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PIL, CV2: Image quality breaks after converting from PIL to Numpy

I have this image and I read as a PIL file. Then, I save it back using save method in PIL and imwrite method in cv2. Saving the image with imwrite downgrades the image quality (it becomes black and white and text can't be read).
image = Image.open("image.png")
cv2_image = numpy.asarray(image)
image.save("pil.png")
cv2.imwrite("opencv.png", cv2_image)
Here are the output files:
pil.png
opencv.png

The input image is a palette image - see here. So, you need to convert it to RGB otherwise you just pass OpenCV the palette indices but without the palette.
So, you need:
image = Image.open(...).convert('RGB')
Now make it into a Numpy array:
cv2image = np.array(image)
But that will be in RGB order, so you need to reverse the channel order:
cv2image = cv2image[..., ::-1]

How to change the background of an image using PIL?

I was trying to find how to remove/change the background of a grayscale image in Python using PIL package but I failed. What I have is an RGB image which has a white background and I would like to load it, resize, change the background from white to black and save. So far I can do the beginning:
from PIL import Image
img = Image.open('my_picture.jpg').convert('LA')
# im1 = img.crop((left, top, right, bottom))
which gives me a grayscale image of a size I want but now I do not know how to change the background. I have found a really good post using cv2 for cropping the image out from a green bg and also another setting the background directly, but I couldn't find it for PIL. Is there such an option?

Convert image into RGB and get the data. Then do follow the step.
from PIL import Image
img = Image.open("test_image.jpg")
img = img.convert("RGB")
datas = img.getdata()
new_image_data = []
for item in datas:
if item[0] in list(range(190, 256)):
new_image_data.append((255, 204, 100))
else:
new_image_data.append(item)
img.putdata(new_image_data)
img.save("test_image_altered_background.jpg")
img.show()
You can get some idea from here

Convert non-transparent image to transparent GIF image PIL

How can I convert a non-transparent PNG file into a transparent GIF file with PIL?
I need it for my turtle-graphics game. I can only seem to transparentize a PNG file, not a GIF file.

It's not obvious, to me at least, how you are supposed to do that! This may be an unnecessary work-around for a problem that doesn't exist because I don't know something about how PIL works internally.
Anyway, I messed around with it long enough using this input image:
#!/usr/bin/env python3
from PIL import Image, ImageDraw, ImageOps
# Open PNG image and ensure no alpha channel
im = Image.open('start.png').convert('RGB')
# Draw alpha layer - black square with white circle
alpha = Image.new('L', (100,100), 0)
ImageDraw.Draw(alpha).ellipse((10,10,90,90), fill=255)
# Add our lovely new alpha layer to image
im.putalpha(alpha)
# Save result as PNG and GIF
im.save('result.png')
im.save('unhappy.gif')
When I get to here, the PNG works and the GIF is "unhappy".
PNG below:
"Unhappy" GIF below:
Here is how I fixed up the GIF:
# Extract the alpha channel
alpha = im.split()[3]
# Palettize original image leaving last colour free for transparency index
im = im.convert('RGB').convert('P', palette=Image.ADAPTIVE, colors=255)
# Put 255 everywhere in image where we want transparency
im.paste(255, ImageOps.invert(alpha))
im.save('result.gif', transparency=255)
Keywords: Python, image processing, PIL, Pillow, GIF, transparency, alpha, preserve, transparent index.

How do i convert an image between PIL and cv2 without needless saving/loading (Python 3.6.3) [duplicate]

I want to convert an image loaded
TestPicture = cv2.imread("flowers.jpg")
I would like to run a PIL filter like on the example with the variable
TestPicture
but I'm unable to convert it back and forth between these types.
Is there a way to do these conversions?
Can OpenCV do all of the image filters that are in the PIL package?
Example:
Result:
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
threshold_img = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
im_pil = cv2_to_pil(threshold_img)
pytesseract.image_to_string(im_pil)
Out[5]: 'TUM'

Yes OpenCV is more robust and flexible and can perform most of the image processing routines which are available out there, So probably this filter can be done with OpenCV> However, there may not be a straightforward API for that.
Anyways, as far as the conversion of image format from OpenCV to PIL is concerned you may use Image.fromarray as:
import cv2
import numpy as np
from PIL import Image
img = cv2.imread("path/to/img.png")
# You may need to convert the color.
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
im_pil = Image.fromarray(img)
# For reversing the operation:
im_np = np.asarray(im_pil)
But you must keep in mind that, OpenCV follows BGR convention and PIL follows RGB color convention, so to keep the things consistent you may need to do use cv2.cvtColor() before conversion.

Pillow and OpenCV use different formats of images. So you can't just read an image in Pillow and manipulate it into an OpenCV image.
Pillow uses the RGB format as #ZdaR highlighted, and OpenCV uses the BGR format. So, you need a converter to convert from one format to another.
To convert from PIL image to OpenCV use:
import cv2
import numpy as np
from PIL import Image
pil_image=Image.open("demo2.jpg") # open image using PIL
# use numpy to convert the pil_image into a numpy array
numpy_image=numpy.array(pil_img)
# convert to a openCV2 image, notice the COLOR_RGB2BGR which means that
# the color is converted from RGB to BGR format
opencv_image=cv2.cvtColor(numpy_image, cv2.COLOR_RGB2BGR)
To convert from OpenCV image to PIL image use:
import cv2
import numpy as np
from PIL import Image
opencv_image=cv2.imread("demo2.jpg") # open image using openCV2
# convert from openCV2 to PIL. Notice the COLOR_BGR2RGB which means that
# the color is converted from BGR to RGB
color_converted = cv2.cvtColor(opencv_image, cv2.COLOR_BGR2RGB)
pil_image=Image.fromarray(color_converted)

Here are two functions to convert image between PIL and OpenCV:
def toImgOpenCV(imgPIL): # Conver imgPIL to imgOpenCV
i = np.array(imgPIL) # After mapping from PIL to numpy : [R,G,B,A]
# numpy Image Channel system: [B,G,R,A]
red = i[:,:,0].copy(); i[:,:,0] = i[:,:,2].copy(); i[:,:,2] = red;
return i;
def toImgPIL(imgOpenCV): return Image.fromarray(cv2.cvtColor(imgOpenCV, cv2.COLOR_BGR2RGB));
Convert from OpenCV img to PIL img will lost transparent channel. While convert PIL img to OpenCV img will able to keep transparent channel, although cv2.imshow not display it but save as png will gave result normally.

PNG won't autocrop using image.getbbox()

I've been trying to get thisimage to automatically crop to the smallest size possible, removing the transparent bits around it. I can't just crop this image myself manually, as more things will be added on the image like this .
I've been using this code:
from PIL import Image, ImageChops
image=Image.open('headbase1.png')
image.load()
imageSize = image.size
imageBox = image.getbbox()
print(image.getbbox())
cropped=image.crop(imageBox)
cropped.save('headbase_end.png')
It does not crop out the transparency around it, and the bounding box is this (0, 0, 45, 45), which I do not think is right.
Thanks, VOT.
Edit, this does work: Automatically cropping an image with python/PIL with that image, however it refuses to work for my image. .

getbbox doesn't work on PNGs with alpha channels: image.mode == 'RGBA'
First remove the alpha channel and then obtain the bounding box. image.convert('RGB').getbbox()