im试图弄清楚如何使用SVM对我自己的数据集中的图像进行图像分类,im通过他的链接使用笔记本:https://github.com/whimian/SVM-Image-Classification。问题是,对于其他任何我使用skimage的项目,它都可以正常工作,但是对于这个项目,我在上面一行的标题中得到了上述错误:
img = skimage.io.imread(file)
我已经使用命令pip卸载scikit-image并安装,但仍然无法正常工作。
而且,以下错误发生在下行中,我不确定它们是否与此问题有关:
image_dataset.data, image_dataset.target, test_size=0.3,random_state=109
NameError: name 'image_dataset' is not defined
clf.fit(X_train, y_train)
NameError: name 'X_train' is not defined
并且为了可视化,这是该错误所属的代码片段:
image_dir = Path(container_path)
folders = [directory for directory in image_dir.iterdir() if directory.is_dir()]
categories = [fo.name for fo in folders]
descr = "A image classification dataset"
images = []
flat_data = []
target = []
for i, direc in enumerate(folders):
for file in direc.iterdir():
img = skimage.io.imread(file)
img_resized = resize(img, dimension, anti_aliasing=True, mode='reflect')
flat_data.append(img_resized.flatten())
images.append(img_resized)
target.append(i)
flat_data = np.array(flat_data)
target = np.array(target)
images = np.array(images)
return Bunch(data=flat_data,
target=target,
target_names=categories,
images=images,
DESCR=descr)
至于进口:
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
%matplotlib notebook
from sklearn import svm, metrics, datasets
from sklearn.utils import Bunch
from sklearn.model_selection import GridSearchCV, train_test_split
from skimage.io import imread
from skimage.transform import resize
img = skimage.io.imread(file)
将此行更改为
img = imread(file)