Hello coders!! In this article, we will be learning about matplotlib imread. We will learn about its syntax and then see some illustrated examples. Without wasting any time, let us get straight into the topic.
This method is used to read an image from a file into an array.
Syntax Matplotlib Imread:
- fname : image file
- format: image file format
Return Value of Matplotlib Imread:
This method returns the image data.
The image data. The returned array has shape
- Grayscale images: (M, N)
- RGB images: (M, N, 3)
- RGBA images: (M, N, 4)
Let us now look into some examples to grasp a clearer concept.
Example 1: Loading Image:
import numpy as np import matplotlib.cbook as cbook import matplotlib.image as image import matplotlib.pyplot as plt with cbook.get_sample_data('img.jpg') as image_file: image = plt.imread(image_file) fig, ax = plt.subplots() ax.imshow(image) ax.axis('off') plt.show()
cbook.get_sample_data() method is used to get the sample data file. Sample data files are stored in the ‘mpl-data/sample_data’ directory within the Matplotlib package. We then used the imread() method to return the image file. Lastly, using the imshow() method, we displayed the output.
Example 2: Watermark Image using matplotlib imread:
import numpy as np import matplotlib.cbook as cbook import matplotlib.image as image import matplotlib.pyplot as plt with cbook.get_sample_data('img.jpg') as file: im = image.imread(file) fig, ax = plt.subplots() ax.plot(np.sin(10 * np.linspace(0, 1)), '-o', ms = 15,alpha = 0.6, mfc ='green') fig.figimage(im, 5, 5, zorder = 3, alpha =.5) plt.show()
As you can see, in this example, we have used the same image as a background and plotted the sine function curve over it. We used the same steps as the previous example to load and display the image. We then plotted the sin method over it using the numpy sin method.
Example 3: Clipping Image With Patches:
import matplotlib.pyplot as plt import matplotlib.patches as patches import matplotlib.cbook as cbook with cbook.get_sample_data('img.jpg') as image_file: image = plt.imread(image_file) fig, ax = plt.subplots() im = ax.imshow(image) patch = patches.Circle((100, 100), radius=90, transform=ax.transData) im.set_clip_path(patch) ax.axis('off') plt.show()
In this example, we have clipped our image. Just like the previous examples, we used the cbook.get_sample_data() method to load our image. We then used patches.Circle() method to create a circle at the center (100,100) and radius 90. Using the set_clip_path() method is used to set the artist’s clip-path.
Example 4: Matplotlib imread grayscale:
import matplotlib.pyplot as plt import matplotlib.image as img image = img.imread('img.jpg') plt.imshow(image[:,:,1], cmap='gray') plt.show()
For this code, we have converted the image into grayscale. Like the previous examples, we use the imread() method to read the image file. We then slice the array and use cmap gray to convert our image to grayscale.
Example 5: Matplotlib imread RGB:
import matplotlib.pyplot as plt import matplotlib.image as img image = img.imread("img.jpg") plt.imshow(image) plt.show()
Here, we have loaded the image using matplotlib imread in RGB format. We then used the imshow() method to display the loaded image.
Specify the type of image in matplotlib imread:
As discussed earlier, the syntax of imread is as follows:
The format parameter specifies the image file format that will be assumed for reading the data. If not given, the format is deduced from the filename. If nothing can be deduced, PNG is tried.
Matplotlib imread vs cv2 imread:
|Matplotlib imread||CV2 imread|
|Reads color value as RGB||Reads color value as BGR|
|Lists pixel rows from the bottom to the top||Lists pixel rows from the top to bottom|
|Less efficient||More efficient|
With this, we come to an end with this article. I hope that the concept of matplotlib imread was clarified from this article. It is essentially useful when we want to implement an image into our graphical representation.
However, if you have any doubts or questions, do let me know in the comment section below. I will try to help you as soon as possible.