Python: ValueError: The number of classes has to be greater than one; got 1

Question

在Tonechas suggestion from 之后，计算一组图像的红色通道直方图然后将它们分类为正确类型的代码是这样的：

import cv2
import os
import glob
import numpy as np
from skimage import io


root = "C:/Users/joasa/data/train"
folders = ["Type_1", "Type_2", "Type_3"]
extension = "*.jpg"


# skip errors caused by corrupted files

def file_is_valid(filename):
    try:
        io.imread(filename)
        return True
    except:
        return False

def compute_red_histogram(root, folders, extension):
    X = []
    y = []
    for n, imtype in enumerate(folders):
        filenames = glob.glob(os.path.join(root, imtype, extension))
        for fn in filter(file_is_valid, filenames):
            print(fn)
            image = io.imread(fn)
            img = cv2.resize(image, None, fx=0.1, fy=0.1, interpolation=cv2.INTER_AREA)
            red = img[:, :, 0]
            h, _ = np.histogram(red, bins=np.arange(257), normed=True)
            X.append(h)
            y.append(n)
     return np.vstack(X), np.array(y)

X, y = compute_red_histogram(root, folders, extension)

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.5, random_state = 0)

from sklearn.svm import SVC
clf = SVC()
clf.fit(X_train, y_train)

y_test
clf.predict(X_test)
y_test == clf.predict(X_test)
score = clf.score(X_test, y_test)

prediction = pd.DataFrame(y_test, score, columns=['prediction', 'score']).to_csv('prediction.csv')

我收到这个错误：

ValueError: 类的个数必须大于一；得到 1

有人可以帮忙吗？谢谢

Answer 1

看看你的功能：

def compute_red_histogram(root, folders, extension):
    X = []
    y = []
    for n, imtype in enumerate(folders):
        filenames = glob.glob(os.path.join(root, imtype, extension))
        for fn in filter(file_is_valid, filenames):
            print(fn)
            image = io.imread(fn)
            img = cv2.resize(image, None, fx=0.1, fy=0.1, interpolation=cv2.INTER_AREA)
            red = img[:, :, 0]
            h, _ = np.histogram(red, bins=np.arange(257), normed=True)
            X.append(h)
            y.append(n)
        return np.vstack(X), np.array(y) ## <--- this line is not properly indented.

你 return 在 for 循环的第一次迭代结束时结束了 folders。你需要取消缩进这一行。

Answer 2

我也遇到了同样的问题我想通了有时，当您下载数据时，标签或目标是字符串尝试 y=y.astype(np.uint8)

Python: ValueError: The number of classes has to be greater than one; got 1

Python: ValueError: The number of classes has to be greater than one; got 1

python

classification

image-processing

svm

computer-vision