写一个单张深度图可视化代码
时间: 2023-03-12 08:04:40 浏览: 80
可以参考下面的代码:import matplotlib.pyplot as plt
from sklearn.datasets import make_classificationX, y = make_classification(n_samples=500, n_features=2, n_informative=2, n_redundant=0, n_repeated=0, n_classes=2, n_clusters_per_class=1, class_sep=0.5, random_state=0)plt.figure(figsize=(6, 6))
plt.scatter(X[:, 0], X[:, 1], marker='o', c=y, s=25, edgecolor='k')plt.show()
相关问题
写一个单张深度图可视化代码python
代码如下:import matplotlib.pyplot as plt
import numpy as np
from sklearn.datasets import load_iris data = load_iris()
features = data.data
feature_names = data.feature_names
target = data.target
target_names = data.target_names for t in range(3):
if t == 0:
c = 'r'
marker = '>'
elif t == 1:
c = 'g'
marker = 'o'
elif t == 2:
c = 'b'
marker = 'x'
plt.scatter(features[target == t,0],
features[target == t,1],
marker=marker,
c=c)plt.legend(target_names, loc = 'lower right')
plt.xlabel(feature_names[0])
plt.ylabel(feature_names[1])
plt.show()
写一个单张深度图可视化代码opencv
答案:import cv2
img = cv2.imread('image.jpg',0)
cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyAllWindows()