teleren/devto huggingface dataset:
Ant Motion Tracking with Python and OpenCV!
Published: 2024-01-11 16:58:57



🔍 Explore the mesmerizing world of Ant Motion Tracking using Python and OpenCV! 🐜💻 Uncover the secrets of precise motion detection with our easy-to-follow tutorial. Subscribe for more coding insights and stay at the forefront of tech innovation! 🚀📈

Implementation code

Now, let's dive into the implementation. Ant Motion Tracking implementation using Python and the OpenCV library. This assumes that you have prior knowledge of setting up Python and installing the necessary libraries.:




**CODE**

import cv2
import numpy as np

# Initialize video capture
cap = cv2.VideoCapture('ant.mov') # Replace with your video file

# Create background subtractor
fgbg = cv2.createBackgroundSubtractorMOG2()

# Create an empty list to store the ant positions
ant_positions = []

while True:
ret, frame = cap.read()
if not ret:
break

# Apply background subtraction
fgmask = fgbg.apply(frame)

# Remove noise using morphological operations
kernel = np.ones((5, 5), np.uint8)
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_CLOSE, kernel)
# Find contours in the binary mask
contours, _ = cv2.findContours(fgmask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# Draw bounding boxes and circles around moving objects (ants)
for contour in contours:
if cv2.contourArea(contour) > 500: # Adjust the area threshold as needed
x, y, w, h = cv2.boundingRect(contour)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)

# Calculate the centroid of the bounding box
cx, cy = x + w // 2, y + h // 2

# Draw a circle at the centroid
cv2.circle(frame, (cx, cy), 10, (0, 0, 255), -1)

# Save the ant position
ant_positions.append((cx, cy))

# Display the original video and the processed video
cv2.imshow('Original Video', frame)
cv2.imshow('Foreground Mask', fgmask)

if cv2.waitKey(30) & 0xFF == 27: # Press 'Esc' to exit
break

cap.release()
cv2.destroyAllWindows() 





Save the above script as a Python file (e.g., streamlit run app.py ) and run it on your os system . The script upload iamge from the machine, performs analyze images , and displays the live feedback.

Conclusion

In conclusion, this Python and OpenCV implementation showcases a simple yet effective Ant Motion Tracking system. By leveraging computer vision techniques, we've created a program that detects motion, making it a versatile tool for various applications. This project serves as a foundation for further exploration and customization, empowering developers to delve into the exciting realm of computer vision and real-time object tracking. Happy coding! 🚀🐜💻
WEB DEV SECRETS E-BOOK
Tags: webdev, javascript, beginners, html
Published: 2024-01-11 16:58:11

``Discover The secrets Of WEB DEV With Our E-book !!!

## 📚 Who Is This For?

- Beginners Exploring Web Development
- Developers Enhancing Their Skills
- Tech Enthusiasts Keen on the Latest Trends


![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/osruckr8uffr4mdnnuwa.png)

 [Buy From Here !!](https://topdigital28.gumroad.com/l/nnjyl)
Gemini Pro Vision Image Analysis Project 📷
Published: 2024-01-11 16:57:15



This project involves leveraging the powerful capabilities of the Gemini Pro Vision Model for comprehensive image analysis. Through a user-friendly web interface, users can upload images, triggering a backend process that utilizes the Gemini Pro Vision Model to provide insightful analysis. The results, ranging from object detection to intricate details, are then presented to the user, enhancing their understanding of the uploaded images.



Implementation code

Now, let's dive into the implementation. We'll use Python and streamlit to local interface and easy upload an image and Image Analysis Below is a simple Python script for Gemini Pro Vision Image Analysis Project:


**CODE**

import streamlit as st

import google.generativeai as genai

import google.ai.generativelanguage as glm

from PIL import Image

API_KEY = ''

genai.configure(api_key=API_KEY)

st.set_page_config(page_title="Gemini Pro Vision Image Analysis Project" ,page_icon="📸", layout="centered", initial_sidebar_state='collapsed')

st.header("Google AI Studio + Gemini Pro")

uploaded_file = st.file_uploader("Choose an Image file", accept_multiple_files=False, type=['jpg', 'png'])

if uploaded_file is not None:

image = Image.open(uploaded_file)

st.image(image, caption='Uploaded Image', use_column_width=True)

bytes_data = uploaded_file.getvalue()

generate = st.button("Generate!")

if generate:

model = genai.GenerativeModel('gemini-pro-vision')

response = model.generate_content(glm.Content(parts = [glm.Part(text="Write a short, you know this? what is this?"),glm.Part(inline_data=glm.Blob(mime_type='image/jpeg', data=bytes_data )),], ),stream=True)

response.resolve()

st.write(response.text)





Save the above script as a Python file (e.g., streamlit run app.py ) and run it on your os system . The script upload iamge from the machine, performs analyze images , and displays the live feedback.


