We make code more accessible by helping people comprehend and automatically document codebases from multiple repositories, fast and simple. Developers, managers, teams, and companies benefit from Augoor.
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With innovation at our core, we bridge the gap between big cluttered codebases and the time and knowledge required to comprehend them.
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def square_crop(im, S):
if im.shape[0] > im.shape[1]:
height = S
width = int(float(im.shape[1]) / im.shape[0] * S)
scale = float(S) / im.shape[0]
else:
width = S
height = int(float(im.shape[0]) / im.shape[1] * S)
scale = float(S) / im.shape[1]
resized_im = cv2.resize(im, (width, height))
det_im = np.zeros((S, S, 3), dtype=np.uint8)
det_im[: resized_im.shape[0], : resized_im.shape[1], :] = resized_im
return det_im, scale
Square crop the image.
Parameters:
im: (H, W) image to be cropped.
S: the size of the crop.
Returns:
det_im: (H, W, 3) cropped image.
scale: the scale of the crop.
We first check if the image is wider than it is tall (if it's the other way around, we can just flip the image). If the image is wider than it is tall, we resize it to the given size.
We then create a new image with the same size as the original image, but with the same number of channels. We then copy the original image into the new image, and we set the new image to be the same type as the original image. We then resize the new image to the given size.
Finally, we return the new image and the scale factor.
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Crop an image to a square
If the number of rows is greater than the number of columns
Set the height to S
Calculate the width of the image
Calculate the scale of the image
else statement
Set the width of the window
Calculate the height of the image
Calculate the scale of the image
Resize an image to a new size
Create a 3D array of zeros
Resize the image to a smaller size
Returns the determinant and the scale of the matrix
We enable code understanding, documentation, and retrieval so devs can focus on the creative side of coding, while companies boost software development cycles and accelerate their go-to-market strategy.
Code needs documentation to become a sustainable project. It’s not news that keeping your code well documented and up-to-date is critical but also usually neglected. The good news is that now we can do it for you.
Our AI documents code automatically in a natural and comprehensive way, as a developer would, optimizing team productivity and keeping the code healthy.
Searching for code often feels like looking for needles in a haystack, and if you really want to understand it, those needles become breadcrumbs. So enabling developers to find, understand and interact with code in a more efficient way means better equipping them for their job.
We generate different layers of information, and offer code auto-tagging and intelligent queries suggestions, extending classical search capabilities.
Remote work is here to stay, hence the need for the right tool to embrace it. We boost software development teams with intelligence designed to foster a healthier collaborative culture and to build self-trust, by allowing them to easily share their knowledge and collectively take care of their code.
Turning individual efforts into group benefits is always a win-win.
Development work is all about collaboration with the right tools.
