semvec/pypi-packages huggingface dataset:
pyroll-integral-thermal 3.0.0
Plugin for PyRolL providing an integral thermal moddeling approach.
Requires Python: >=3.9

# PyRolL Integral Thermal Model

Plugin for PyRolL providing an integral approach for thermal modelling.

## Documentation

See the [documentation](https://pyroll-project.github.io/modules/pyroll-integral-thermal/docs/docs) to learn about basic
concepts and usage.

## License

The project is licensed under the [BSD 3-Clause license](LICENSE).

## Installation

The package is available via [PyPi](https://pypi.org/project/pyroll-integral-thermal/) and can be installed with
    
    pip install pyroll-integral-thermal
ADBconnect 0.1.1
Controlling your phone via ADB.
Requires Python: >=3.6
Keywords: adb phone ADB

# ADBconnect  
**Control your phone from your PC via USB debugging.**

### Installation:  
Before using ADBconnect, you need to install [ADB](https://developer.android.com/tools/releases/platform-tools?hl=ru).  

### Setup:
#### USB:  
To configure the device you can use arguments:  
```commandline
adb_path - path to adb
device - ID of the device to connect (if you donвЂ™t specify it, it will try to connect to the first existing one)
name - device name
``` 
<br>

```python
from ADBconnect import USB

phone = USB(adb_path=r"C:\Users\ijidishurka\platform-tools", device='67e345rf')

phone.action.tap(100, 100)
```
in order to find out the device ID, enter adb devices

<br>

#### WIFI:  
```commandline
*ip - device ip address
adb_path - path to adb
port - device port (default 5555)
name - device name
``` 
<br>

```python
from ADBconnect import WIFI

phone = WIFI(adb_path=r"C:\Users\ijidishurka\platform-tools", ip='192.168.0.101')

phone.action.tap(100, 100)
```

### See code examples on our [github](https://github.com/Ijidishurka/ADBconnect/tree/main/examples)
opencv-ffmpeg-gstreamer 4.5.3
Custom OpenCV build with FFmpeg and GStreamer support
Requires Python: >=3.6

# OpenCV with FFmpeg and GStreamer Support

This project provides a custom build of OpenCV with support for FFmpeg and GStreamer, enabling enhanced video and image processing capabilities. It’s packaged as a Python wheel for easy installation and compatibility across different projects.

## Features
- **FFmpeg Integration**: Enables advanced video processing, encoding, and decoding.
- **GStreamer Integration**: Provides support for flexible multimedia pipelines and video processing tasks.
- **Python Bindings**: Easily installable as a Python package, making OpenCV available for use in your Python projects.

## Installation

Ensure that you have `FFmpeg` and `GStreamer` installed on your system. You can install them on Ubuntu using:

```bash
sudo apt update
sudo apt install -y libavcodec-dev libavformat-dev libswscale-dev \\
                    gstreamer1.0-tools libgstreamer-plugins-base1.0-dev \\
                    libgstreamer1.0-dev

Installing the Package
You can install the custom OpenCV package directly using pip:

pip install opencv-ffmpeg-gstreamer


System Requirements
Python: Version 3.6 or higher
Linux: Compatible with many manylinux-compatible distributions
Libraries: FFmpeg and GStreamer libraries must be installed on the system for full functionality


Usage
After installation, you can use OpenCV with Python just like the standard OpenCV package. Here is an example to get you started:

import cv2

# Print OpenCV version
print("OpenCV Version:", cv2.__version__)

# Load and display an image using OpenCV
image = cv2.imread('sample.jpg')
if image is not None:
    cv2.imshow('Sample Image', image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
else:
    print("Image not found. Make sure 'sample.jpg' is in the current directory.")


Verifying FFmpeg and GStreamer Support
To confirm that FFmpeg and GStreamer are enabled in your OpenCV build, run the following:

import cv2
print(cv2.getBuildInformation())

In the output, look for the following entries:

FFMPEG: YES - Confirms that FFmpeg support is enabled.
GStreamer: YES - Confirms that GStreamer support is enabled.

Example: Capturing Video from a Webcam
Here’s a quick example of using OpenCV to capture video from a webcam:

import cv2

# Open a connection to the webcam (0 is the default camera)
cap = cv2.VideoCapture(0)

if not cap.isOpened():
    print("Error: Could not open video device.")
    exit()

while True:
    # Capture frame-by-frame
    ret, frame = cap.read()
    if not ret:
        break

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

    # Press 'q' to exit the loop
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the capture and close the windows
cap.release()
cv2.destroyAllWindows()


License
This project is licensed under the MIT License. See the LICENSE file for more information.

Author
Heramb Mishra

For any questions or feedback, you can reach me at heramb1008@gmail.com. """