Waad Mawlood's starred repositories
laravel-dynamic-observer
Call observer of the model from direct model by trait HasObserver without requiring in any provider, support multi observers
Laravel-Disposable-Email
Disposable email address validator for Laravel
nova-select-plus
A Laravel Nova Select Field
laravel-postgresql-enhanced
Support for many missing PostgreSQL specific features
laravel-auditing
Record the change log from models in Laravel
filament-curator
A media picker plugin for Filament Panels.
laravel-pivot
This package introduces new events for sync(), attach(), detach() or updateExistingPivot() methods on BelongsToMany relation.
laravel-searchable
Easily add weighted searches through model attributes and relationships
filament-rating
Add rating fields and columns to Filament forms and tables
filament-local-logins
This package allows you to log in locally using pre-set email addresses, making it easy to log into one or multiple development user accounts. It can be used in an admin panel or multiple panels.
dictionary
Dictionary for use with Thwords development
laravel-authz
An authorization library that supports access control models like ACL, RBAC, ABAC in Laravel.
clean-code-php
:bathtub: Clean Code concepts adapted for PHP
laravel-vouchers
Allow users to redeem vouchers that are bound to models.
Note_AppWith_Hive
NoteApp with Hive NoSql Database with CRUD Operation , Bloc/Cubit SM , Clean Architecture ,Caching Drak/Light Theme, Custom Widgets screensShots in README 👇❤
filament-tiptap-editor
A Rich Text Editor plugin for Filament Forms.
Brain-Tumor-Detection-from-MRI-images-Spring-2018
Earlier detection of brain tumors plays a vital role in its treatment as well as dynamically increase the survival rate of the patients. Magnetic Resonance Imaging (MRI) scans are widely used to diagnose the brain tumors which provides better accuracy than other medical imaging techniques. Still, the manual segmentation of MRI images and detecting the brain tumors is a time consuming and prone to error task, which is currently done by the medical experts or radiologists. So, there is an evident necessity for automatic brain tumor segmentation and extracting various characteristics of brain tumors. In this study, three widely used standard image segmentation methods (threshold based, k-means clustering and watershed segmentation) has been tested using collected brain MRI images to isolate the tumors from the rest of the brain regions, and their performance was compared based on the segmentation output. K-means clustering showed a better result than two other methods. Besides this, a graphical user interface (GUI) is designed based on primary image processing techniques and by using the solidity feature of brain tumors. Two of the highly useful brain tumor characteristics (area, and perimeter) are also measured here and displayed on the output window of GUI. The accuracy of this application for tumor detection on brain MRI images and features calculation is much high. More features can be extracted, and the accuracy can be maximized by following some other rigorous techniques, which later could be highly helpful for the medical practitioners working in this field.
Car-Speed-Detection
Estimate the speed of the car using OpenCV and Python
Speed-Detection-Using-OpenCV
The camera will capture all the cars/bike number plate. It will monitor cars speed limit. If the cars speed limit is greater it will store the image of the vehicle in the folder.
Speed_tracking
Multiple Cars Detection and Speed Tracking