Flask API for handling bookmarks

REST API built using flask framework that used for managing bookmarks by individual users. This app is built using flask framework that helps this api can be cosumed both on andriod or web applications. API Endpoints POST user registration bookmarks posting GET user login refresh token bookmarks bookmark/{id} bookmark/stats bookmark/short_url PUT / PATCH bookmark/{id} DELETE bookmark/{id} Test Live API API have been configured and deployed using Heroku. Test Live version by clicking here. Documentation Every Aspect of using this API […]

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The NLP Cypher | 12.26.21

Merry Christmas 🎄 for those celebrating. And Happy New Year! Even OpenAI is feeling the holiday spirit: they open sourced their photorealistic GLIDE model several days ago. Includes three notebooks: The text2im notebook shows how to use GLIDE (filtered) with classifier-free guidance to produce images conditioned on text prompts. The inpaint notebook shows how to use GLIDE (filtered) to fill in a masked region of an image, conditioned on a text prompt. The clip_guided notebook shows how to use GLIDE […]

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Optimal Scraping Technique: CSS Selector, XPath, & RegEx

Web scraping deals with HTML almost exclusively. In nearly all cases, what is required is a small sample from a very large file (e.g. pricing information from an ecommerce page). Therefore, an essential part of scraping is searching through an HTML document and finding the correct information. How that should be done is the matter of some debate, preferences, experience, and types of data. While all scraping and parsing methods are “correct”, some of them have benefits that may be […]

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Detecting haze image with hazer

Detecting haze image with hazer. What is hazer Hazer is a lib for getting “haze degree”. This repository is python version of hazer:https://cran.r-project.org/web/packages/hazer/vignettes/detecting-hazy-images.htmlhttps://github.com/bnasr/hazer/ The method is from this paper: https://www.hilarispublisher.com/open-access/detecting-foggy-images-and-estimating-the-haze-degree-factor-jcsb.1000226.pdf How to use git clone https://github.com/Joey777210/hazer-py.git Run the example in hazer_example.py. GitHub View Github    

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LazyText: a library which helps build a lot of basic models without much code

LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic mpdels without much code. LazyText is for text what lazypredict is for numeric data. Free Software: MIT licence Installation To install LazyText pip install lazytext Usage To use lazytext import in your project as from lazytext.supervised import LazyTextPredict Text Classification Text classification on BBC News article classification.

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Downloader Middleware to support Playwright in Scrapy & Gerapy

This is a package for supporting Playwright in Scrapy, also thispackage is a module in Gerapy. Installation pip3 install gerapy-playwright Usage You can use PlaywrightRequest to specify a request which uses playwright to render. For example: yield PlaywrightRequest(detail_url, callback=self.parse_detail) And you also need to enable PlaywrightMiddleware in DOWNLOADER_MIDDLEWARES: DOWNLOADER_MIDDLEWARES = { ‘gerapy_playwright.downloadermiddlewares.PlaywrightMiddleware’: 543, } Congratulate, you’ve finished the all of the required configuration. If you run the Spider again, Playwright    

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A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization

A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization pip install madgrad Try it out! A best-of-both-worlds optimizer with the generalization performance of SGD and at least as fast convergence as that of Adam, often faster. A drop-in torch.optim implementation madgrad.MADGRAD is provided, as well as a FairSeq wrapped instance. For FairSeq, just import madgrad anywhere in your project files and use the –optimizer madgrad command line option, together with –weight-decay, –momentum, and optionally –madgrad_eps. The madgrad.py file containing […]

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ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement

Recently, the power of unconditional image synthesis has significantly advanced through the use of Generative Adversarial Networks (GANs). The task of inverting an image into its corresponding latent code of the trained GAN is of utmost importance as it allows for the manipulation of real images, leveraging the rich semantics learned by the network. Recognizing the limitations of current inversion approaches, in this work we present a novel inversion scheme that extends current encoder-based inversion methods by introducing an iterative […]

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