Search Results for "image segmentation algorithm" - Page 5
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Showing 228 open source projects for "image segmentation algorithm"
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Computer Vision Pretrained Models
A collection of computer vision pre-trained models
...Instead of building a model from scratch to solve a similar problem, we can use the model trained on other problem as a starting point. A pre-trained model may not be 100% accurate in your application. For example, if you want to build a self-learning car. You can spend years building a decent image recognition algorithm from scratch or you can take the inception model (a pre-trained model) from Google which was built on ImageNet data to identify images in those pictures. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone. ... -
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Frontend Regression Validator (FRED)
Visual regression tool used to compare baseline and updated instances
...The visual analysis computes the Normalized Mean Squared error and the Structural Similarity Index on the screenshots of the baseline and updated sites, while the visual AI looks at layout and content changes independently by applying image segmentation Machine Learning techniques to recognize high-level text and image visual structures. This reduces the impact of dynamic content yielding false positives. FRED is designed to be scalable. It has an internal queue and can process websites in parallel depending on the amount of RAM and CPUs (or GPUs) available. -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own learnable weights and biases. ... -
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DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups. -
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SwiftOCR
Fast and simple OCR library written in Swift
SwiftOCR is a fast and simple OCR library written in Swift. It uses a neural network for image recognition. As of now, SwiftOCR is optimized for recognizing short, one-line long alphanumeric codes (e.g. DI4C9CM). We currently support iOS and OS X. If you want to recognize normal text like a poem or a news article, go with Tesseract, but if you want to recognize short, alphanumeric codes (e.g. gift cards), I would advise you to choose SwiftOCR because that's where it exceeds. Tesseract is... -
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DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based... -
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COCO Annotator
Web-based image segmentation tool for object detection & localization
COCO Annotator is a web-based image annotation tool designed for versatility and efficiently label images to create training data for image localization and object detection. It provides many distinct features including the ability to label an image segment (or part of a segment), track object instances, label objects with disconnected visible parts, and efficiently store and export annotations in the well-known COCO format. The annotation process is delivered through an intuitive and... -
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Primitive Pictures
Reproducing images with geometric primitives
Primitive Pictures is an image processing command-line tool written in Go that reproduces images using geometric primitives (triangles, rectangles, ellipses, polygons, etc.). The core algorithm is iterative and “hill-climbing”: given a target image, it repeatedly finds the best single shape to add that will reduce the error between the current approximation and the target image, then draws that shape. -
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imgaug
Image augmentation for machine learning experiments
...Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions, hue/saturation changes, cropping/padding, blurring, etc. Rotate image and segmentation map on it by the same value sampled. Convert keypoints to distance maps, extract pixels within bounding boxes from images, clip polygon to the image plane, etc. Scale segmentation maps, average/max pool of images/maps, pad images to aspect ratios (e.g. to square them). Draw heatmaps, segmentation maps, keypoints, bounding boxes, etc. -
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Anime4kSharp
Anime4K implemented in C#
...Each phase takes a input image and renders it to a output image. This makes it easy to port the algorithm (back) to GLSL fragment shaders. As bloc97 described in his pseudo-preprint, the Anime4K algorithm is actually quite simple. -
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the... -
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NiftyNet
An open-source convolutional neural networks platform for research
...Adapt existing networks to your imaging data. Quickly build new solutions to your own image analysis problems. NiftyNet currently supports medical image segmentation and generative adversarial networks. NiftyNet is not intended for clinical use. -
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Zopfli
Zopfli Compression Algorithm is a compression library
Zopfli is a compression library and command-line tool that produces exceptionally small DEFLATE, zlib, and gzip streams by spending more CPU time to search for better encodings. It keeps strict compatibility with the ubiquitous DEFLATE format, so outputs can be decompressed by any standard tool or browser. The encoder performs exhaustive block splitting and greedy but thorough match searching to shave extra bytes off assets, which is ideal for web content and firmware where size matters more... -
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DSeg software
A MATLAB program to segment filamentous bacteria and hyphae structures
