Develop Reference

Saving image list in a dir

X_image_train = []
for fname in os.listdir(images_dir):
fpath = os.path.join(images_dir, fname)
im = Image.open(fpath)
im_resized = im.resize(dim)
X_image_train.append(im_resized)
I want to save the above X_image_train list as dir in my laptop. How can I do that?

If you are using Image objects from the PIL package, simply use im.save('folder/path', 'JPEG') in your foor loop

Converting directory with images to csv file in python

Im trying to copy the pixel information of a group of images to a CSV, however when I try the following code, Im unable to create the csv. Is there any other way to copy the pixels to a csv?
from PIL import Image
import numpy as np
import sys
import os
import csv
# default format can be changed as needed
def createFileList(myDir, format='.png'):
fileList = []
print(myDir)
for root, dirs, files in os.walk(myDir, topdown=False):
for name in files:
if name.endswith(format):
fullName = os.path.join(root, name)
fileList.append(fullName)
return fileList
# load the original image
myFileList = createFileList('/test/surprise')
for file in myFileList:
print(file)
img_file = Image.open(file)
# img_file.show()
# get original image parameters...
width, height = img_file.size
format = img_file.format
mode = img_file.mode
# Make image Greyscale
img_grey = img_file.convert('L')
#img_grey.save('result.png')
#img_grey.show()
# Save Greyscale values
value = np.asarray(img_grey.getdata(), dtype=np.int).reshape((img_grey.size[1], img_grey.size[0]))
value = value.flatten()
print(value)
with open("imagenes.csv", 'a') as f:
writer = csv.writer(f)
writer.writerow(value)
I would like to generate a csv with the pixel information similar to FER2013.csv as can be see in the following image.

How to save images with the same name to the different direction using PIL and os.path?

While trying to split the path to get a name, I get the traceback:
TypeError: expected str, bytes or os.PathLike object, not JpegImageFile . How can I solve it or is there other methods?
I try to save resized images with the same name to a different direction. For this reason, I use os.path.split() functions.
import glob
from PIL import Image
import os
images = glob.glob("/Users/marialavrovskaa/Desktop/6_1/*")
path = "/Users/marialavrovskaa/Desktop/2.2/"
quality_val=95
for image in images:
image = Image.open(image)
image.thumbnail((640, 428), Image.ANTIALIAS)
image_path_and_name = os.path.split(image)
image_name_and_ext = os.path.splitext(image[0])
name = image_name_and_ext[0] + '.png'
name = os.path.splitext(image)[0] + '.png'
file_path = os.path.join(path, name)
image.save(file_path, quality=quality_val)

import glob
from PIL import Image
import os
images = glob.glob("Source_path")
path = r"Destination_path"
quality_val=95
for image in images:
img = Image.open(image)
img.thumbnail((640, 428), Image.ANTIALIAS)
name = os.path.split(image)
file_path = os.path.join(path, name[1])
img.save(file_path, quality=quality_val)
The primary problem with your code was that you were using a variable and an object under the same name image. Which was causing problems.
LOGICAL ERRORS:-
image_path_and_name is a needless variable in the code, as it is
used for nothing.
name has been initialized with totally different values twice,
instead use name = os.path.split(image) which serves the purpose
of both.
you should not try to explicitly define the extension of each image
as .png as it might create issues when dealing with other image
formats.

for image in images:
image = Image.open(image)
image.thumbnail((640, 428), Image.ANTIALIAS)
image_path_and_name = os.path.split(image)
When you say image = Image.open(image), you're overwriting the loop variable also named image, and it's no longer a splittable string.
Change one of the image variables to a different name.

firstly,
image_name_and_ext = os.path.splitext(image[0])
should be
image_name_and_ext = os.path.splitext(image_path_and_name[1])
because image is string so image[0] just get first character of image not useless in this case
secondly,
name = os.path.splitext(image)[0] + '.png' equal image
name = os.path.splitext(image)[0] should return path of image not include extention
to solve this problem, you can try:
for image in images:
img = Image.open(image)
img.thumbnail((640, 428), Image.ANTIALIAS)
name = os.path.split(image)
file_path = os.path.join(path, name[1])
image.save(file_path, quality=quality_val)

