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How to apply color balance from one image to another

I've got two images, the first one contain multiple items, which shows true colors. Then when I removed most of the item, then the webcam tried to auto-balance the image and yielded really false color.
Is there a way (in code) to apply the color profile of the first (true-color) image to the second image?
(or point me to some keywords, I'm new to the field, thanks)
Attached them here for easy comparison
True color
Falsely-adjusted color
I used Logitech webcam, which I can't figure out how to turn off auto-balance in code (in Linux).

I use this method and it works very well:
#pip install color_transfer
from color_transfer import color_transfer
# Load the two images
img1 = cv2.imread('image12.png')
img2 = cv2.imread('image1.png')
# Apply the color transfer
img2_transferred = color_transfer(img1, img2)
cv2.imshow("image", img2_transferred)
if cv2.waitKey(0) == chr("q"):
exit(0)

OpenCV imread transparency gone

I have an image (a captcha) that I download from the web.
When I loaded to opencv it seems to loose its properties or simply mixes the transparent background with the dark/black colors:
Currently the code does nothing but loading a writing again:
captchaImg = cv2.imread('captcha1.png')
cv2.imwrite("captcha2.png", captchaImg)
I have tried loading also with options 0, 1, 2, 3 but the result is the same.

Using the provided constants might help. I do the equivalent of
captchaImg = cv2.imread('captcha1.png', cv2.IMREAD_UNCHANGED)
which reads the alpha channel (if there is one). The REPL says that cv2.IMREAD_UNCHANGED is -1

Well this is a problem with opencv and it has a solution with opencv but it is kind of complex so I went on and use another libary (PIL) that I was going to use any way.
Basically what you do is put a white image behind the transparent one an with that you solve the problem.
The code is the following:
image = Image.open("captcha1.png")
image.convert("RGBA")
canvas = Image.new('RGBA', image.size, (255,255,255,255)) # Empty canvas colour (r,g,b,a)
canvas.paste(image, mask=image) # Paste the image onto the canvas, using it's alpha channel as mask
canvas.save("captcha1.png", format="PNG")
I hope it helps someone with the same problem.

How do I convert an RGB picture into graysacle using simplecv?

So working with windows, python 2.7 and simplecv I am making a live video with my webcam and want simplecv to give me a grayscale version of the video. Is there any simple way to achieve that?
I found the command
grayscale()
on the opencv page, which should do exactly that but when I run it I get the error:
NameError: name "grayscale" is not defined
I am currently using this prewritten code for object tracking but I don't know whether I should use the command I found, and where in the code I should put it, does anybody have an idea? :
print __doc__
import SimpleCV
display = SimpleCV.Display()
cam = SimpleCV.Camera()
normaldisplay = True
while display.isNotDone():
if display.mouseRight:
normaldisplay = not(normaldisplay)
print "Display Mode:", "Normal" if normaldisplay else "Segmented"
img = cam.getImage().flipHorizontal()
dist = img.colorDistance(SimpleCV.Color.BLACK).dilate(2)
segmented = dist.stretch(200,255)
blobs = segmented.findBlobs()
if blobs:
circles = blobs.filter([b.isCircle(0.2) for b in blobs])
if circles:
img.drawCircle((circles[-1].x, circles[-1].y), circles[-1].radius(),SimpleCV.Color.BLUE,3)
if normaldisplay:
img.show()
else:
segmented.show()

There are multiple ways to do this in SimpleCV.
One way has been already described, it's the toGray() method.
There's also a way you can do this with gaussian blur, which also helps to remove image noise:
from SimpleCV import *
img = Image("simplecv")
img.applyGaussianFilter(grayscale=True)
After the third line, img object contains the image with a lot less high-frequency noise, and converted to grayscale.
You may check out pyimagesearch.com who works with OpenCV, but he explains why applying Gaussian Blur is a good idea.

In simple cv theres a function called toGray() for example:
import SimpleCV as sv
img = img.jpg
sv.img.jpg.toGray()
return gimg.jpg

white border while displaying a full image with python and opencv

This question is related with this one:
how to display a full screen images with python2.7 and opencv2.4
I want to display a black image full screen, i have created even a black image with the same resolution of the screen.
But i get a little white stripe on top and on the left of the screen.
I don't know if it is a problem of my screen that is not aligned or its my code. I have tried in 2 displays and the white stripe is displayed.
So if you run this code below, do you get a full black image?
import numpy as np
import cv2
if __name__ == "__main__":
img = cv2.imread('nero.jpg')
cv2.namedWindow("test", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("test", cv2.WND_PROP_FULLSCREEN, cv2.cv.CV_WINDOW_FULLSCREEN)
cv2.imshow("test",img)
cv2.waitKey(0)
cv2.destroyAllWindows()
EDIT :
This method is not working for me. do you know anther way or libraries to display a full screen image?
EDIT 2: still unsolved, i am starting to think that it is an openCv bug

I have the same problem, there is a white stripe of 1 pixel on the left and on the top side of the window. Tested it with multiple monitors. OpenCV version 3.4.2
But there is a workaround which works perfectly fine in my case (see also https://gist.github.com/goraj/a2916da98806e30423d27671cfee21b6). Here's the code:
import cv2
import win32api
import win32gui
cv2.namedWindow("fullScreen", cv2.WINDOW_FREERATIO)
cv2.setWindowProperty("fullScreen",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
hwndMain = win32gui.FindWindow(None, "fullScreen")
rgb = win32gui.CreateSolidBrush(win32api.RGB(0, 0, 0))
GCLP_HBRBACKGROUND = -10
win32api.SetClassLong(hwndMain, GCLP_HBRBACKGROUND, rgb)

Yes I do.
img = np.zeros((900, 1600)) #my aspect ratio is 16x9
cv2.namedWindow("test", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("test", cv2.WND_PROP_FULLSCREEN, cv2.cv.CV_WINDOW_FULLSCREEN)
cv2.imshow("test",img)
cv2.waitKey(0)
gives me a fully black screen. Are you sure you are using the right aspect ratio?

PIL Image mode "P" -> "RGBA"

This is my issue:
import Image
im = Image.open("1.png")
im.show()
print im.mode
im.convert("RGBA").save("2.png")
Well, with my image you can see the difference.
My question is: how do I convert it properly?
Image:
Result:
NOTE: The original image has a semi-transparent glow, the result has a solid green "glow"

This issue was reported here:
https://bitbucket.org/effbot/pil-2009-raclette/issue/8/corrupting-images-in-palette-mode
In March 2012, a comment says it's now fixed in development version of PIL. The most recent released version is 1.1.7, so the fix won't be available until 1.2 comes out. PIL updates very slowly, so don't expect this to come out soon.

Unfortunately your PNG image is a type that PIL doesn't handle very well - a paletted image with an alpha channel. When you open the image, the alpha is thrown away and there's no way to get it back.
This is different from the usual palette transparency where one index of the palette is used to denote fully transparent pixels.

You could use scipy.misc.imread:
img = scipy.misc.imread(filename, mode='RGBA')
img = Image.fromarray(img)

Your problem is that you do not provide info about what PIL should use as source of ALPHA channel.
PIL will not on its own add transparency to your image.
What part of your image you want to be transparent?