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giserh's Projects

megreader icon megreader

A research project for text detection and recognition using PyTorch 1.2.

meijster-distance icon meijster-distance

A canvas implementation of the Meijster algorithm to compute Euclidean, Manhattan, and Chessboard distances

meili-mobility-collector-android icon meili-mobility-collector-android

The MEILI Mobility Collector [Android version] gathers trajectories fused with accelerometer readings in a seamless and battery efficient way.

mercator.py icon mercator.py

Python utilities for Google Maps-style Mercator geometry

meshpy icon meshpy

2D/3D simplicial mesh generator interface for Python (Triangle, TetGen, gmsh)

metis icon metis

METIS - Serial Graph Partitioning and Fill-reducing Matrix Ordering

mgwr icon mgwr

Multiscale Geographically Weighted Regression (MGWR)

micropather icon micropather

MicroPather is a path finder and A* solver (astar or a-star) written in platform independent C++ that can be easily integrated into existing code. MicroPather focuses on being a path finding engine for video games but is a generic A* solver.

min-max-heap icon min-max-heap

Python implementation of the Min-Max Heap datastructure

minewechat icon minewechat

python小工具,微信聊天、自动回复、手机微信远程控制电脑

miniaudio icon miniaudio

Single file audio playback and capture library written in C.

miniweibo icon miniweibo

使用Python开发的基于新浪微博API的迷你微博网站

minorthird icon minorthird

MinorThird is a collection of Java classes for storing text, annotating text, and learning to extract entities and categorize text.

minpy icon minpy

NumPy interface with mixed backend execution

mips-simulator icon mips-simulator

A simulator that can run programs written in the MIPS assembly language

mistletoe icon mistletoe

A fast, extensible and spec-compliant Markdown parser in pure Python.

mistune icon mistune

The fastest markdown parser in pure Python with renderer feature, inspired by marked and misaka.

mixed_cell_cellullar_automata icon mixed_cell_cellullar_automata

The Mixed-Cell Cellullar Automata (MCCA) provides a new approach to enable more dynamic mixed landuse modeling to move away from the analysis of static patterns. One of the biggest advantages of mixed-cell CA models is the capability of simulating the quantitative and continuous changes of multiple landuse components inside cells.

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