Requirement
I got say 100 jpg files with different dimensions one is 700*900 while another image is 1400*1800. I need to merge all this jpg files into a single pdf and they must be resized to the same dimensions.
I have tried different things programs and code but couldnt find something that resizes the image.
This might be already answered here: Create PDF from a list of images
Related
I am working on creating an image dataset in CSV format. I looked into MIST dataset, which stores pixel values in CSV files. But I am looking for a tool which can segment characters from image and save them in jpg/png format for future processing. Can anyone help me with it? I have already tried labelme, labelIMG but that only store in the format of yolo,XML etc
I am trying to work on a computer vision model but the dataset is completely new to me. It is as shown :
Dataset folders image
I have to extract each image in every folder and combine them into one train and one test folder. This is to get the filepaths of each image which I will use to decode jpeg. Can someone help me with the same ? Basically I need the filepaths of each image in one list. But the image names are also duplicate in each folder.
I have a multi-page tiff file (merged.tiff) out of which I need to extract individual images in their original format. PIL allows you to iterate through pages and writing them to disk in a format I need (png/jpg).
Ex:
from PIL import Image
img = Image.open('merged.tiff')
for i in range(img.n_frames):
try:
img.seek(i)
img.save(f'individual_{i}.jpg')
img.save(f'individual_{i}.png')
except EOFError:
break
But is there a way to know the original format of those images?
I have tried with tifffile and tiffany which allow me to convert the pages to a numpy array and then write to disk as an image, but they don't allow me to know the source format of the images contained in the TIFF file.
In the most general case, I believe this is impossible, because it is perfectly feasible to take, say, a JPEG image and include it in the TIFF file as an uncompressed RGB array.
Realistically, though, you should be able to look at some of the tags of the TIFF file, e.g. Compression, to make an educated guess about what the image used to be. Tools like tiffinfo and tiffdump (from the libtiff package) can be used to examine the TIFF file.
No matter how much I research, I still can't figure out how to do this with Mutagen; all I want to do is somehow export an audio file's (either FLAC or MP3) album artwork to a .png or .jpg file in a given directory; but I just can't figure out how to do this (the documentation does not make it clear to me at all). Preferably, it would be able to detect whether or not the image saved inside the audio file is in JPG or PNG format, and then save it appropriately based on that information (along with preserving other specification of the original file, like dimensions, color depth, etc.).
How can this be done with Mutagen? Can it be done with Mutagen?
I have a script to save between 8 and 12 images to a local folder. These images are always GIFs. I am looking for a python script to combine all the images in that one specific folder into one image. The combined 8-12 images would have to be scaled down, but I do not want to compromise the original quality(resolution) of the images either (ie. when zoomed in on the combined images, they would look as they did initially)
The only way I am able to do this currently is by copying each image to power point.
Is this possible with python (or any other language, but preferably python)?
As an input to the script, I would type in the path where only the images are stores (ie. C:\Documents and Settings\user\My Documents\My Pictures\BearImages)
EDIT: I downloaded ImageMagick and have been using it with the python api and from the command line. This simple command worked great for what I wanted: montage "*.gif" -tile x4 -geometry +1+1 -background none combine.gif
If you want to be able to zoom into the images, you do not want to scale them. You'll have to rely on the image viewer to do the scaling as they're being displayed - that's what PowerPoint is doing for you now.
The input images are GIF so they all contain a palette to describe which colors are in the image. If your images don't all have identical palettes, you'll need to convert them to 24-bit color before you combine them. This means that the output can't be another GIF; good options would be PNG or JPG depending on whether you can tolerate a bit of loss in the image quality.
You can use PIL to read the images, combine them, and write the result. You'll need to create a new image that is the size of the final result, and copy each of the smaller images into different parts of it.
You may want to outsource the image manipulation part to ImageMagick. It has a montage command that gets you 90% of the way there; just pass it some options and the names of the files in the directory.
Have a look at Python Imaging Library.
The handbook contains several examples on both opening files, combining them and saving the result.
The easiest thing to do is turn the images into numpy matrices, and then construct a new, much bigger numpy matrix to house all of them. Then convert the np matrix back into an image. Of course it'll be enormous, so you may want to downsample.