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The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.
Selenium Grid is a server that allows tests to use web browser instances running on remote machines. With Selenium Grid, one server acts as the central hub. Tests contact the hub to obtain access to browser instances. The hub has a list of servers that provide access to browser instances (WebDriver nodes), and lets tests use these instances.
For example, attempting to read a pixel 3 units outside an edge reads one 3 units inside the edge instead. Crop / Avoid overlap Any pixel in the output image which would require values from beyond the edge is skipped. This method can result in the output image being slightly smaller, with the edges having been cropped.
This template creates a box with two to ten images arranged vertically or horizontally with captions for the entire box and each image. Template parameters [Edit template data] This template has custom formatting. Parameter Description Type Status Alignment align Sets text-wrapping around image box, where "none" places the box on the left edge with no text-wrapping, "center" places the box at ...
Test drivers are tailored to meet the unique requirements of different testing environments. With manual test drivers, testers can directly initiate actions, offering them direct control throughout the testing phase. In comparison, automated test drivers—typically in the form of tools or scripts—can carry out tests on their own.
Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [2] navigation of mobile robots, [3] or edge detection in images.
Two images stitched together. The photo on the right is distorted slightly so that it matches up with the one on the left. Image stitching or photo stitching is the process of combining multiple photographic images with overlapping fields of view to produce a segmented panorama or high-resolution image.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]