teleren/devto huggingface dataset:
A beginner's guide to the Image-Tagger model by Pengdaqian2020 on Replicate
Tags: coding, ai, beginners, programming
Published: 2024-05-01 15:39:05

*This is a simplified guide to an AI model called [Image-Tagger](https://aimodels.fyi/models/replicate/image-tagger-pengdaqian2020) maintained by [Pengdaqian2020](https://aimodels.fyi/creators/replicate/pengdaqian2020). If you like these kinds of guides, you should subscribe to the [AImodels.fyi newsletter](https://aimodels.substack.com) or follow me on [Twitter](https://twitter.com/mikeyoung44).*

## Model overview

The `image-tagger` model is a AI-powered image tagging tool developed by [pengdaqian2020](https://aimodels.fyi/creators/replicate/pengdaqian2020). This model can be used to automatically generate relevant tags for a given image. It is similar to other image processing models like [gfpgan](https://aimodels.fyi/models/replicate/gfpgan-tencentarc), which focuses on face restoration, and [codeformer](https://aimodels.fyi/models/replicate/codeformer-sczhou), another robust face restoration algorithm.

## Model inputs and outputs

The `image-tagger` model takes an image as input and generates a list of tags as output. The model allows users to set thresholds for the "general" and "character" scores to control the sensitivity of the tagging.

### Inputs
- **Image**: The input image to be tagged
- **Score General Threshold**: The minimum score threshold for general tags
- **Score Character Threshold**: The minimum score threshold for character tags

### Outputs
- An array of tags generated for the input image

## Capabilities

The `image-tagger` model can automatically generate relevant tags for a given image. This can be useful for organizing and categorizing large image libraries, as well as for adding metadata to images for improved search and discovery.

## What can I use it for?

The `image-tagger` model can be used in a variety of applications, such as:
- Automating the tagging and categorization of images in an online store or media library
- Generating relevant tags for social media images to improve engagement and discoverability
- Enhancing image search and recommendation engines by providing accurate and comprehensive tags

## Things to try

One interesting aspect of the `image-tagger` model is the ability to fine-tune the sensitivity of the tagging by adjusting the "general" and "character" score thresholds. By experimenting with different threshold values, users can optimize the model's output to best fit their specific needs and use cases.

**If you enjoyed this guide, consider subscribing to the [AImodels.fyi newsletter](https://aimodels.substack.com) or following me on [Twitter](https://twitter.com/mikeyoung44) for more AI and machine learning content.**
A beginner's guide to the Gfpgan model by Tencentarc on Replicate
Tags: coding, ai, beginners, programming
Published: 2024-05-01 15:37:20

*This is a simplified guide to an AI model called [Gfpgan](https://aimodels.fyi/models/replicate/gfpgan-tencentarc) maintained by [Tencentarc](https://aimodels.fyi/creators/replicate/tencentarc). If you like these kinds of guides, you should subscribe to the [AImodels.fyi newsletter](https://aimodels.substack.com) or follow me on [Twitter](https://twitter.com/mikeyoung44).*

## Model overview

`gfpgan` is a practical face restoration algorithm developed by the Tencent ARC team. It leverages the rich and diverse priors encapsulated in a pre-trained face GAN (such as StyleGAN2) to perform blind face restoration on old photos or AI-generated faces. This approach contrasts with similar models like [Real-ESRGAN](https://aimodels.fyi/models/replicate/real-esrgan-nightmareai), which focuses on general image restoration, or [PyTorch-AnimeGAN](https://aimodels.fyi/models/replicate/pytorch-animegan-ptran1203), which specializes in anime-style photo animation.

## Model inputs and outputs

`gfpgan` takes an input image and rescales it by a specified factor, typically 2x. The model can handle a variety of face images, from low-quality old photos to high-quality AI-generated faces.

### Inputs
- **Img**: The input image to be restored
- **Scale**: The factor by which to rescale the output image (default is 2)
- **Version**: The `gfpgan` model version to use (v1.3 for better quality, v1.4 for more details and better identity)

### Outputs
- **Output**: The restored face image

## Capabilities

`gfpgan` can effectively restore a wide range of face images, from old, low-quality photos to high-quality AI-generated faces. It is able to recover fine details, fix blemishes, and enhance the overall appearance of the face while preserving the original identity.

