Tool for segmentation in bioimaging
- napari
- bioimage-analysis
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Tool for segmentation in bioimaging
Flutter TF Segmentation is an example app that uses Flutter for the ios/android app and uses TensorFlow Lite for Image segmentation.
An interactive tool for segmenting yeast cells using deep learning.
Micropython driver for the max7219 with 8 x 7segment display
Unicode text segmentation for OCaml
A Python library which extracts strokes (outlines) from an SVG file as a series of line segments appropriate for driving pen plotters
Accurate segmentation of bacterial microscope images using deep learning synthetically generated image data.
A tokenizer based on the dictionary and Bigram language models for Go. (Now only support chinese segmentation)
Static analysis from configs → Kubernetes NetworkPolicies in seconds
#ZVQ - Zebrafish Vascular Quantification - https://doi.org/10.1242/dev.199720
Realtime Image Segmentation using TFLite and Flutter
QuimP is software for tracking cellular shape changes and dynamic distributions of fluorescent reporters at the cell membrane.
DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.
MicroPython driver for MY9221 10-segment LED bar graph modules
A micropython driver for 8-segment displays controlled by the TM74HC595 controller
Segment-segment intersection classifier and calculator for Elixir
Panoptic segmentation algorithms for 2D and 3D electron microscopy images
Micropython library for a 8 digits 7-segment display based on the MAX7219.
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gateway for segmentation data to Rstats & visualization with ggplot2 - in development
🗺 General purpose U-Network implemented in Keras for image segmentation
A lightweight MicroPython library for controlling single-digit 7-segment displays (ESP32, ESP8266, Raspberry Pi Pico W supported).
Micropython driver for the max7219 with 8 x 7segment display
Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.