There might be better ways, but at least you can always make a planar mesh and color it: import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np # create a 21 x 21 vertex mesh xx, yy = np.meshgrid(np.linspace(0,1,21), np.linspace(0,1,21)) # create some dummy data (20 x 20) for the image data … Read more
Does plt.tricontourf(x,y,z) satisfy your requirements? It will plot filled contours for irregularly spaced data (non-rectilinear grid). You might also want to look into plt.tripcolor(). import numpy as np import matplotlib.pyplot as plt x = np.random.rand(100) y = np.random.rand(100) z = np.sin(x)+np.cos(y) f, ax = plt.subplots(1,2, sharex=True, sharey=True) ax[0].tripcolor(x,y,z) ax[1].tricontourf(x,y,z, 20) # choose 20 contour levels, … Read more
Because OpenCV stores images in BGR order instead of RGB. Try plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) See here for an example.
Google colab crashes if you try to display image using cv2.imshow() instead import from google.colab.patches import cv2_imshow and display using cv2_imshow(<image>)
Just specify vmin=0, vmax=1. By default, imshow normalizes the data to its min and max. You can control this with either the vmin and vmax arguments or with the norm argument (if you want a non-linear scaling). As a quick example: import matplotlib.pyplot as plt data = [[0, 0.25], [0.5, 0.75]] fig, ax = plt.subplots() … Read more
It seems you are using Juypter notebook. This always shows any autogenerated output (like the matplotlib figures) last in the output. You may use IPython.display.display to display the figures at the position of the output where they belong. import matplotlib.pyplot as plt import numpy as np from IPython.display import display images = [np.random.rayleigh((i+1)/8., size=(180, 200, … Read more
I will answer the general question of how to set a particular value to a particular color regardless of the color map. In the code below for illustration purposes I supposed that is the value -1 that you want to map white. You will be wanting to do something different for your code. This technique … Read more
You can set the height_ratios of the subplots using the gridspec_kw argument in the call to plt.subplots, and use the heights of the different images to set that ratio. From the docs to plt.subplots(): gridspec_kw : dict, optional Dict with keywords passed to the GridSpec constructor used to create the grid the subplots are placed … Read more
Since the limitation in this case is the call to plt.savefig() it cannot be optimized a lot. Internally the figure is rendered from scratch and that takes a while. Possibly reducing the number of vertices to be drawn might reduce the time a bit. The time to run your code on my machine (Win 8, … Read more
Interactive mode One way of updating a plot in matplotlib is to use interactive mode (plt.ion()). You should then not recreate new subplots for each frame you capture, but create your plot with images once and update it afterwards. import cv2 import matplotlib.pyplot as plt def grab_frame(cap): ret,frame = cap.read() return cv2.cvtColor(frame,cv2.COLOR_BGR2RGB) #Initiate the two … Read more