## What can I use it for?

You can use `gfpgan` to restore old family photos, enhance AI-generated portraits, or breathe new life into low-quality images of faces. The model's capabilities make it a valuable tool for photographers, digital artists, and anyone looking to improve the quality of their facial images. Additionally, the maintainer [tencentarc](https://aimodels.fyi/creators/replicate/tencentarc) offers an online demo on Replicate, allowing you to try the model without setting up the local environment.

## Things to try

Experiment with different input images, varying the scale and version parameters, to see how `gfpgan` can transform low-quality or damaged face images into high-quality, detailed portraits. You can also try combining `gfpgan` with other models like [Real-ESRGAN](https://aimodels.fyi/models/replicate/real-esrgan-nightmareai) to enhance the background and non-facial regions of the image.

**If you enjoyed this guide, consider subscribing to the [AImodels.fyi newsletter](https://aimodels.substack.com) or following me on [Twitter](https://twitter.com/mikeyoung44) for more AI and machine learning content.**
A beginner's guide to the Text-Extract-Ocr model by Abiruyt on Replicate
Tags: coding, ai, beginners, programming
Published: 2024-05-01 15:35:46

*This is a simplified guide to an AI model called [Text-Extract-Ocr](https://aimodels.fyi/models/replicate/text-extract-ocr-abiruyt) maintained by [Abiruyt](https://aimodels.fyi/creators/replicate/abiruyt). If you like these kinds of guides, you should subscribe to the [AImodels.fyi newsletter](https://aimodels.substack.com) or follow me on [Twitter](https://twitter.com/mikeyoung44).*

## Model overview

`text-extract-ocr` is a simple OCR (Optical Character Recognition) model created by [abiruyt](https://aimodels.fyi/creators/replicate/abiruyt) that can easily extract text from an image. It is similar to other OCR models like [ocr-surya](https://aimodels.fyi/models/replicate/ocr-surya-cudanexus) and can be useful for a variety of text extraction tasks. Unlike more complex multimodal models like [bunny-phi-2-siglip](https://aimodels.fyi/models/replicate/bunny-phi-2-siglip-adirik), this model focuses solely on the task of extracting text from images.

## Model inputs and outputs

`text-extract-ocr` takes an image as input and outputs the extracted text. The input schema specifies that the model expects a single `image` parameter in the form of a URI (Uniform Resource Identifier).

### Inputs
- **image**: The image to process and extract text from.

### Outputs
- **Output**: The extracted text from the input image.

## Capabilities

`text-extract-ocr` is capable of accurately extracting text from a wide variety of image types, including scanned documents, screenshots, and photographs. It can handle multiple languages and different font styles and sizes.

## What can I use it for?

You can use `text-extract-ocr` for tasks like digitizing physical documents, automating data entry from forms, or extracting relevant information from images. It could be particularly useful for businesses or organizations that need to process large volumes of documents or images containing text. The model could also be integrated into broader computer vision pipelines or combined with other models like [stylemc](https://aimodels.fyi/models/replicate/stylemc-adirik) for more advanced image processing workflows.

## Things to try

Some ideas for trying out `text-extract-ocr` include:
- Extracting text from screenshots of web pages or mobile apps
- Digitizing physical documents like invoices, contracts, or reports
- Automating the process of extracting key information from forms or surveys
- Integrating the model into a workflow for processing large batches of images or documents

**If you enjoyed this guide, consider subscribing to the [AImodels.fyi newsletter](https://aimodels.substack.com) or following me on [Twitter](https://twitter.com/mikeyoung44) for more AI and machine learning content.**
How Fast can Python Parse 1 Billion Rows of Data?
Tags: programming, python, opensource, dataengineering
Published: 2024-05-01 15:02:57

Covered about “One Billion Row Challenge” a couple of times in the newsletter. This is another one by Doug Mercer. He adapted one of the top Python submissions which uses only built-in libraries and he also used a few awesome libraries (polars, DuckDB) that shared that approach too. Of Course, they are not near to the winner approaches for top submissions but using Python libraries we can write simple and elegant solutions which will do the magic in sub-10 seconds.

