semvec/pypi-packages huggingface dataset:
django-ref 0.5.2
A Django app defining data models for managing bibliographic references for scientific databases.
Requires Python: >=3.6
Keywords: django,database,references,citation

============
django-pyref
============

The project, django-pyref, defines a Django app, refs, to create references for
scientific databases.  The goal of the app is to create a referencing system
where an administrator can obtain the full citation of an article from its
Digital Object Identifier (DOI). The stored references can be output in HTML,
BibTeX and JSON format.
dig-mhd 0.0.1
Dig, short for diagnostic, is used to help acquire diagnostic data from MDSplus.
Requires Python: >=3.8

# dig

## Structure


- *dig*, python package folder
- *notebooks*, python notebook folder to demonstrate how can we use dig

## Install

Prequisite: 
- [MDSplus](https://mdsplus.org/index.php?title=Downloads&open=1769734509572583850001&page=Software%2FDownloads)
- We do not support Anaconda. Use [virtualenv](https://wenyin.xyz/archives/python-virtual-env) instead if you don't want to mess up your system built-in python environment.

```bash
# for clients
pip install dig-mhd 

# for developers
cd /to-somewhere-you-want-to-clone-the-repo
git clone https://github.com/WenyinWei/dig.git
cd dig # (not dig/dig)
pip install -e . # "-e" means editable
```

Add `mhd_settings.ini` (you can find a template at this repo) to you application data path, *e.g.*
- `C:\Users\<your-user-name>\mhd\mhd_settings.ini` for Windows,
- `/home/<your-user-name>/.mhd/mhd_settings.ini` for Debian systems like Ubuntu.

Parameters are stored in this *.ini* file and you need to check and modify some of them. Having configuring the *.ini* file in a right way, the following import should be successful.


```python
import dig 
```

## Use Python in Matlab

### Common Data Format

_*.npy_, _*.npz_ file formats are common in python/numpy community; while _*.mat_ file format is common in matlab community. Matlab has professional [documents](https://ww2.mathworks.cn/products/matlab/matlab-and-python.html) to demonstrate how to use Python from Matlab and vice.

```python
from scipy.io import loadmat
annots = loadmat('*.mat')
```

```matlab
% In Matlab, npy-matlab module could help you read and write npy format files, https://github.com/kwikteam/npy-matlab
a = rand(5,4,3);
writeNPY(a, 'a.npy');
b = readNPY('a.npy');
```

```matlab
% In Matlab, configure Python environment https://ww2.mathworks.cn/help/matlab/ref/pyenv.html
pyenv % 返回当前默认的 Python 环境
pyenv('Version', 3.8) % 寻找当前电脑上的对应版本的 Python 环境
pyenv('Version', path-to-your-python-executable) % 寻找当前电脑上的对应路径的 Python 环境

if count(py.sys.path,'path-to-your-package') == 0
    insert(py.sys.path,int32(0),'path-to-your-package');
end

py.importlib.import_module('dig')
py.importlib.reload('dig')
returned_tuple = py.dig.utilvar.get_EAST_EFIT_BR_BZ_Bt(shotnum, py.list({tpoint1, tpoint2, ...}));
R = returned_tuple{1};
Z = returned_tuple{2};
tpoints = returned_tuple{3};
BRs = returned_tuple{4};
BZs = returned_tuple{5};
Bts = returned_tuple{6};
```

```python
# Rewrite all npy files in mat format, https://ww2.mathworks.cn/matlabcentral/answers/444998-how-do-read-npy-files-in-matlab#answer_624742
from scipy.io import savemat
import numpy as np
import glob
import os

npzFiles = glob.glob("*.npz")
for f in npzFiles:
    fm = os.path.splitext(f)[0]+'.mat'
    d = np.load(f)
    savemat(fm, d)
    print('generated ', fm, 'from', f)
```
coterie 0.0.1
Direct Implementation of computer vision with just a line of code
Requires Python: >=3.3

More about dronevision
==============================
It is a package having pre-built codes of face recognition, hands tracking module and body pose tracking. Implemented with a single line of code.

https://www.lakshaykumar.tech/

What Is This?
-------------

Implement the power of Computer Vision in your program with just few simple lines of code. Hand detection, Body Pose and face Recognition modules are included in this package


faceProcessor(image, draw=False)
> This function returns a 1D list of 3 items. Image (with rectangular box, if drawArea=True), area of face and [x,y,w,h]

bodyProcessor(image, draw=False)
> This function returns a list of 3 items i.e. Image (with rectangular box, if drawArea=True), list of body points and area of body.

handProcessor(image, draw=False)
> This function returns a list having image (with hand connections, if drawArea=True) and points in handlandmarks

Usage
-------

> faceProcessor(image, draw=True)
```
from cvindrone import faceProcessor
import cv2
cap = cv2.VideoCapture(0)
while True:
    success, image = cap.read()
    funValues = faceProcessor(image,draw=True)
    image = funValues[0]
    area = funValues[1]
    x,y,w,h = funValues[2]
    cv2.imshow('Faces', image)
    cv2.waitKey(1)
cap.release()
```

> bodyProcessor(image, draw=True)
```
from cvindrone import bodyProcessor
import cv2
cap = cv2.VideoCapture(0)
while True:
    success, image = cap.read()
    funValues = bodyProcessor(image,draw=True)
    image = funValues[0]
    poseList = funValues[1]
    area = funValues[2]
    cv2.imshow('Body Posture Detection', image)
    cv2.waitKey(1)
cap.release()
```

> handProcessor(image,draw=True)
```
from cvindrone import handProcessor
import cv2
cap = cv2.VideoCapture(0)
while True:
    success, image = cap.read()
    funValues = handProcessor(image,draw=True)
    image = funValues[0]
    handLms = funValues[1]
    cv2.imshow('Hand Gesture Controller', image)
    cv2.waitKey(1)
cap.release()
```