Conclusion

As we conclude this exploration, we celebrate the marriage of cutting-edge technology and user- centric design. The Gemini Pro Vision Model opens a new frontier, where users seamlessly navigate the intricacies of image analysis. This project is not just about technology; it's a testament to the transformative power of models like Gemini Pro, where every image tells a story waiting to be discovered. Join us on this exhilarating journey into the depths of visual intelligence. As we continue to push the boundaries of AI applications, Gemini Pro stands as a symbol of what's possible when innovation and accessibility converge.
Actuators in SpringBoot :
Published: 2024-01-11 16:55:19


 
Actuators are the list of endpoints which are provided by spring boot by default so that our applications has production ready features. the main benefit of actuators is that we can get production grade tool without having implement these features by ourselves .
 
To enable spring boot actuator , we need to add spring boot actuator dependency in
pom.xml :

`<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>`


also add configuration to application.property file:

```
management.endpoints.web.exposure.include=* 
```

some of the endpoints :

>  /health - it summarizes the health status of application.
> /loggers- it enables us to query and modify the logging level of 
             our application.
>  /env    - returns the current enviroment property .
>  /info   - returns general information.
>  /beans  - returns all available beans in our BeanFactory. 

There are many benefits of using actuators but main is that we can check the health of microservices .for example there is an order service and a discovery server. the server send message to the service in every T seconds to check wheather service is UP or Down . if it is UP then order service send status code 200 otherwise 500 or 503 . 
here T seconds should be chosen in a such  a manner so that the api calls should be minimum .
VSCode TypeScript is Stuck!?
Tags: vscode, typescript, devtip
Published: 2024-01-11 16:55:10


![TypeScript Code with an error](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/ncwd3lt9j5h56afeliy1.png)

How many times have you seen this little squiggley in your code and you are sure it shouldn't be there? Happens to me quite a lot. Usually when I install a new package and TypeScript doesn't seem to pick it up. Well there is a quick way to fix it (if it really shouldn't be there).

While you are focused on a typescript file (.ts), open the command prompt `cmd` + `shift` + `p`. Type "restart" in the prompt and look for "TypeScript: Restart TS Server". 

Now, assuming you don't have a type or lint error, you will be good to go again.
How to Update Jupyter Notebook or Jupyterlab 🧑🏻‍💻
Published: 2024-01-11 16:54:42

To update Jupyter Notebook or Jupyterlab to a particular version or the most recent version, use pip or conda. These instructions can be used to update Jupyter Notebooks or Jupyterlabs running Linux, Windows, or Mac OS.



Upgrade Jupyterlab using pip

pip compatibility and ease of use make it a dependable and practical option for updating Jupyterlab or Jupyter Notebook. It guarantees that your Jupyter environment is kept and current for your data analysis, coding, and research needs. Upgrade pip first, then the necessary package, before using pip.


Note: If you have installed Jupyterlab with conda, do not use pip to upgrade instead use conda to upgrade.


# Upgrade pip
pip install --upgrade pip

# Update jupyterlab using pip
pip install --upgrade jupyterlab

# Using pip3
pip3 install --upgrade jupyterlab



To utilize the new version of Jupyter Notebook, exit the browser and launch Jupyter Lab after the upgrade is finished.


If you want to install a specific Jupyter version use the below command.


# Update jupyterlab to specific version
pip install jupyterlab==1.2.4



Upgrade Jupyterlab using conda

If you are using Jupyterlab on Anaconda, you can use the conda command to update Jupyter Notebook to the latest version.

conda is a command-line package and environment management system primarily associated with Anaconda and Miniconda, two popular distributions of Python and data science packages. Conda is used to create, manage, and switch between different Python environments, as well as to install, update, and manage software packages such as Python packages, libraries, and applications.


# Update jupyterlab using conda
conda update -c conda-forge jupyterlab


You can also uninstall and install the specific or latest version.


# Uninstall and install
conda uninstall jupyterlab

conda install -c conda-forge jupyterlab=3


Alternatively, you can also upgrade all packages in Conda in one go.


# Upgrade all packages
conda update --all



Update using Homebrew

Open your terminal and run the following command to update Homebrew to the latest version. In order to use this, you should have Jupyterlab installed with the brew command.