{% embed https://www.youtube.com/watch?v=utTaPW32gKY %}
ImportError: attempted relative import with no known parent package
Tags: python, django, developer
Published: 2024-05-01 14:59:17

The error message below occurs when you use the incorrect virtual environment interpreter that you created for your Django project. To resolve this issue, follow the steps outlined in this instructional video.
[How to Resolve Django ImportError](<iframe width="693" height="382" src="https://www.youtube.com/embed/UakORYk-rsk" title="django  Import Error" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>)

```
ImportError: attempted relative import with no known parent package
```
Linkedin: www.linkedin.com/in/albert-eromosele-47321370
twitter: @crawlerdO1
Exploring Servlets in Java: Building Dynamic Web Applications
Published: 2024-05-01 14:55:29

Hey Dev.to community! Today, I embarked on a journey to explore Servlets in Java, and it's been an enlightening experience. Here's a breakdown of what I learned:

Introduction to Servlets: Explored the basics of Servlets, understanding their role in Java web development and their significance in building dynamic web applications.
Servlet Architecture: Discussed the architecture of Servlets, including servlet containers, servlet lifecycle, and how servlet instances handle client requests and responses.
Sending Data between Servlets: Explored various techniques for sending data from one servlet to another, such as request forwarding, request attributes, session attributes, and URL parameters.
Overall, my journey into Servlets has equipped me with valuable insights into web development and enhanced my ability to build interactive and scalable web applications. Excited to continue exploring and experimenting with Servlets in my projects! #Java #Servlets #LearningJourney
my favorite 3 Chrome extensions
Tags: extensions
Published: 2024-05-01 14:51:55

I introduce my my favorite 3 Chrome extensions.

## Voice In
this is especially recommend chrome extension!!
We can voice input easily on chrome.

voice input is not used much in Japan.
But, I use voice input everyday.

I usually voice input in Japanese.
so, it is difficult to input programming code by this extensions for me.
but, I wanna be speak English well, and input programming code by this extensions.
[get Voice in](https://chromewebstore.google.com/detail/voice-in-speech-to-text-d/pjnefijmagpdjfhhkpljicbbpicelgko)

## Video Speed Controller
this is extension that can control video speed easily.
just one touch keyboard 's' or 'd'.
[get Video Speed Controller](https://chromewebstore.google.com/detail/image-downloader/cnpniohnfphhjihaiiggeabnkjhpaldj)

## Image Downloader
this is excellent extension.
because it can list and download all images in bulk in current page.  
we do not need to open developer mode to download images.
by the way, take care copyright of images.
[get Image Downloader](https://chromewebstore.google.com/detail/image-downloader/cnpniohnfphhjihaiiggeabnkjhpaldj)


next time, I'm gonna introduce another chrome extensions when I using in the work.
Looking for an app where I can take a screenshot of a few different numbers and it'll sum them up!
Tags: discuss, help
Published: 2024-05-01 14:43:40

I have an itch I need to scratch!

![A three-toed sloth scratching itself and looking content while hanging on a tree branch](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/z8fkiaohpth7e36xpmos.gif)

Anybody know of any apps out there that allow the user to take a picture of a handful of numbers and it'll add them together?

Ideally, I'd like the app to work on my MacBook Air and allow me to feed it screenshots. I'm not really looking for a mobile app right now, though I found this cool-looking option called [PhotoCalc](https://apps.apple.com/ca/app/photocalc-image-calculator/id1626268219) that's designed for iPhone.

Anywho, if you know of an app like this, please give me a shout — thanks!
Kompleksowy przewodnik po zakupie samochodu w Warszawie
Published: 2024-05-01 14:37:52

Kiedy już będziesz miał jasny obraz swojego budżetu i preferencji, czas zbadać lokalny rynek samochodowy. Przeglądaj renomowanych dealerów, zarówno offline, jak i online, aby porównać ceny, modele i dostępny asortyment. Serwisy otomoto.pl i allegro.pl to popularne platformy zakupu samochodów nowych i używanych w Polsce, oferujące szeroki wybór pojazdów od prywatnych sprzedawców i dealerów na terenie całego kraju. Dodatkowo wizyta w lokalnych salonach w Gdańsku pozwala na osobiste oględziny samochodów, jazdę próbną oraz omówienie możliwości finansowania z kompetentnymi przedstawicielami handlowymi.