By the code above you will get image in thumbnails I recommend to use resize function because from resize you can maintain you aspect ratio that helps you in getting better results.
image.thumbnail((640, 428), Image.ANTIALIAS)
this line of code is converting your thumbnail.which is not good approach of resizing. Try the code below.
import os
from PIL import Image
PATH = "F:\\FYP DATASET\\images\\outliers Dataset\\Not Outliers\\"
Copy_to_path="F:\\FYP DATASET\\images\\outliers Dataset\\"
for filename in os.listdir(PATH):
img = Image.open(os.path.join(PATH, filename)) # images are color images
img = img.resize((224,224), Image.ANTIALIAS)
img.save(Copy_to_path+filename+'.jpeg')
In this code you are taking images directly from folder resize them and saving them to other location with same name. All the images are processing one by one So you need not worry to load all the images at once into the memory.

Take an image directory and resize all images in the directory

I am trying to convert high resolution images to something more manageable for machine learning. Currently I have the code to resize the images to what ever height and width I want however I have to do one image at a time which isn't bad when I'm only doing a 12-24 images but soon I want to scale up to do a few hundred images.
I am trying to read in a directory rather than individual images and save the new images in a new directory. Initial images will vary from .jpg, .png, .tif, etc. but I would like to make all the output images as .png like I have in my code.
import os
from PIL import Image
filename = "filename.jpg"
size = 250, 250
file_parts = os.path.splitext(filename)
outfile = file_parts[0] + '_250x250' + file_parts[1]
try:
img = Image.open(filename)
img = img.resize(size, Image.ANTIALIAS)
img.save(outfile, 'PNG')
except IOError as e:
print("An exception occured '%s'" %e)
Any help with this problem is appreciated.

Assuming the solution you are looking for is to handle multiple images at the same time - here is a solution. See here for more info.
from multiprocessing import Pool
def handle_image(image_file):
print(image_file)
#TODO implement the image manipulation here
if __name__ == '__main__':
p = Pool(5) # 5 as an example
# assuming you know how to prepare image file list
print(p.map(handle_image, ['a.jpg', 'b.jpg', 'c.png']))

You can use this:
#!/usr/bin/python
from PIL import Image
import os, sys
path = "\\path\\to\\files\\"
dirs = os.listdir( path )
def resize():
for item in dirs:
if os.path.isfile(path+item):
im = Image.open(path+item)
f, e = os.path.splitext(path+item)
imResize = im.resize((200,100), Image.ANTIALIAS)
imResize.save(f+'.png', 'png', quality=80)
resize()

You can loop over the contents of a directory with
import os
for root, subdirs, files in os.walk(MY_DIRECTORY):
for f in files:
if f.endswith('png'):
#do something

You can run through all the images inside the directory using glob. And then resize the images with opencv as follows or as you have done with PIL.
import glob
import cv2
import numpy as np
IMG_DIR='home/xx/imgs'
def read_images(directory):
for img in glob.glob(directory+"/*.png"):
image = cv2.imread(img)
resized_img = cv2.resize(image/255.0 , (250 , 250))
yield resized_img
resized_imgs = np.array(list(read_images(IMG_DIR)))

I used:
from PIL import Image
import os, sys
path = os.path.dirname(os.path.abspath(__file__))
dirs = os.listdir( path )
final_size = 244
print(dirs)
def resize_aspect_fit():
for item in dirs:
if ".PNG" in item:
print(item)
im = Image.open(path+"\\"+item)
f, e = os.path.splitext(path+"\\"+item)
size = im.size
print(size)
ratio = float(final_size) / max(size)
new_image_size = tuple([int(x*ratio) for x in size])
im = im.resize(new_image_size, Image.ANTIALIAS)
new_im = Image.new("RGB", (final_size, final_size))
new_im.paste(im, ((final_size-new_image_size[0])//2, (final_size-new_image_size[1])//2))
print(f)
new_im.save(f + 'resized.jpg', 'JPEG', quality=400)# png
resize_aspect_fit()

