从源代码显示不同的输出(机器学习)(Python)

根据您的文件夹 struct 和您提供的代码，问题是您没有在文件夹路径的末尾放置尾随斜杠. 在提供的代码中，您试图将文件夹名称直接与路径连接.但是，如果您遗漏了斜杠或文件夹变量不包含尾随斜杠，则可能导致路径不正确.

更新路径如下:

trainDataset = 'melanoma_cancer_dataset/train/'
testDataset = 'melanoma_cancer_dataset/test/'
predictionDataset = 'melanoma_cancer_dataset/skinTest/'

你的代码在这里做什么:

for folder in os.listdir(trainDataset):
    data = gb.glob(pathname=str(trainDataset + folder + '/*.jpg'))

它将转到trainDataset的路径，然后使用os.listdir()列出那里的文件夹(命名为恶性和良性). 这些路径被连接以生成最终的图像路径:

data = gb.glob(pathname=str(trainDataset + folder + '/*.jpg'))

此外，行中有轻微语法错误:

imageList = cv2.resize(image(120,120))

应当

cv2.resize(image, (120, 120))

此外，您添加到training_List的方式可能是错误的.在添加之前，您需要将imageList转换为列表，或者如果您想保留图像数组 struct ，则直接添加imageList.

完整更新代码:

# Data processing modules
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import cv2
# File directory modules
import glob as gb
import os
# Training and testing (machine learning) modules
import tensorflow as tf
import keras

# Directories
trainDataset = 'melanoma_cancer_dataset/train/'
testDataset = 'melanoma_cancer_dataset/test/'
predictionDataset = 'melanoma_cancer_dataset/skinTest/'

# Empty list for the images
training_List = []
testing_list = []

# Classification dictionary
diction = {'benign': 0, 'malignant': 1}

# Read through the folder's contents
for folder in os.listdir(trainDataset):
    # Corrected the path pattern and added a slash
    data = gb.glob(pathname=str(trainDataset + folder + '/*.jpg'))
    print(f'{len(data)} in folder {folder}')
    # Read the images, resize them, and store them in the list
    for file_path in data:
        image = cv2.imread(file_path)
        # Corrected the resize function call
        imageList = cv2.resize(image, (120, 120))
        # Append the image array directly
        training_List.append(imageList)

print(f'Total images in training set: {len(training_List)}')