# Update brew
brew update

# Update jupyterlab
brew upgrade --cask jupyterlab


Update Jupyter Notebook

If you have Jupyter Notebook installed without Jupyterlab then follow the following steps to update Jupyter Notebook


# Upgrade Jupyter notebook
conda update notebook

# Using pip
pip install -U notebook


If you are running an older version of the IPython Notebook (version 3 or earlier) you can use the following to upgrade to the latest version of the Jupyter Notebook.


# Upgrade Jupyter notebook
conda update jupyter

# Using pip
pip install -U jupyter
How to Install Anaconda on Windows 🧑🏻‍💻
Published: 2024-01-11 16:53:01



How to Install Anaconda on Windows Step-by-Step. The data science and machine learning community uses Anaconda as the primary and most popular distribution platform for Python and R programming languages because it makes installing programs like PySpark, pandas, Numpy, SciPy, and many more easier.


Steps to Install Anaconda on Windows

Step 1. Download Anaconda windows version

Step 2. Install Anaconda

Step 3. Create Anaconda Environment

Step 4. Install and Run Jupyter Notebook


1. Download & Install Anaconda Distribution for Windows

Follow the below step-by-step instructions to install Anaconda distribution on windows.

1.1 Download Anaconda Distribution

Go to [https://www.anaconda.com/](https://www.anaconda.com/ )and select Anaconda Individual Edition to download the latest version of Anaconda for windows. This downloads the .exe file to the windows download folder.

1.2 Install Anaconda on Windows


Double click the .exe file to start the Anaconda installation, follow the below steps to complete the installation on windows
qh88watch
Published: 2024-01-11 16:51:57

QH88 là nhà cái quốc tế, có trụ sở chính đặt tại Philippines. QH88.WATCH kênh thông tin hỗ trợ chính thức của nhà cái QH88 - QH88 CASINO tại thị trường Việt Nam #qh88 #nha_cai_qh88 #game_bai_qh88 #casino #QH88_Watch  Phone: 0562203459  Địa chỉ: 36 Ng. 39 Đ. Yên Xá, Tân Triều, Thanh Trì, Hà Nội, Việt Nam  [https://qh88.watch/](https://qh88.watch/) [https://qh88.watch/dang-ky-qh88/](https://qh88.watch/dang-ky-qh88/)
Enabling & Increasing Raspberry Pi Swap! 🖥️
Published: 2024-01-11 16:50:46

**Note.** Due to RAM limitations in Raspberry Pi 3 and earlier versions, we now recommend ALL users to use Neblio with Raspberry Pi 4. Any model of Raspberry Pi 4 should work, models with more RAM are more likely to run Neblio.

Users of Neblio who stake on Raspberry Pis earlier than the Raspberry Pi 3 (such as the Original Raspberry Pi, Raspberry Pi Zero, and potentially the Raspberry Pi 2) may benefit from a significant increase in performance by enabling and/or increasing the size of the Raspberry Pi's swap file.

To enable the Raspberry Pi swap file and set it to a size of 1 GB (1024 MB), run the following commands on the Raspberry Pi in a terminal window:

**COPY and Paste Terminal**

1. Temporarily Stop Swap:

sudo dphys-swapfile swapoff 

2. Modify the size of the swap

As root, edit the file /etc/dphys-swapfile and modify the variable CONF_SWAPSIZE to 1024:

CONF_SWAPSIZE=1024

Using a command such as:

sudo nano /etc/dphys-swapfile 

3. Initialize Swap File

sudo dphys-swapfile setup 

4. Start Swap

sudo dphys-swapfile swapon

That's it! Now simply restart neblio-Qt or nebliod on your Raspberry Pi for increased performance!

Note: Using a swap file could potentially result in an increase in writes & reads to your Raspberry Pi's SD card, possibly lowering the lifespan of the card. However in most cases Raspbian ships with a default swap file with a size of 100 MB and in this case we are simply increasing that to 1024 MB.
Face Detection With OpenCV on Raspberry Pi 3,4,5
Published: 2024-01-11 16:46:54



In this tutorial, we will explore how to perform face detection using OpenCV on a Raspberry Pi 3,4,5 with a webcam. Face detection is a computer vision task that involves identifying and locating human faces in images or video. OpenCV, a popular computer vision library, provides powerful tools for face detection.

