semvec/pypi-packages huggingface dataset:
cython-bbox-nguyenchien 0.1.3
Standalone cython_bbox
Keywords: cython_bbox_nguyenchien

# cython_bbox

cython_bbox is widely used in object detection tasks. To my best knowledge, it was first implemented in [Faster-RCNN](https://github.com/rbgirshick/py-faster-rcnn). Since then, almost all object detection projects use the source code directly.

In order to use it in standalone code snippets or small projects, I make it a pypi module. The `cython_bbox.pyx` is totally borrowed from [Faster-RCNN](https://github.com/rbgirshick/py-faster-rcnn). Thanks [RBG](http://www.rossgirshick.info/)!

## install

```
pip install cython_bbox
```

## usage


```
from cython_bbox import bbox_overlaps
overlaps = bbox_overlaps(
        np.ascontiguousarray(dt, dtype=np.float32),
        np.ascontiguousarray(gt, dtype=np.float32)
    )

```
scanfs 0.0.6
File system scanner in Python

# scanfs

This module scans the filesystem and provides custom hooks to handle each file
type of your choice.

## Installation

```bash
pip install scanfs
```

## Example

### How to write your own scanner enhancements?

This example scans the `/usr/bin` folder for ELF files and handles the callback
to provide file stat info.

```python
import os
from scanfs.fsscanner import FileSystemScanner
from scanfs.fsscannerex import FSScannerException


def callback(fpath, node):
    try:
        path = os.path.join(fpath, node.name)
        # Now do what you want on the instance of file
        # eg. stat
        statinfo = os.stat(path)
        print(statinfo)
    except FSScannerException as e:
        print("An exception occurred: " + str(e))


fss = FileSystemScanner("/usr/bin")
fss.scan_for_elfs(callback)
```

### Simple way to scan ELF files for binary protection check using `checksec` utility

> `checksec` utility can be downloaded [here](https://github.com/slimm609/checksec.sh)

```python
import os
import subprocess
from scanfs.fsscanner import FileSystemScanner
from scanfs.scanners.checksecscanner import CheckSecScanner

css = CheckSecScanner("/usr/bin", "/tmp/checksec_results.json")
css.checksec_on_elfs()

css = CheckSecScanner("/usr/bin", "/tmp/checksec_results.csv", fformat="csv")
css.checksec_on_elfs()
```

## Developer

```bash
python -m build
twine upload dist/*
```

> Ref: https://packaging.python.org/tutorials/packaging-projects/
pypownetr 0.1.0
Chowdhury et al. PowNet Refactored
Requires Python: >=3.6

# PowNet Refactored

![license MIT](https://img.shields.io/github/license/kamal0013/PowNet) 



# PyPowNet: A Python Library for PowNet Model Optimization

[PowNet](https://github.com/kamal0013/PowNet/) is a least-cost optimization model for simulating the Unit Commitment and Economic Dispatch of large-scale power systems.

It has been applied to model Cambodian, Laotian, and Thai power systems.

PyPowNetR improves the original implementation of PowNet and simplifies the model specification process.

It aims to help researchers to import their own power system data on the PowNet model and and serve as a benchmark for optimization solvers.

Ultimately, we hope that our effort will encourage more regions to adopt renewable energy sources in the power system.



# Requirements

PyPowNetR is written in Python 3.6. It requires the following Python packages: (i) Pyomo, (ii) NumPy, and (iii) Pandas. It also requires an optimization solver (e.g. CPLEX). 

PyPowNetR has been tested in Anaconda on Windows 10.



# How to run

If you have installed [glpk], this will execute the model using the data on Cambodian power system.

The script also generates .csv files containing the values of each decision variable.



# Citation

If you use PyPowNetR for your research, please cite the following papers (mainly from the original authors), which can be found in [this document](README_LONG.md)



# License

PyPowNetR is released under the MIT license.
vve23 2.0.10
aownierewe
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

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