Acquiring images with OpenCV

Posted on Mon 16 April 2018 in OpenCV

To manipulate an image, the first thing you must do is open it. OpenCV lets you open images and videos from files and cameras, both locally attached and on the network. Let's check it out.

Still images

We'll start with the simple case of still images. This is probably best illustrated with some sample code:

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import cv2

# read an image from the current folder
image = cv2.imread('cat.jpg')

# or from another folder
image = cv2.imread('images/cat.jpg')

# then we'll just show it in an OpenCV window
cv2.imshow('Photo', image)

In the above example, the image variable is a binary object representing the RGB data of your file. Keep in mind that internally, OpenCV represents these "backwards" as BGR images. That will matter if you use a different library, such as matplotlib, in your script which expects RGB image data.

OpenCV supports the most common image file formats, including JPG, PNG, WebP, TIF, and more.

Errors and exception handling

The imread method does not raise a proper exception in the case the file doesn't exist. So, you can't wrap your code in a try/except block to handle errors. Instead, you'll need to check before calling imread with Python's usual file-handling functions, for example:

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from os import path

if path.isfile('cat.jpg'):
    image = cv2.imread('cat.jpg')
    ...

However, just because a file exists and can be opened by imread does not mean that you can successfully read image data from it. In such cases, the function will return None which you should test for:

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image = cv2.imread('not_an_image.txt')
if image is None:
print('Could not read image data')

Note: OpenCV determines the file type by its contents, not its extension. So, if you renamed cat.jpg to cat.txt, the imread() function would still be able to read it as a JPG file.

Video files and cameras

OpenCV lets you read video data from files and cameras. What's better, you use the same technique no matter the video source. First, you get a reference, or handle to the video source. Then, you read from that source frame by frame.

Strictly speaking, you use the cv2.VideoCapture.open() method to get a reference to your video source. However, OpenCV offers a shorter equivalent in the cv2.VideoCapture() method.

VideoCapture(source[, options])

Where source is one of:

  • an integer, representing which locally attached webcam to read from. A value of 0 represents your built-in webcam if available.
  • a string, representing a path to a local video file
  • a string, representing the URL to a streaming network camera, such as an IP camera

Typically, you don't need to provide any options for the method. These flags would be used to specify the format of the data stream and other specifics. As with still images, OpenCV can typically figure out the video parameters automatically by examining the input data.

Here is a very typical loop used to read frames from a video source. In this simple example, we just show each frame in an OpenCV window. Within each loop, the script checks for a key-press and if the letter "q" was typed, we break out of the loop, which in this example would release the video source and end the program:

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camera = cv2.VideoCapture(0)
while True:
    # loop continuously reading frame-by-frame
    success, frame = camera.read()
    if success:
        # a frame was successfully read
        # we'll just show it in a window
        cv2.imshow("Live Video", frame)

        # if the 'q' key is pressed, stop the loop
        if cv2.waitKey(1) & 0xFF == ord("q"):
            camera.release()
            break
    else:
        # frame wasn't read, handle that problem, for example
        camera.release()
        break

Errors and exceptions

As with reading still images, OpenCV does not offer proper exception handling when reading from a video source. If you specify a source that doesn't exist, you'll get an error like the following

out device of bound (0-0): 1 opencv: camera failed to properly initialize!

(To create the preceding error, I used camera = cv2.VideoCapture(1) and since my laptop has just one camera, camera 1 doesn't exist.)

It's important to release the video source properly when you're done by calling the release() method. Failing to do so can leave your camera unusable. Below is an example of the error you get attempting to use the built-in camera on a Mac that was not released properly before.

OpenCV: error in [AVCaptureDeviceInput initWithDevice:error:]
OpenCV: Cannot Use FaceTime HD Camera (Built-in)
OpenCV: camera failed to properly initialize!

If you end up in this state, you may have to restart your computer to recover. On the Mac, you can use the following command rather than restarting:

sudo killall VDCAssistant

Summary

There you have it, the ins-and-outs of aquiring image data to use with OpenCV.

opencv python