opencv 转 matplotlib 坐标

最新推荐文章于 2023-11-17 12:31:58 发布

EmoC001

最新推荐文章于 2023-11-17 12:31:58 发布

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分类专栏： General Algorithm 文章标签： python opencv

本文链接：https://blog.youkuaiyun.com/u013302570/article/details/123715973

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这篇博客演示了如何将2D OpenCV图像处理技术与2D及3D的Matplotlib可视化相结合。首先，通过OpenCV创建2D圆点并保存为图像，然后使用Matplotlib将这些点转换为2D散点图。进一步，通过添加时间序列，将2D点升级到3D空间，并用Matplotlib绘制出3D轨迹。颜色编码表明了点的顺序：蓝->绿->红。

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2D opencv -> 2D matplotlib

width = 200
height = 200
points = [[100,120],[130,140],[150,180]]
mask = np.zeros((200,200))
cv2.circle(mask,tuple(points[0]),3,(255,255,0),-1)
cv2.circle(mask,tuple(points[1]),3,(255,255,0),-1)
cv2.circle(mask,tuple(points[2]),3,(255,255,0),-1)
cv2.imshow('',mask)
cv2.imwrite('2dopencv.jpg',mask)
cv2.waitKey(1)

xy = np.asarray(points)
x_pos = xy[:,0]
y_pos = xy[:,1]
xy = np.asarray([np.asarray(x_pos), height-np.asarray(y_pos)])
plt.scatter(xy[0], xy[1], s=15, c='orange')
plt.xlim([0, 200])
plt.ylim([0, 200])
plt.pause(1)
plt.savefig('2dmatplotlib.jpg')

请添加图片描述
在这里插入图片描述

2D opencv + 时序 -> 3D matplotlib

width = 200
height = 200
points = [[180,180],[120,120],[10,10]]

mask = np.zeros((200,200,3))
cv2.circle(mask,tuple(points[0]),3,(255,0,0),-1)
cv2.circle(mask,tuple(points[1]),3,(0,255,0),-1)
cv2.circle(mask,tuple(points[2]),3,(0,0,255),-1)
cv2.imshow('',mask)
cv2.imwrite('3dopencv.jpg',mask)
cv2.waitKey(1)

xy = np.asarray(points)
x_pos = xy[:,0]
y_pos = xy[:,1]
xy = np.asarray([np.asarray(x_pos), height-np.asarray(y_pos)])
z_pos = np.asarray(list(range(len(points)))) # 时间序列 t1 -> t3
fig = plt.figure(1)
ax = Axes3D(fig)
ax.plot3D(xy[0],  z_pos,  xy[1], 'grey', alpha=0.75)
ax.scatter(xy[0], z_pos,  xy[1], 'red', alpha=0.75)
ax.set_ylim([-1,4])
ax.set_xlim([0,200])
ax.set_zlim([0,200])
plt.savefig('3matplotlib.jpg')
plt.show()