Develop Reference

Load Images in Runtime

I'm using opencv and face recognition model to detect and Identify the face in webcam.
I saw that all Images in folder are encoded once then search faces .. but if I add the image in runtime it'll not pick up that image
can anyone help , how to load images in runtime if Images are not found in particular folder
Thanks,
Chiranjit

OpenCV: Stitch with saving warping/arrangement informations and re-stitch with the saved info

First of all, I am a beginner in computer vision field, learning OpenCV from the web.
What I am trying is stitching multispectral (bands > 3) images with OpenCV stitching APIs.
I already know that OpenCV doesn't support multispectral image.
So, the idea I came up with is as follows:
Extract the RGB images from each multispectral image.
Use cv2.Stitcher_create() and stitcher.stitch class to stitch all the RGB images (reference: https://pyimagesearch.com/2018/12/17/image-stitching-with-opencv-and-python/). And save the warping and arrangement informations (ex. Homography, matching keypoints...) in making RGB panorama.
Stitch each remaining bands' image by loading the informations that saved in step 2.
The problem is, I can't find the codes for the saving and loading informations that required in step 2 and 3.
Is the suggested method possible? And if possible, is there any tips or references that I can use?

Yes you can do it (I did it before for my paper on stitching construction plans). You need to save the camera parameters after the feature matching and probably also the seam masks.
Look here (cameras) and here (seam masks)

python: when reading and saving a image the color change

I tried loading and saving images with python using cv2,PIL, scipy , but the saved image has a bit different color compare to the original.
I am loading and saving tif format, so i expect no color change.
link to the image I am using:
https://data.csail.mit.edu/graphics/fivek/img/tiff16_c/a0486-jmac_MG_0791.tif
the difference between loaded image and saved image is:
can you help me understand what I am doing wrong? why the color change?
update:
the problem is because the image is prophoto rgb color.
does anyone knows how can i convert a batch of images from prophoto rgb to rgb?
thanks,
yoav
option 1:
img = imread(file_name)
imsave('imread.tif', img)
option 2:
img = cv2.imread(file_name)
cv2.imwrite('cv2.tif', img)
option 3:
img = Image.open(file_name)
img.save('pil.tif')

I think OpenCV is more interested in Computer Vision - i.e. detecting and measuring objects etc than printing or high quality image reproduction, editing and printing, so it pretty much ignores ICC profiles. If anyone knows better, I am happy to be corrected.
You can use ImageMagick to convert images from one format to another, and to do many, many other things, one of which is changing colour profiles. So, I think, if you go to this website and download an sRGB profile (I chose the first one with "preference" in its name) and save it as sRGB.icc, you can change one of your ProPhoto images to a normal sRGB image with the following command in Terminal:
convert input.tif -profile sRGB.icc output.tiff
Try that and see if it works. If so, make a copy of your images and on a copy, you can run mogrify to do the whole lot in one go - beware and make a copy like I suggest because it will very quickly alter all your images...
magick mogrify -profile sRGB.icc *tif
You can see the embedded profile and loads of other information about an image using ImageMagick's identify command:
magick identify -verbose OneOfYourImages.tiff

Tiling of large numer of images using database

I have coordinates in a numpy array of all the images which needs to be joined. I have used OpenCV to find the coordinates using normalized cross-correlation. I am having a problem in tiling those images as it is very large 300X300 images of resolution 640X480 pixels. For now, I am using pyvips to merge all this image to form a high-resolution image, but it is talking around 20GB RAM.
Is there any method to bring it down to <4GB? Is there any database to store all the images and display the tiled images?
I will do all the preprocessing steps before using a database. I just need a high-resolution tiled image using images and coordinates without utilizing much RAM. Even I can make those images in a grid which can be joined directly without coordinates. Please suggest a way to achieve this.

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.