Oceniając potencjalne samochody, zwróć uwagę na takie czynniki, jak przebieg, wiek, stan i historia serwisowa. Dokładna inspekcja może pomóc w zidentyfikowaniu wszelkich istniejących problemów lub potencjalnych kosztów konserwacji w przyszłości. Zastanów się, czy zaufany mechanik sprawdzi pojazd przed dokonaniem zakupu, zwłaszcza jeśli kupujesz używany samochód. Ten dodatkowy krok może zapewnić spokój ducha i zapobiec przykrym niespodziankom po zakupie.

W Polsce rejestracja pojazdu i przeniesienie własności wiążą się ze specyficznymi procedurami prawnymi, których muszą przestrzegać zarówno kupujący, jak i sprzedający. Kupując samochód w Gdańsku, upewnij się, że cała niezbędna dokumentacja, w tym umowa sprzedaży, dokumenty rejestracyjne i dowód własności, została prawidłowo wypełniona i podpisana. Dodatkowo sprawdź, czy pojazd przeszedł wszelkie wymagane przeglądy i spełnia obowiązujące normy emisji i bezpieczeństwa.

https://www.autoholowaniekatowice.pl/
Is it possible to have a service only used by an AuthGuard in the same module be a singleton?
Tags: nestjs, help
Published: 2024-05-01 14:37:15

I haven't been able to get it to work. It seems like the constructor of the auth guard is only called once, but I get a different instance of the service when canActivate is called in the guard.

Is there a way to confirm this? Is there a thing I can log to get the instanceId of the service or something?
PHP: testing, "Attention please!"
Tags: php, programming, beginners, testing
Published: 2024-05-01 14:31:26

![](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/g66w2j8nonltj5uevkfu.jpg)

## Why bother with tests anyway?

Unit tests encourages developers to write modular and reusable components.

If those components are isolated enough, it should be easier to validate and maintain.

However, dev teams need other types of tests in addition, for example:

* functional tests
* e2e (end-to-end) tests

Just because a single component works does not mean the entire feature is ready to go. Dependence on unit tests alone is risky. 

## Signs that your units tests should be improved

![](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/7gk2p1c6phtsn48jx7qp.jpg)

Let's review some examples:

* the tests are not automated (e.g., manual run, no build, no CI/CD)
* the tests are difficult to read (e.g., no recognizable patterns like AAA, nonexistent or bad naming convention, too much asserts per test, etc)
* there's a tight coupling between 2 or several tests (e.g., chained tests)
* the tests focus on the implementation instead of the behavior (e.g., it duplicates the implementation logic)
* there are too many tests, to the point that modifying small blocks of code breaks dozens of tests
* some tests are redundant, which could impact the build time and the CI/CD
* the tests never fail, regardless of your modifications in the code
* you read code coverage at face value: while it IS important, it's not a quality indicator

## So... developers are doomed?

![](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/zedc01eamta7e2my7nlt.gif)

Don't give up. Just because tests can be tricky doesn't mean it's a losing game.

It's a craft.

Besides, there are practical solutions to improve the situation:

* code reviews: let [more experienced] teammates read your tests, not just your code
* you may remove redundant tests and improve existing tests when refactoring
* consider adding [mutation tests](https://infection.github.io/)
Machine Learning: Day 2
Tags: machinelearning, programming
Published: 2024-05-01 14:29:52

## Types of Machine Learning Algorithms

1. Supervised Learning
2. Unsupervised Learning
3. Recommender Systems
4. Reinforcement Learning

## Supervised Learning

- Refers to algorithms that learn input-to-output mappings.
- Give learning algorithm examples to learn from that include the "output" label for a given input X.
- Eventually learns to take just the input alone without the output label and gives a reasonably accurate prediction or guess of the output.
- Learns from being given "right answers."

## Examples of Supervised Learning

| Input (X)         | Output (Y)             | Application          |
|-------------------|------------------------|----------------------|
| Email             | Spam (0/1)             | Spam Filtering       |
| Audio             | Text Transcripts       | Speech Recognition   |
| English           | Spanish, Chinese, etc  | Machine Translation  |
| Ad, User Info     | User Click (0/1)       | Online-Advertisments |
| Image, Radar Info | Position of other cars | Self-Driving Cars    |

## How does it learn? (Simplified)

1. Split the data by 80% for training data and 20% for test data.
2. Train the model with examples of Input (X) and Labels (Y) using the 80% training data.
3. Use the 20% test data or unseen data, to predict or guess the output.

