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.
We'll start with the simple case of still images. This is probably best illustrated with some sample code:
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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
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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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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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
Where source is one of:
- an integer, representing which locally attached webcam to read from. A value of
0represents 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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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
There you have it, the ins-and-outs of aquiring image data to use with OpenCV.