Using plt.imshow() to display multiple images

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How do I use the matlib function plt.imshow(image) to display multiple images?

For example my code is as follows:

for file in images:

def process(filename):
    image = mpimg.imread(filename)
    <something gets done here>

My results show that only the last processed image is shown effectively overwriting the other images

You can set up a framework to show multiple images using the following:

import matplotlib.pyplot as plt
import matplotlib.image as mpimg

def process(filename: str=None) -> None:
    View multiple images stored in files, stacking vertically

        filename: str - path to filename containing image
    image = mpimg.imread(filename)
    # <something gets done here>

for file in images:

This will stack the images vertically

How to show multiple images in one figure?, np fig = plt.figure() a=fig.add_subplot(1,2,1) img = mpimg.imread('../_static/ stinkbug.png') lum_img = img[:,:,0] imgplot = plt.imshow(lum_img)� It’s time to show an image using a read dataset. To show an image, use plt.imshow() function. Syntax : plt.imshow( X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, shape=None, filternorm=1, filterrad=4.0, imlim=None, resample=None, url=None, *, data=None, **kwargs, ) plt.imshow(img) Output >>>

To display the multiple images use subplot()


#subplot(r,c) provide the no. of rows and columns
f, axarr = plt.subplots(4,1) 

# use the created array to output your multiple images. In this case I have stacked 4 images vertically

How to display multiple images in one figure correctly in Matplotlib , Use Matplotlib add_subplot() in for loop The simplest approach to display multiple images in a figure might be displaying every image using add_subplot() to initiate subplot and imshow() method to display an image inside a for loop. for ima in images: plt.figure() plt.imshow(ima) But to clarify the confusion with Image: IPython.display.Image is for displaying Image files, not array data. If you want to display numpy arrays with Image, you have to convert them to a file-format first (easiest with PIL):

In first instance, load the image from file into a numpy matrix

import numpy
import cv2
import os
def load_image(image: Union[str, numpy.ndarray]) -> numpy.ndarray:
    # Image provided ad string, loading from file ..
    if isinstance(image, str):
        # Checking if the file exist
        if not os.path.isfile(image):
            print("File {} does not exist!".format(imageA))
            return None
        # Reading image as numpy matrix in gray scale (image, color_param)
        return cv2.imread(image, 0)

    # Image alredy loaded
    elif isinstance(image, numpy.ndarray):
        return image

    # Format not recognized
        print("Unrecognized format: {}".format(type(image)))
        print("Unrecognized format: {}".format(image))
    return None

Then you can plot multiple image using the following method:

import matplotlib.pyplot as plt
def show_images(images: list) -> None:
    n: int = len(images)
    f = plt.figure()
    for i in range(n):
        # Debug, plot figure
        f.add_subplot(1, n, i + 1)

Plot multiple images with matplotlib in a single figure. Titles can be , """Display a list of images in a single figure with matplotlib. Parameters. ---------. images: List of if image.ndim == 2: plt.gray(). plt.imshow(image). a.set_title(title) . plt.imshow displays the image on the axes, but if you need to display multiple images you use show() to finish the figure. The next example shows two figures: The next example shows two figures: import numpy as np from keras.datasets import mnist (X_train,y_train),(X_test,y_test) = mnist.load_data() from matplotlib import pyplot as plt plt

Two images side-by-side using matplotlib (pylab) � GitHub, Two images side-by-side using matplotlib (pylab). f = plt.figure(). f. add_subplot(1,2, 1). plt.imshow(np.rot90(imgLr,2)) To display the multiple images use subplot () plt.figure() #subplot (r,c) provide the no. of rows and columns f, axarr = plt.subplots(4,1) # use the created array to output your multiple images.

Multi Image — Matplotlib 3.1.2 documentation, Make a set of images with a single colormap, norm, and colorbar. axs = plt. subplots(Nr, Nc) fig.suptitle('Multiple images') images = [] for i in range(Nr): for j in 20) * 1e-6 images.append(axs[i, j].imshow(data, cmap=cmap)) axs[i, j]. label_outer() # Find callbacksSM.connect('changed', update) Display Multiple Images in a Montage. You can view multiple images as a single image object in a figure window using the montage function. By default, montage scales the images, depending on the number of images and the size of your screen, and arranges them to form a square.

Image Demo — Matplotlib 3.1.2 documentation, The most common way to plot images in Matplotlib is with imshow() . The following examples demonstrate much of the functionality of imshow and the to layer multiple images of different sizes over one another with different� The image module also includes two useful methods which are imread which is used to read images and imshow which is used to display the image. Below are some examples which illustrate various operations on images using matplotlib library: Example 1: In this example, the program reads an image using the matplotlib.image.imread() and displays