...A fast binary level-set based algorithm is implemented for extracting object contour and refining shapes. The software is implemented in MATLAB for segmenting and tracking of cell contours from various microscopy systems. Video instructions: https://www.youtube.com/embed/qMbM0shkk7A?rel Lastest updates: 20190930 DSeg: A dynamic segmentation program to extract backbone patterns for filamentous bacteria and hyphae structures,(2018). -
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Batch PIE
A batch pipelined image editor
Current filter functionality: - Simple editing options: Image cropping, resizing, rotation, Color brightness curve alignment - Histobram processing: Convolution, statistics (e. g. f_max or median analysis) - Image segmentation: The actual segmentation process as well as group weight calculation for further filtering (both functions rely on self defined custom dynamic mathematical functions) - Dynamic mathematical functions for custom and automated image filtering: General mathematical operations, using image or matrix as f(x, y), export f(x, y) as image or matrix, mapping variables on other ones and of course boolean operation for case sensitivity - A flexible variables model of dynamic mathematical function that sets no restriction on particular variables count - Sub project support for an organized total process targeting to save time using previously created editing routines instead of redoing steps each time -
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Deep Learning for Medical Applications
Deep Learning Papers on Medical Image Analysis
Deep-Learning-for-Medical-Applications is a repository that compiles deep learning methods, code implementations, and examples applied to medical imaging and healthcare data. The project addresses domain-specific challenges like segmentation, classification, detection, and multimodal data (e.g. MRI, CT, X-ray) using state-of-the-art architectures (e.g. U-Net, ResNet, GAN variants) tailored to medical constraints (small datasets, annotation costs, class imbalance). It includes Jupyter... -
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easy12306
Automatic recognition of 12306 verification code
Automatic recognition of 12306 verification code using machine learning algorithm. Identify never-before-seen pictures. -
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pyfolio
Portfolio and risk analytics in Python
...It works well with the Zipline open source backtesting library. At the core of pyfolio is a so-called tear sheet that consists of various individual plots that provide a comprehensive image of the performance of a trading algorithm. Here's an example of a simple tear sheet analyzing a strategy. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. -
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DeepMask
Torch implementation of DeepMask and SharpMask
DeepMask is an early, influential approach to class-agnostic object segmentation that learns to propose pixel-accurate masks directly from images. Instead of first generating boxes and then refining them, the network predicts a foreground mask and an “objectness” score for a given image patch, yielding high-quality segment proposals suitable for downstream detection or instance segmentation. The model is trained end-to-end to align mask shape with object extent, which markedly improves recall at a manageable number of proposals. ... -
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cocolib / light field suite
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: documentation on the SourceForge page is outdated and not updated anymore, please visit http://cocolib.net *** -
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Dynamic Routing Between Capsules
A PyTorch implementation of the NIPS 2017 paper
Dynamic Routing Between Capsules is a PyTorch implementation of the Capsule Network architecture originally proposed to address limitations in traditional convolutional neural networks. Capsule networks aim to improve how neural models represent spatial hierarchies and relationships between objects within images. Instead of scalar neuron activations, capsules output vectors that encode both the presence of features and their spatial properties such as orientation or pose. The repository... -
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Source code for the article: 'The Influence of Object Shape on the Convergence of Active Contour Models for Image Segmentation'. Images and .mat files are included to both run active contour models and create phase diagrams showing how object shape and choice of parameters affect the convergence of the models.
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mzitu
Python crawler that downloads image galleries and analyzes titles
mzitu is a Python-based web crawling project designed to automatically download and organize image galleries from a specific photography site. It demonstrates how to build a scraper that navigates gallery pages, retrieves image links, and saves the images locally in a structured directory layout. It focuses on automating the collection of large sets of images by programmatically parsing page content and iterating through gallery entries. mzitu also includes a simple analysis script that processes downloaded folder names to generate statistics and visualizations. ... -
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Packery
Gapless, draggable grid layouts
Packery is a JavaScript library and jQuery plugin that makes gapless and draggable layouts. It uses a bin-packing algorithm to fill in empty gaps. Packery layouts can be intelligently ordered or organically wild. Elements can be stamped in place, fit in a specific spot, or dragged around. It’s perfect for draggable dashboard and seamless Masonry image galleries. If you want to use Packery to develop commercial sites, themes, projects, and applications, the Commercial license is the appropriate license. ... -
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DIGITS
Deep Learning GPU training system
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. ...