You can use this code to resize multiple images and save them after conversion in the same folder for let's say dimensions of (200,200):
import os
from PIL import Image
f = r' ' #Enter the location of your Image Folder
new_d = 200
for file in os.listdir(f):
f_img = f+'/'+file
try:
img = Image.open(f_img)
img = img.resize((new_d, new_d))
img.save(f_img)
except IOError:
pass

you can try to use the PIL library to resize images in python
import PIL
import os
import os.path
from PIL import Image
path = r'your images path here'
for file in os.listdir(path):
f_img = path+"/"+file
img = Image.open(f_img)
img = img.resize((100, 100)) #(width, height)
img.save(f_img)

from PIL import Image
import os
images_dir_path=' '
def image_rescaling(path):
for img in os.listdir(path):
img_dir=os.path.join(path,img)
img = Image.open(img_dir)
img = img.resize((224, 224))
img.save(img_dir)
image_rescaling(images_dir_path)

Resize multiple images in a folder (Python)

I already saw the examples suggested but some of them don't work.
So, I have this code which seems to work fine for one image:
im = Image.open('C:\\Users\\User\\Desktop\\Images\\2.jpg') # image extension *.png,*.jpg
new_width = 1200
new_height = 750
im = im.resize((new_width, new_height), Image.ANTIALIAS)
im.save('C:\\Users\\User\\Desktop\\resized.tif') # .jpg is deprecated and raise error....
How can I iterate it and resize more than one image ? Aspect ration need to be maintained.
Thank you

# Resize all images in a directory to half the size.
#
# Save on a new file with the same name but with "small_" prefix
# on high quality jpeg format.
#
# If the script is in /images/ and the files are in /images/2012-1-1-pics
# call with: python resize.py 2012-1-1-pics
import Image
import os
import sys
directory = sys.argv[1]
for file_name in os.listdir(directory):
print("Processing %s" % file_name)
image = Image.open(os.path.join(directory, file_name))
x,y = image.size
new_dimensions = (x/2, y/2) #dimension set here
output = image.resize(new_dimensions, Image.ANTIALIAS)
output_file_name = os.path.join(directory, "small_" + file_name)
output.save(output_file_name, "JPEG", quality = 95)
print("All done")
Where it says
new_dimensions = (x/2, y/2)
You can set any dimension value you want
for example, if you want 300x300, then change the code like the code line below
new_dimensions = (300, 300)

I assume that you want to iterate over images in a specific folder.
You can do this:
import os
from datetime import datetime
for image_file_name in os.listdir('C:\\Users\\User\\Desktop\\Images\\'):
if image_file_name.endswith(".tif"):
now = datetime.now().strftime('%Y%m%d-%H%M%S-%f')
im = Image.open('C:\\Users\\User\\Desktop\\Images\\'+image_file_name)
new_width = 1282
new_height = 797
im = im.resize((new_width, new_height), Image.ANTIALIAS)
im.save('C:\\Users\\User\\Desktop\\test_resize\\resized' + now + '.tif')
datetime.now() is just added to make the image names unique. It is just a hack that came to my mind first. You can do something else. This is needed in order not to override each other.

I assume that you have a list of images in some folder and you to resize all of them
from PIL import Image
import os
source_folder = 'path/to/where/your/images/are/located/'
destination_folder = 'path/to/where/you/want/to/save/your/images/after/resizing/'
directory = os.listdir(source_folder)
for item in directory:
img = Image.open(source_folder + item)
imgResize = img.resize((new_image_width, new_image_height), Image.ANTIALIAS)
imgResize.save(destination_folder + item[:-4] +'.tif', quality = 90)