Rename script

src/resizer.py

@@ -1,50 +0,0 @@
-# Required Libraries
-import cv2
-import numpy as np
-from os import listdir
-from os.path import isfile, join
-from pathlib import Path
-import argparse
-import numpy
-
-# Argument parsing variable declared
-ap = argparse.ArgumentParser()
-
-ap.add_argument("-i", "--image",
-                required=True,
-                help="Path to folder")
- 
-args = vars(ap.parse_args())
- 
-# Find all the images in the provided images folder
-mypath = args["image"]
-onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
-images = numpy.empty(len(onlyfiles), dtype=object)
- 
-# Iterate through every image
-# and resize all the images.
-for n in range(0, len(onlyfiles)):
- 
-    path = join(mypath, onlyfiles[n])
-    images[n] = cv2.imread(join(mypath, onlyfiles[n]),
-                           cv2.IMREAD_UNCHANGED)
- 
-    # Load the image in img variable
-    img = cv2.imread(path, 1)
- 
-    # Define a resizing Scale
-    # To declare how much to resize
-    resize_scaling = 50
-    resize_width = int(img.shape[1] * resize_scaling/100)
-    resize_hieght = int(img.shape[0] * resize_scaling/100)
-    resized_dimensions = (resize_width, resize_hieght)
- 
-    # Create resized image using the calculated dimensions
-    resized_image = cv2.resize(img, resized_dimensions,
-                               interpolation=cv2.INTER_AREA)
- 
-    # Save the image in Output Folder
-    cv2.imwrite(
-      'output/' + str(resize_width) + str(resize_hieght) + str(n) + '_resized.jpg', resized_image)
- 
-print("Images resized Successfully")