Search Results for "neural network visualiser"

...Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to generate new views interactively. The representation is metric, meaning it supports camera movements with an absolute scale rather than only relative depth cues, which is useful for consistent viewpoint changes and downstream spatial tasks. ...

...Drop in a photo and the background disappears in one click, leaving a clean transparent PNG. Your images never leave your computer - there is no upload, no sign-up, no account, no watermark and no limits, ever. The app runs the open source u2net neural network locally on your CPU through onnxruntime, so it works on any modern Windows PC and does not need a GPU. Pick a single photo or drop a whole folder for batch processing. The cutout pipeline mirrors the default u2net path of the well-known rembg library, so the quality matches what you would get from popular online background removers - without giving up your photos, paying for full resolution, or watching ads. ...

...Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy.

Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch. The main novelty seems to be an extra layer of indirection with the prior network (whether it is an autoregressive transformer or a diffusion network), which predicts an image embedding based on the text embedding from CLIP. Specifically, this repository will only build out the diffusion prior network, as it is the best performing variant (but which incidentally involves a causal transformer as the denoising network) To train DALLE-2 is a 3 step process, with the training of CLIP being the most important. ...

TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information.

...It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. ...

A library written in C# for encoding and decoding animated Graphics Interchange Format (GIF) images. Based on NGif http://www.codeproject.com/KB/GDI-plus/NGif.aspx. Includes sample apps for encoding and decoding GIF files.

detect human presence Uses artificial neural network Complete netbeans project No need to train Just start to use it as u like!

...Finding patient disease started by taking Fourier transform (FFT) from input signal and extract a single cycle. Based on some heuristic algorithm the most important feature like P , Q , R , S , T captured and feed to trained neural network. and so the final decision made by CNN library. As mentioned before this software also capable do some image processing on scanned paper to lower the final costs.

Qt Handwriting Recognizing it's a simple Qt GUI interface of a artificial neural network to provide handwrite recognition. This project use FANN (Fast Artificial Neural Network) on first approach.

Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.

This project uses massively parallel Graphics Processing Units(GPU) for neural network(Backpropagation) purposes.

A handwritten number recognition system was developed by using image processing and neural network technique. The system was developed in Java. Other applications which make use of image processing and neural network technique will be published too.

A Neural network based, handwriting recognition software who's aim is to have a cursive OCR software. Although it is used in handwriting recognition, it can be used as well for creating Neural Networks and learning of those networks.

Neural network based pattern recognition software. Aim is to provide a program what is able to find pictures by a text line input. For example -> find all pictures with a red car?

openlpr is a open source project to implement license plate recognition in Win32 and Linux platform. It will provide the basic image processing to locate plate and character split and a neural network design to recognize character.