Prerequisites

Before we begin, make sure you have the following:

- Raspberry Pi 4    

- Webcam connected to the Raspberry Pi 4    

- Power supply (official Raspberry Pi power supply is preferable)    

Download the haarcascade_frontalface_default.xml:

Visit the haarcascade xml file and download the haarcascade frontalface and put same folder

Implementation

Now, let's dive into the implementation. We'll use Python and OpenCV to capture video from the webcam and apply face detection. Below is a simple Python script for face detection:

CODE:  

import cv2
import sys

cascPath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascPath)

video_capture = cv2.VideoCapture(0)
video_capture.set(3, width)
video_capture.set(4, height)

while True:
# Capture frame-by-frame
ret, frame = video_capture.read()

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.cv.CV_HAAR_SCALE_IMAGE
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)

# Display the resulting frame
cv2.imshow('Video', frame)

if cv2.waitKey(1) & 0xFF == ord('q'):
break

# When everything is done, release the capture

video_capture.release()
cv2.destroyAllWindows()




Save the above script as a Python file (e.g., face_detection.py) and run it on your Raspberry Pi. The script captures video from the webcam, performs face detection, and displays the live feed with rectangles around detected faces. Press 'q' to exit the application.
Introduce to Connecting Raspberry Pi 4 with a mini LCD display!
Published: 2024-01-11 16:44:00

1. Get the Necessary Hardware:

- Raspberry Pi 4    

- MicroSD card (16GB or higher is recommended)    

- Power supply (official Raspberry Pi power supply is preferable)     


2. Download the Operating System:

Visit the [official Raspberry Pi website](https://www.raspberrypi.com/software/operating-systems/) and download the latest version of Raspberry Pi OS.


3. Flash the MicroSD Card:

Use a tool like [Etcher](
3. Flash the MicroSD Card:

Use a tool like Etcher to flash the downloaded Raspberry Pi OS image onto the microSD card.
) to flash the downloaded Raspberry Pi OS image onto the microSD card.


**[Installation & setup on Raspberry Pi 4 ](https://youtu.be/L4vRqnG6ZXU?si=tKYvSpeOiUCIMrUo)**

Step 1: Install dependencies

1. Updating Existing Packages:
sudo apt update && sudo apt upgrade

2. Installing Image I/O Packages:
sudo apt-get install libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev

3. Setting Up Video I/O Packages:
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev

sudo apt-get install libxvidcore-dev libx264-dev

4. Installing the GTK Development Library:
sudo apt-get install libgtk2.0-dev

5. Additional Dependencies for OpenCV Optimization:
sudo apt-get install libatlas-base-dev gfortran

Step 2: Installing pip (Package Management Tool)
sudo apt-get install python3-pip

Step 3: Installing the Numpy Library
pip install numpy sudo apt-get install python3-pip

Step 4: Accessing OpenCV on Raspbian Repository
apt list python*opencv*

Step 5: Installing OpenCV
sudo apt install python3-opencv

To confirm the installation of OpenCV, use:
apt show python3-opencv
Odoo : database initialized error
Published: 2024-01-11 16:36:00

In odoo, if you ever an error as  below 


```
 20440 ERROR ? odoo.modules.loading: Database somedatabase not initialized, you can force it with `-i base` 
```
try running odoo with below command 

```
odoo.bin -c odoo.conf -i base -d somedatabase
```
How to install tensorrt on Jetson
Published: 2024-01-11 16:33:28

**Copy and paste Terminal** 

sudo apt update && sudo apt upgrade && sudo apt autoremove &&  &&  sudo apt install nvidia-tensorrt

you should find some python libraries installed. (ex. python3-libnvinfer) 

$ apt show cache nvidia-tensorrt Package: nvidia-tensorrt Version: 4.6.2-b5 Priority: standard Section: metapackages Mainta…
Ibuprofeno.py💊| #20: Explica este código Python
Published: 2024-01-11 16:32:41

## **<center>Explica este código Python</center>**
#### <center>**Dificultad:** <mark>Básico</mark></center>

```py
list = [1,2,2,3,4,5,5,6]
set = set(list)
print(set)
```

- A. `{1, 2, 3, 4, 5, 6}`
- B. `{2, 2, 5, 5}`
- C. `{1, 3, 4, 6}`
- D. `{2, 5}`

---

Respuesta en el primer comentario.
Data Ownership Protocol (DOP) Airdrop!!
Published: 2024-01-11 16:26:41

**🚀 Exciting News in Data Privacy! 🌐**
I'm thrilled to share information about the Data Ownership Protocol (DOP), an innovative project reshaping the landscape of data ownership, privacy, and sharing.

