semvec/pypi-packages huggingface dataset:
media-preprocessor 10.0
tool for preprocessing media
License: MIT
Keywords: image,preprocessing,reshape,resize,background

Overview:
The objective of this package, as the name suggest, is to act as a media pre-processing tool. It simplifies the process of importing media to the python environment.
It takes input from the user in the form of images or video capture and lets the user define certain parameters, pertaining to which the function gives the output. The package primarily consists of two functions:
1.	img_pre()
2.	nbg_vc()
Functions:
1.	img_pre(location, shape, edges)

This function takes input from the user in the form of images and performs pre-processing operations on it like reshape, resize (1:1 ratio) and standardize. It also gives the users an option to remove the background from the images and retain only the edges of the subject of the image. 

Parameters:
•	location (string)
input folder path of where the images are stored

•	shape (integer)
input desired shape of image

•	edges (boolean)
False: original pictures after pre-processing
True: output images have edges of the subject without the background
2.	nbg_vc(shape)
It allows the user to capture video using their webcam and removes the background by only capturing objects that move in the frame.

Parameters: 
shape (integer): defines shape of the desired output image.
PixelP 0.5
Image augmeantation and preprocessing tool
License: MIT
Keywords: Image,Augment,Reshape,Color,Gray

Overview: PixelP (PixelProcessor) is an image augmentation and preprocessing package.This tool has 3 functions idg,create_gray_data and create_color_data

1.idg():Augments new images
	Arguements : Data_path - Path to source folder
		      CATEGORIES - Name of folders inside parent source folder
		      Data_out - Path to output folder
		      rotrange - Rotation range varying from 0-360
		      wshift - Width shift 0-1
		      hshift - Height shift 0-1
		      srange - Shear Range 0-1
		      zoom - Zoom Range 0.1
		      hflip - horizontal flip TRUE or FALSE
		      fill - Fill Mode 'wrap','nearest','constant','reflect'

2. create_gray_data():Turns image to grayscale and reshapes to user defined size
	Arguements : IMG_SIZE - no. of pixels (pixel x pixel)
		     training_data - empty list []
		     Data_train - Path to images
		     CATEGORIES - Name of folders inside parent source folder

3. create_color_data():reshapes to user defined size
	Arguements : IMG_SIZE - no. of pixels (pixel x pixel)
		     training_data - empty list []
		     Data_train - Path to images
		     CATEGORIES - Name of folders inside parent source folder