Develop Reference

Multiple image folders joining in google colab

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.

How should python convert tiff image to jpg format without having to save to harddrive?

I'm trying to process some images and obtain numerical output. The skimage library only works with jpg format images. I only have tiff images on hand. Most converting functions work by loading a tiff image and saving it in jpg format. I do agree that the easiest way is
PIL.Image.open('pic.tiff').save('pic.jpg','jpeg')
I'm, on the other hand, trying to abstain from using hard drive for several reasons, but mainly due to the complexity file handling on heroku. Hence the question.

How to convert entire dataset of images into sketch with following python code

Below is the code by which I convert one image into a sketch. Now my question is that How I can convert entire dataset of images (88 images of CUHK Dataset) into a sketch and save it in a new directory.
image of my code

How do I prepare data (images) for py-faster-rcnn classification training?

I am trying to train my own image classificator with py-faster-rcnn link using my own images.
It looks rather simple in the example here, but they are using some ready dataset (INRIA Person). Datasets are structured and cropped to sub-images (actually data sets there are both original images and cropped people images from them) and text notation of each image with coordinates of crops. Pretty straightforward.
Still I have no idea how this is done - do they use any sort of tool for this (I can hardly imagine some test lots of data are cropped and notated manually)?
Could anyone please suggest a solution for this one? Thanks.

Python: Import multiple images from a folder and scale/combine them into one image?

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.