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arrow_augoor

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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AI-powered code knowledge

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

Auto-tagging
Enhance your code search experience with an AI-generated tag navigation to discover more in your codebases.
Python
Image
image-resizing
opencv
processing
Formal code documentation
Better understand code with automatic one-sentence snippet descriptions, extendable with i/o parameters.

Square crop the image.
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Parameters:
  im: (H, W) image to be cropped.
  S: the size of the crop.
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Returns:
  det_im: (H, W, 3) cropped image.
  scale: the scale of the crop.

Code explanation
Deep dive into codebases with automatically generated human-like descriptions and associated data.

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.
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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.
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Finally, we return the new image and the scale factor.

arrow_augoor

Knows your tools,
supports your languages

↳ Works with public and private repositories.
Github
↳ Languages we support:
Python
JavaScript
Java
C#
TypeScript
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Code comprehension

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.

↗  Documentation

A smart way to document code

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.
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↗  Exploration

Much more than a code search engine

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.
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We generate different layers of information, and offer code auto-tagging and intelligent queries suggestions, extending classical search capabilities.
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↗  Collaboration

Empowerment for emerging work practices 

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.
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 Smarten up your software development 
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Augoor makes the complex, simple.

Development work is all about collaboration with the right tools.

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