> "Eventually learns to take just the input alone without the output label and gives a reasonably accurate prediction or guess of the output"

- Andrew Ng

## Types of Supervised Learning Algorithm

![Linear Regression Plot](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/pgb94hkpx8i43pm0c03o.png)

### 1. Regression

- It is used to analyze the relationship between the independent variables and dependent variables.
- Predict a number from infinitely many possible numbers.
- Example: house prices (Y), size of the house (X)
- When you see a plot that uses linear regression, the Y always refers to the value we want to predict.

![Classification Plot](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/eu11krvek2oro5icfyho.png)

### 2. Classification

- We are trying to predict only a small number of possible outputs or categories.
- There are more than two possible outputs.
- **Class/Category** is the term that we use for the output.
- Predict categories, usually non-numeric.
- Find the boundary line that separates 0 and 1.
- Breast Cancer Detection ``[0: benign, 1: malignant]``
- Examples: Cat or Dog, Benign or Malignant

## Image References

[Linear Regression Plot](https://www.researchgate.net/figure/Linear-Regression-model-sample-illustration_fig3_333457161)

[Classification Plot](https://machinelearningmastery.com/types-of-classification-in-machine-learning/)
Simple Route53 :)
Published: 2024-05-01 14:12:09

Hey guys!! 
 I would like to explain the concept of Route53 in simple....Let us walk together through my blog..
 
 Firstly Route53 in aws denotes the DNS as a Service.Here's how..
When the user sends any request to the application the flow is as follows 
Internet Gateway -> Route53 -> In the Public Subnets we have NAT and Load Balancers -> Private subnets
 From the flow Route53's work is like when an user for an instance tries to access the flipkart.com , amazon.com so on ,it has to convert the domain name i.e like flipkart.com into an ip address of a load balancer.Its because its hectic for the users to remember all the ip address instead of accessing them like a piece of cake by the domain names.So the users always tries to access only through the Domain names.Thus the Route53 takes care of this translation into a load balacers's ip address.

How to register our domain names in AWS Route53?
  1.If you already have a domain name purchased form GoDaddy or some other else ,aws can integrate it ,or if you are going to purchase a new domain 
 2.This step is mandatory i.e Hosting Zones in which the aws can have the DNS records that maps the domain name into an ip address 

-----------------Its how the Route53 functions-------------------- 
Also it performs Health Checks by sending request like 2mins once or 5mins once to web server to check the condition of the web servers,if it is good ,it will forward the traffic,and if we have more instances ,it will balance the traffic..

Thank you for your valuable time here .But its a simple concept of Route53 ,there is also a vast complexity too...Happy reading!!
Interview Question: Explain the lifecycle of HTTP request
Tags: webdev
Published: 2024-05-01 14:05:50

It is one of the most common question these days for interviews. However I think this question has very little utility. A person can be excellent front end engineer without ever having to know how DNS works. 

But those who are looking for answers I have written this answer by [referring to this excellent resource for frontend engineering](https://www.frontendeng.dev/). 

## Request Initiation 

Request is often initiated by some user action. Typing url in browser, clicking on a link etc. The browser obtains the link and decides to fetch it for you by first looking at the TLD of the hostname. For example www.mydomain.com/path would make the browser first look at mydomain.com 

## DNS Resolution 

Browser queries the DNS service in OS to convert mydomain.com to an ip address. Once it is resolved it looks up the www.mydomain.com which is called the subdomain. 

## TCP connection

Browser that tries to open a connection on port 80 on the resolved IP address. These days it is going to be port 443 because of SSL. 

This process involves TCP/TLS handshake. Once the connection is established browser looks at the "path" portion in the URL. 

## PATH 

Browser then presents the rest of the path to the server with which it has oppened the connection. Depending on the request type (GET/POST/DELETE) etc. it might also provide additional data to server. 

The server will handle this information based on what kind of technology and architecture it has. 

## The server takes in all the input and generates an outpu

This output is passed back to the server. 

Both client and server close the TCP connection. 

## The browser loads everything on the screen. 

The browser then looks at the content-Type of the response and renders it in the viewport. 

There are plenty of steps that go into this rendering process but we will leave that out. 

## Conclusion

This is what an interviewer is looking for in such questions whether you have good basic understanding of most of these steps or not. 

[1] https://www.frontendeng.dev/blog/46-explain-lifecycle-of-internet-request