How to resolve 'ValueError: Found array with dim 4. Estimator expected <= 2.'?

Question

我正在制作一个 SVM 分类器来对图像进行分类。本程序使用Google collab，文件上传到Google Drive。图片的形状是torch.Size([32, 3, 224, 224]).

这就是我拆分数据集的方式，

images = (images.numpy())
labels = (labels.numpy())
X_train, X_test, y_train, y_test = train_test_split(images, labels, test_size=0.3, random_state=42)

训练数据和测试数据拆分后，X_train和X_test的新形状为(22, 3, 224, 224)和(10, 3, 224, 224)。现在，当我尝试这样做时，出现了问题

# Create a classifier: a support vector classifier
classifier = svm.SVC(gamma=0.001)
#fit to the trainin data
classifier.fit(X_train,y_train)

----> 3 classifier.fit(X_train,y_train)

   537         if not allow_nd and array.ndim >= 3:
    538             raise ValueError("Found array with dim %d. %s expected <= 2."
--> 539                              % (array.ndim, estimator_name))
    540         if force_all_finite:
    541             _assert_all_finite(array,

ValueError: Found array with dim 4. Estimator expected <= 2.

我有 4 张图像类，我想要 SVM 分类器来训练模型，之前我是用 CNN 和迁移学习来训练的。我已经阅读了一些 post，在这里我可能不得不重塑它。你能帮我解决这个问题吗？感谢您的帮助。

Answer 1

目前，您的输入数据有 4 个维度 (batch size, channels, height, width) 您需要将图像展平为二维 (number of images, channels* height* width)

X_train = X_train.reshape(22,3*224*224)
X_test = X_test.reshape(10,3*224*224)

希望对您有所帮助！

How to resolve 'ValueError: Found array with dim 4. Estimator expected <= 2.'?

How to resolve 'ValueError: Found array with dim 4. Estimator expected <= 2.'?

image

machine-learning

svm

scikit-learn