I'm looking to be able to read in pixel values as captured in a raw NEF image, process the data for noise removal, and then save the new values back into the raw image format maintaining all the metadata for later use. I've seen dcraw can read in raw format and output the Bayer pattern data as a tiff or other image but I can't save it back to my NEF. I've also been attempting to read in and save the image with simple python file open or numpy memmap but have no clue how to handle the binary data. Any help would be appreciated. Thanks!
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Interested in getting the raw data that is streamed from a webcam..before it is transformed into binary -> pixels or whatever the sequence is.
From my understanding, libraries like opencv won't help with this.
Edit: kiss
in order to see the image output from a webcam using python you need to convert it from raw image data (the pixels) into a image that can be displayed one way you can do it is by using matplotlib more info here https://matplotlib.org/stable/tutorials/introductory/images.html
this will display the image but will not convert it into other image formats such as .png .jpeg ext. but the data you are getting is probably pixel data which is the rawest image data you will get
I have a BMP image and I want to extract a small portion of it and save it as a new BMP image file.
I was able to load image and read it however I was not able to extract the small portion of BMP image as I am new to manipulating BMP image with python and also it not same as reading text file.
Things I have to do is
load image.
extract small portion of image.
eg. I have to extract 40X40 pixel image from 900X900 image file
then save extracted image as new file. eg new.bmp
I am trying to do this for last 3 days also I have searched a lot in the net but got solution which uses Pillow library however I need it to do this without using any external module of Python. Stackoverflow is my last hope I need some guidance from a expert people present here, please provide my some guidance.
I am trying to read image.jpg (RGB) into an array in python without any additional module but it doesn't work?
pic = open('image.jpg')
array=[]
with open(p, 'rb') as inf:
jpgdata = inf.read()
values=jpgdata.split()
array=array.append(values[:][:])
print (array)
Can anyone help me how to read an image 3 bands (RGB) in python without using external module?
A JPEG image is not just a series of pixels, unlike some other formats like BMP.
In order to get the pixel data from a JPEG image you need to decompress it, which involves reading its header data, then rebuilding the data from 8x8px blocks which contain information regarding the brightness and color (YCbCr).
You need to:
Build the Huffman tree and revert the blocks
Invert the discrete cosine transform with the given parameters
Revert the YCbCr into RGB
Place each block into its corresponding location in the image
Building a simple decoder from scratch is certainly possible, but it's not going to be done in a few lines.
I know that ghostscript can convert pdf to tiff and even has python bindings but I'm wondering whether there is a way to avoid writing the resulting tiff to disk (-SOutputFile=/path/to/file.tiff. Rather I want to keep the resulting tiff in memory and use it as a PIL image.
Basically, no, not using the standard devices. That's because the strip size of the TIFF file (and potentially other entries in the TIFF header) can't be written until after the compressed bitmap has been created because the sizes aren't known. So you need to be able to seek back to the beginning and update the header.
Now you could modify the standard TIFF output devices so that they maintain the output in memory, rather than writing to disk, but that's not how they currently work.
Is it possible to use the Python wrappers for GDCM to decode the image data in a DICOM file?
I have a byte array / string with the bytes of the image data in a DICOM file (i.e. the contents of tag 7fe0,0010 ("Pixel Data")) and I want to decode the image to something raw RGB or greyscale.
I am thinking of something along the lines of this but working with just the image data and not a path to the actual DICOM file itself.
You can read the examples, there is one that shows how one can take an input compressed DICOM and convert it to an uncompressed one. See the code online here:
Decompress Image
If you are a big fan of NumPy, checkout:
This module add support for converting a gdcm.Image to a numpy array.
This is sort of a low level example, which shows how to retrieve that actual raw buffer of the image.
A much nicer class for handling Transfer Syntax conversion would be to use gdcm.ImageChangeTransferSyntax class (allow decompression of icon)
gdcm::ImageChangeTransferSyntax Class Reference
If you do not mind reading a little C++, you can trivially convert the following code from C++ to Python:
Compress Image
Pay attention that this example is actually compressing the image rather than decompressing it.
Finally if you really only have access to the data values contains in the Pixel Data attribute, then you should really have a look at (C# syntax should be close to Python syntax):
Decompress JPEG File
This example shows how one can decompress a JPEG Lossless, Nonhierarchical, First- Order Prediction file. The JPEG data is read from file but it should work if the data is already in memory for your case.