        sample_list = []
        label_list = []
        with open(xml_df) as xml_df:
            i = 0
            for xml in xml_df:
                if i == 0:
                    i =+ 1
                    continue
                else:
                    xml = list(xml.split(','))
                    filename = xml[0]
                    width = int(xml[1])
                    height = int(xml[2])
                    if xml[3] == "Red_TL":
                        label = 1
                    elif xml[3] == "Orange_TL":
                        label = 2
                    elif xml[3] == "Green_TL":
                        label = 3
                    
                    label_list.append(np.array(label))
                    
                    xmin = int(xml[4])
                    ymin = int(xml[5])
                    xmax = int(xml[6])
                    ymax = int(xml[7])

                    image = cv2.imread(path + "/" +filename)
                    image = image[ymin:ymax, xmin:xmax]
                    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
                    gray_image = cv2.resize(gray_image, None,fx=xscaling/(xmax-xmin),fy=yscaling/(ymax-ymin), interpolation = cv2.INTER_NEAREST)
                    np_image = np.array(gray_image)
                    flat_image = np_image.ravel()
                    sample_list.append(flat_image)
                    i =+ 1
        return sample_list, label_list

支持向量机包装器

class Learn:
    def __init__(self):
        self.est = cv2.ml.SVM_create()
    
    def train(self, X, y, params = dict(kernel_type=cv2.ml.SVM_LINEAR, svm_type=cv2.ml.SVM_C_SVC) ):
        self.est.trainAuto(X, responses = y,layout = cv2.ml.ROW_SAMPLE, kFold = 3) #kfold=3 (default: 10)
        print("Model has been trained")
    
    def load(self, file):
        with file as f:
            self.est.load(f)
        print("SVM File Loaded")
        
    def save(self, file):
        with file as f:
            self.est.save(f)
        print("SVM File Saved")

    def predict(self, X):
        return self.est.predict_all(X).ravel()

训练支持向量机

path = "/"
xml_df = dataPrep().import_from_XML(path)
xml_df.to_csv('xml_test.csv',index=False)

sample_list, label_list = dataPrep().samplePrep(xml_df = 'xml_test.csv', path = path)
print(np.shape(sample_list))

Learn().train(sample_list, label_list)

错误

TypeError: samples is not a numpy array, neither a scalar

self.est.train(samples, responses, params = params)
TypeError: an integer is required (got type list)
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