Search Results for "find"

...It provides capabilities to quickly locate references, method calls, resource usages, and dependency paths across the project, which can dramatically speed up understanding code flow, tracing bugs, or auditing code. By giving a UI or structured navigation interface (depending on platform integration) over the project’s code and metadata, CodeLocator helps developers find where particular functions, classes or resources are used, and see their call graphs or dependency chains. This becomes particularly valuable in large-scale Android projects, legacy codebases, or when dealing with complicated modular architectures.

The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via...

...This library is still in it's infancy but the early results look promising. So true to the open source mantra of release early, release often, I'm releasing version 0.0.0 of smartcrop.js. Smartcrop.js implements an algorithm to find good crops for images. It can be used in the browser, in node or via a CLI. Smarcrop requires support for Promises, use a polyfill for unsupported browsers or set smartcrop.Promise to your favorite promise implementation (I recommend bluebird).

...We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.

...If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different categories in between, then the other points act as a barrier and the prototype will not find its optimum position during training. Since the model complexity is not known in many cases, we avoid this problem by introducing a "Dynamic" version of LVQ. Dynamic-GRLVQ (DGRLVQ), which adapts the model complexity to the given problem during training by adding or removing prototypes dynamically/realtime one by one for each category until satisfactory classification results are achieved.

...Engage into an epic story where Gods change the future and demons interfere with the present. Download and discover the beginning of an epic story. The Android version is now available! Find it here: http://market.android.com/details?id=toz.android See a promo video here: http://www.youtube.com/watch?v=Rh7GGlk5m30 Follow Sarquah on Twitter about the development: http://www.twitter.com/sarquah87