semvec/pypi-packages huggingface dataset:
image-processing-lib 0.22
This Python module provides utility functions for various image processing tasks, such as image conversion, display, normalization, and enhancement. It leverages the power of libraries like cv2 and numpy to handle and manipulate image data.

# Overview
This Python module provides utility functions for various image processing tasks, such as image conversion, display, normalization, and enhancement. It leverages the power of libraries like cv2 and numpy to handle and manipulate image data.

# Functions
**open_img**
- Purpose: Convert the image to a specified color space.
- Inputs: Image data (or path), desired color space, and data type specifications.
- Output: Image converted to the specified color space.

**display**
- Purpose: Display images with their labels.
- Inputs: Multiple images and labels, display size and layout specifications.
- Output: None, this displays the image.

**normalize_img**
- Purpose: Normalize an image.
- Inputs: Image data.
- Output: Normalized image.

**flatten_unflatten**
- Purpose: Flatten or reshape an image.
- Inputs: Image data, operation type (flatten or reshape), and desired shape if reshaping.
- Output: Flattened or reshaped image.

**binary**
- Purpose: Convert an image to a binary format based on a threshold.
- Inputs: Image data and threshold value.
- Output: Binarized image.

**img2blocs**
- Purpose: Split an image into blocks/blocs of a certain size.
- Inputs: Image data, block size, and padding type.
- Output: List of blocks/blocs.

**resize_img**
- Purpose: Resize an image to the specified dimensions.
- Inputs: Image data and desired dimensions (width & height).
- Output: Resized image.

**rotate_img**
- Purpose: Rotate an image by a specified angle.
- Inputs: Image data and rotation angle.
- Output: Rotated image.

**enhance_img**
- Purpose: Enhance an image by adding noise, applying blur, and adjusting contrast.
- Inputs: Image data, and specifications for noise, blur, and contrast adjustments.
- Output: Enhanced image.

# Requirements
- cv2
- numpy
- matplotlib

# Usage
In order to install the library:

```bash
pip install image-processing-lib
```

To use it, nothing is more simple:

```python
import image_processing.functions as ip

# Load an image
image = ip.open_img('PATH_TO_THE_IMAGE', 'GRAY')

# Use any of the provided functions
processed_image = FUNCTION_NAME(image, ...other_args)
```

# Contribution
Feel free to fork this module and contribute by submitting a pull request. Ensure any new features or changes are well-documented and include relevant tests.
pbstool 2.2
A simple-to-use program for quickly batch creating job tasks based on the PBS job scheduling system (including OpenPBS, PBS Pro, and TORQUE) based on a command list.
Requires Python: >=3.5

Pbstool
====
# Introduction
A simple-to-use program for quickly batch creating job tasks based on the PBS job scheduling system (including OpenPBS, PBS Pro, and TORQUE) based on a command list.

This application consists of two parts, pbstool is used to quickly create pbs job scripts, and qsubs is used to submit job scripts in batches.

# Install
----
From source code
```bash
git clone https://github.com/interestingcn/pbstool.git
cd pbstool
pip install .
```
From Pypi
```bash
pip install pbstool
```

# Usages
----
## Quick start
```shell
# Create job script
pbstool -c cmd.txt -n job_name -q cu 
# Submit them all!
qsubs
```
## pbstool: help information
```shell
Useage: pbstool  <command> [options]
Commands:
    -c / --cmd          Set job command list path.
    -n / --name         Job name prefix.
    -e / --env          If the software you are using is in a conda environment,
                        define the conda environment name here.
    -q / --queue        Target queue name.
    -- / --node         Set the number of nodes required for the job.Default 1.
    -- / --ppn          Set the number of CPU cores that can be used by each node.Default 1.
    -o / --output       Output path to generate job script.Default current path
    --walltime          Set the maximum wallclock time required for the job.Default 1000hours.
    --log_info_output   Job standard log output path.Default current path.
    --log_error_output  Job error log output path.Default current path.
    
    -s / --sample       Create a sample pbs script.
    -h / --help         Display this help message.
    -v / --version      Detailed version information.
```

## qsubs 
qsubs has no parameters. It will submit all pbs job scripts in the current path by default. You only need to execute `qsubs` under the path to be submitted.
```shell
qsubs
```

# License
----
Copyright [2023] [wangzt]

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

# About
----
Author: Wangzt (interestingcn01@gmail.com)

Bioinformatics Laboratory of South China Agricultural University
turp 0.0.2
Python package to calculate the range of cassettes needed for transurethral resection specimens
Requires Python: >=3.7

# Transurethral Resection Specimen Calculator

This package is designed to calculate the range of cassettes needed for a given specimen weight.

To install the package, use pip:

```
pip install turp
```

To use, simply instantiate a TurpCounter object with the specimen weight. 

```
turp = TurpCounter(24)

print(
    turp.weight,
    turp.num_cassette_low_end,
    turp.num_cassette_high_end,
    sep='\n'
)
```

The turp object attributes can be accessed directly or you can simply print the turp object to get the values.

```
print(turp)


TurpCounter(specimen_weight=24, num_cassette_low_end=9, num_cassette_high_end=11)
```