ibrahim-r Goto Github PK

documentation

Official documentation for the Raspberry Pi

dragon-book-exercise-answers

Compilers Principles, Techniques, & Tools (purple dragon book) second edition exercise answers. 编译原理（紫龙书）第2版习题答案。

droid2ino

Android Library for connecting an Android device with an Arduino board via a Bluetooth connection

esp12relayboard

fingertracker

Processing library that performs real-time finger tracking from depth images.

free-programming-books

:books: Freely available programming books

gmaps

Google maps for Jupyter notebooks

gnusim8085

A graphical simulator, assembler and debugger for the Intel 8085 microprocessor

google-maps-services-python

Python client library for Google Maps API Web Services

gsm-gps-book

Code for the GSM & GPS Arduino Projects book

image-processing

introtospartanfpgabook

A book on using the Spartan 3E FPGA with VHDL, using the Papilio One or Digilent Basys2 boards

joule-code-samples

language-c

C support in Atom

learn-opencv-with-python-and-c-

opencv -python - c/c++

learnopencv

Learn OpenCV : C++ and Python Examples

make-avr-programming-book-code

make-fpga

Repository of Verilog code for Make:FPGA book Chapters 2 & 3.

mastering-qt-book-code

mcptam

MCPTAM is a set of ROS nodes for running Real-time 3D Visual Simultaneous Localization and Mapping (SLAM) using Multi-Camera Clusters. It includes tools for calibrating both the intrinsic and extrinsic parameters of the individual cameras within the rigid camera rig.

micropython

MicroPython - a lean and efficient Python implementation for microcontrollers and constrained systems

models

Models built with TensorFlow

mono-vo

An OpenCV based implementation of Monocular Visual Odometry

motion

Motion, a software motion detector.

nextion

A simple Nextion HMI library for Arduino

object-color-tracking-with-opencv-and-python

object tracking with opencv and python

object-detection-with-deep-learning-and-sliding-window

Introduces an approach for object detection in an image with sliding window. The repository contains three files, make_data.py reads the image in gray scale and converts the image into a numpy array. The labels are also appended based on the file name. In this case, if the file name starts with "trn", then 1 is appended else 0. Finally, all the images and labels are saved into .npy file. The test-model-1.py file loads the images and converts the labels into two categories as we are doing binary classification of images. The model is built using keras with theano as backend. In this case, the best training accuracy was 80% since the data was just 500 images and the testing accuracy was 67%

object-tracker

Object Tracker written in Python using dlib and OpenCV

objecttracking

OpenCV and Python based tutorial on object tracking

odin

Open Directions and Improved Narrative - a directions engine for annotating a path through the graph for use in navigation