我试图在我的互动情节中间添加注释 我希望看到生成 test 列表的循环的 i 值 我的所有数据。对于每个imshow情节,我想看到我的 i 值, 我添加了一个ax.annotate,但它不起作用。
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig = plt.figure() # make figure
ax = fig.add_subplot(111)
test = []
mask2 = np.random.randint(255, size=(20, 20))
for i in range(1,5,3):
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(i,i))
res = (cv2.morphologyEx(mask2.astype(uint8),cv2.MORPH_OPEN,kernel))
#plt.imshow(res,cmap=plt.cm.gray,alpha=1);plt.show()
test.append(res)
# make axesimage object
# the vmin and vmax here are very important to get the color map correct
im = ax.imshow(test[0], cmap=plt.get_cmap('hot'), vmin=0, vmax=255)
im2 = ax.annotate('This is awesome!',
xy=(76, -10.75),
xycoords='data',
textcoords='offset points',
arrowprops=dict(arrowstyle="->"))
plt.show()
# function to update figure
def updatefig(j):
# set the data in the axesimage object
im.set_array(test[j])
# return the artists set
return im,
# kick off the animation
ani = animation.FuncAnimation(fig, updatefig, frames=range(20),
interval=50, blit=True)
plt.show()
答案 0 :(得分:1)
我找到了出路。我在更新函数中添加了一个“set_text”,然后返回图片和文本:
test = []
test2 = []
for i in range(3,27,3):
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(i,i))
res = (cv2.morphologyEx(mask2,cv2.MORPH_OPEN,kernel))
#plt.imshow(res,cmap=plt.cm.gray,alpha=1);plt.show()
test.append(res)
test2.append(i)
fig = plt.figure() # make figure
ax = fig.add_subplot(111)
# make axesimage object
# the vmin and vmax here are very important to get the color map correct
im = ax.imshow(test[0], cmap=plt.get_cmap('hot'), vmin=0, vmax=255)
time_template = 'Diffusion - Kernel size : %2.2d' # prints running simulation time
txt = ax.text(500, 80, '', fontsize=15,color='red')
#plt.show()
# function to update figure
def updatefig(j):
# set the data in the axesimage object
im.set_array(test[j])
txt.set_text(time_template%(float(np.asarray(test2[j]))))
return im,txt
ani = animation.FuncAnimation(fig, updatefig, frames=range(len(test)),
interval=100, blit=False,repeat=True)
plt.show()