I used the convert Imagemagik utility to create the grayscale jpg images. Need help in finding the equivalent utility in Python. I tried PIL but this create png images.
I thought of calling the "convert" utility through python. Is there any better solution than this.
I want to feed the images in tensorflow. The issue is I am using tensorflow 1.1.
Huh? This works fine and creates a grey JPEG:
from PIL import Image
image=Image.open('start.png')
grey=image.convert('L')
grey.save("result.jpg")
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I am trying to create a program on the Raspberry Pi Pico W that downloads a jpg image and displays a very pixilated version of the image on an addressable led matrix. I have decided to attempt to use micro python as my coding language for this project since I have already completed a similar project in the full python language. Since I am downloading the images from an online source I am stuck using the '.jpg' format at a fixed size.
I have been running into some difficulties processing the image. To run on the addressable LEDs (Neopixel) I want to collect the rgb data from each individual pixel of the .jpg and add them to a list.
Working on python I know that the PIL/Pillow library is a great solution to this problem.
from PIL import Image
image = Image.open('256256.jpg',formats=None)
print(image)
from numpy import asarray
data = asarray(image)
Unfortunately the RP2040 doesn't seem have enough storage space to handle the module.
I need to find a way to decode the image using the modules readily available to micro python.
I have attempted to reverse engineer the PIL open feature but haven't had any luck so far.
Thank you in advance!
Is there any way to convert .jpeg to .tiff file?
If yes, then how to do that?
There are many library in Python that can convert file from one format to another.
But, I have not found anything for this problem.
Thanks in advance!
see this
from PIL import Image
im = Image.open('yourImg.jpg')
im.save("pathToSave/hello.tiff", 'TIFF')
You can use PIL (Python Imaging Library) for this:
import Image
im = Image.open('test.jpg')
im.save('test.tiff') # or 'test.tif'
Also, this was the first result for your problem on Google, make sure you google extensively first.
According to OpenCV docs for functions used for image and video reading and writing imread does support JPEG files and imwrite can save TIFF files, though with some limitations:
Only 8-bit (or 16-bit unsigned (CV_16U) in case of PNG, JPEG 2000, and TIFF) single-channel or 3-channel (with ‘BGR’ channel order) images can be saved using this function.
How can i transform Image1 to Image2 using matplotlib.pyplot or another library in Python?
Image 1:
Image 2:
(This image turned out to be confidential,i removed it because i can't delete the post. Sorry for the inconvenience)
Any help is appreciated.
Have a look at the Python Imageing Library (which also has python bindings, by the way), especially the ImageFilter module.
But tools like ImageMagick or one of the built-in filters in Gimp might be more suitable for experimenting.
Is it the experimental data and already filtered from image 1 to image 2 by someone else? I wonder whether you have the point spread function along with the raw image 1?
Does anyone know of a method to make images picklable? I am trying to pass OpenCV images between processes to separate display from real-time processing of an OpenCV video. I have tried PIL Image.tostring(), but to no avail. Is there a standard technique?
This is what you are looking for: pickleable image object
Making it a dict and then using the information in the dict to recreate the image again. Hopefully this helps
OpenCV's newer cv2 module uses NumPy arrays, which are inherently pickleable. See my answer here: https://stackoverflow.com/a/17054961/1510289
I am having to do a lot of vision related work in Python lately, and I am facing a lot of difficulties switching between formats. When I read an image using Mahotas, I cannot seem to get it to cv2, though they are both using numpy.ndarray. SimpleCV can take OpenCV images easily, but getting SimpleCV image out for legacy cv or mahotas seems to be quite a task.
Some format conversion syntaxes would be really appreciated. For example, if I open a greyscale image using mahotas, it is treated to be in floating point colour space by default, as I gather. Even when I assign the type as numpy.uint8, cv2 cannot seem to recognise it as an array. I do not know how to solve this problem. I am not having much luck with colour images either. I am using Python 2.7 32bit on Ubuntu Oneiric Ocelot.
Thanks in advance!
I have never used mahotas. But I'm currently working on SimpleCV. I have just sent a pull request for making SimpleCV numpy array compatible with cv2.
So, basically,
Image.getNumpy() -> numpy.ndarray for cv2
Image.getBitmap() -> cv2.cv.iplimage
Image.getMatrix() -> cv2.cv.cvmat
To convert cv2 numpy array to SimpleCV Image object,
Image(cv2_image) -> SimpleCV.ImageClass.Image
With only experience in cv2 and SimpleCV, to convert from SimpleCV to cv2:
cv2_image = simplecv_image.getNumpyCv2()
To convert from cv2 to SimpleCV:
simplecv_image = Image(cv2_image.transpose(1, 0, 2)[:, :, ::-1])