**🔗 What is Data Ownership Protocol?**
Data Ownership Protocol is revolutionizing how users interact with their data. In a world where data privacy often feels like a distant dream, DOP empowers individuals to take control of their information, selectively sharing it on their terms. Leveraging cutting-edge zero-knowledge cryptography, DOP ensures precise control over data related to crypto assets, transactions, NFT ownership, and online activities.

**🔍 Key Features and Benefits:**
Selective data disclosure to platforms and decentralized applications
Privacy control over sensitive blockchain transaction data
Verifiable credential sharing without exposing entire wallet histories
Interoperability with Ethereum dApps (thanks to EVM compatibility)
Ability to control data usage by counterparties and revoke access if necessary.

**🔗 DOP Testnet Airdrop Opportunity:**
To test its groundbreaking technology, DOP has launched a public testnet. Here's your chance to earn free DOP tokens by actively participating in the testnet before the mainnet launch.

**🚀 Key Details about the Testnet Airdrop:**
Complete testnet tasks for proportional DOP token rewards
Mainnet and token launch estimated in Q1 2024.

**🔧 Step-by-Step Guide to DOP Testnet Participation:**
Follow the comprehensive guide below to join the DOP testnet, complete required tasks, and position yourself for potential rewards.

1️⃣ Click [**here**](https://doptest.dop.org?id=pS3NFS1)
2️⃣ Create your DOP testnet wallet and save your recovery phrase securely.
3️⃣ Connect your MetaMask wallet for seamless integration.
4️⃣ Follow DOP's Twitter account for updates.
5️⃣ Claim testnet tokens and complete tasks like encrypting data.
6️⃣ Refer friends for a 20% bonus on their testnet activity.
7️⃣ Wait for the mainnet launch expected in Q1 2024.

**🔐 Why Data Privacy Matters:**
DOP aligns with the growing demand for user control over personal data. With over 2.5 quintillion bytes of data created daily, DOP gives individuals the tools to manage access using encryption, zero-knowledge proofs, and self-sovereign identity. In a world where user privacy is paramount, projects like DOP stand at the forefront of blockchain innovation.

**💡 Conclusion - Seize the Opportunity!**
Participating in the DOP testnet not only aligns with the ethos of decentralization but also positions you to benefit from early access to a groundbreaking data privacy project. Sign up, complete tasks, refer friends, and stay tuned for the DOP mainnet and token launch.
Let's take control of our data and embrace a future where privacy is not just a right but a reality! 

🌐✨ #DataPrivacy #DOP #BlockchainInnovation
React 18's Rendering Revamp: A Deep Dive into the New Client and Server APIs
Tags: react, javascript, webdev, programming
Published: 2024-01-11 16:24:34

Hey devs, it's time to talk about rendering in React 18! This major update brought some significant changes to how we handle both client-side and server-side rendering, opening exciting possibilities for building performant and SEO-friendly web experiences. Buckle up, because we're diving deep into the new APIs and exploring what they mean for your React workflow.

**New Faces on the Block:**
React 18 introduces a fresh set of APIs in `react-dom/client` and `react-dom/server`. These replace the familiar friends like `ReactDOM.render` and `ReactDOM.hydrate`. Don't fret, the old APIs haven't vanished entirely. They're still available in React 17 mode, allowing a smooth transition to the new ways.

**Client-Side Rendering 2.0**
The new `createRoot` API takes center stage for client-side rendering. It offers granular control over root creation and lifecycle, enabling features like concurrent rendering and suspense. No more magic behind the scenes – you're now the conductor of the rendering orchestra!

`Server-Side Rendering Gets Streamlined:`
Say goodbye to clunky SSR workflows! React 18 provides versatile server-side APIs like `renderToStaticMarkup` and `renderToPipeableStream`, letting you generate static or streamed HTML. This opens doors for optimized initial load times, improved SEO, and even progressive rendering experiences.

**Hydration with Precision:**
Hydration, the process of connecting server-rendered HTML to the client-side JavaScript, gets an upgrade with `hydrateRoot`. This API gives you the power to selectively hydrate parts of your app, allowing smoother transitions and better resource management.

**More Than Just APIs:**
These changes go beyond just swapping out functions. They mark a shift in React's philosophy, empowering developers with greater control and flexibility over the rendering process. This opens up doors for innovative server-side architectures, SSR/CSR hybrids, and even custom rendering solutions.

**Conclusion**
React 18's new rendering APIs are a game-changer, offering incredible potential for building exceptional web experiences. Embrace the learning curve, experiment with the features, and discover how these tools can elevate your React development to the next level. Remember, with great power comes great responsibility – use it wisely, fellow devs!