I have a dataset of knee bone MRI but it is in .pck format can anyone help me regarding converting it into the .jpeg format or .png
If you know what Python library was used to create or load the images that were saved as .pcks, yes.
You first need to load the pickle files as objects again using the pickle.load() method (documentation here) and then save them again using whatever library was used to make them in the first place. In the case of OpenCV, you would use the cv2.imwrite() method, for PIL it's Image.save(). If you aren't using those, just look up the documentation for whatever library you're using on saving images.
If you don't know what library was used to make the images, you'll have to see what the data you get after loading the file looks like before you can do anything else.
Related
I'm an experienced Python programmer with plenty of image manipulation and computer vision experience. I'm very familiar with all of the standard tools like PIL, Pillow, opencv, numpy, and scikit-image.
How would I go about reading an image into a Python data format like a nested list, bytearray, or similar, if I only had the standard library to work with?
I realize that different image formats have different specifications. My question is how I would even begin to build a function that reads any given format.
NOTE Python 2.6 had a jpeg module in the standard library that has since been deprecated. Let's not discuss that since it is unsupported.
If you're asking how to implement these formats "from scratch" (since the standard libraries don't do this), then a good starting point would be the format specification.
For PNG, this is https://www.w3.org/TR/2003/REC-PNG-20031110/. It defines the makeup of a PNG stream, consisting of the signature (eight bytes, 8950 4e47 0d0a 1a0a, which identifies the file as a PNG image) and a number of data chunks that contain meta data, palette information and the image itself. (It's certainly a substantial project to take on, if you really don't want to use the existing libraries, but not overly so.)
For BMP, it's a bit easier since the file already contains the uncompressed pixel data and you only need to know how to find the size and offset; some of the format definition is on Wikipedia (https://en.wikipedia.org/wiki/BMP_file_format) and here: http://www.digicamsoft.com/bmp/bmp.html
JPG is much trickier. The file doesn't store pixels, but rather "wavelets" which are transformed into the pixel map you see on the screen. To read this format, you'll need to implement this transformation function.
I am experimenting with packaging of data, and since most of my data is stored as image/graphs and other similar data; I was planning to find a more efficient way to store these images.
I did read about saving them in a DB as blob; and some others are more inclined to save them in the file system; but what I would like is to have the images to not be visible outside the application. This is essential because when I run analysis on instruments; I am not interested in showing users all the images, but only the ones related to their particular instrument.
Plus it is convenient to pack data in one single file, compared to a folder with 20-30 images in it.
I was thinking to store the images in a custom structure, a sort of a bin file, using python; unless there is something that already cover that functionality. In my search I didn't notice any specific struct to save images, while the most common solutions were either a folder in the file system or the DB approach.
If you can convert your images to raster arrays, you can store them in an HDF5 file: Add raster image to HDF5 file using h5py
I'm using py-wand to read images in Python. All I really want though is the image meta information, like size, format, color depth, etc. I don't want to load the entire image. Some of my images are extremely large and loading them this way is causing memory problems.
How can I get just the meta information?
The Magickwand method for this is MagickPingImageFile. I quickly skimmed the pywand documentation and didn't see a binding to this method, but it might be provided under another name than 'ping'. It may require a feature request.
I'm new to Python so forgive my ignorance If I don't have all the info correct. I'm trying raster through a directory and convert all the DICOM files within to TIFF files. I have gotten the search functionality to work, but I am having a hard time saving the images as TIFFs. I'm using the pydicom libraries to read in the DICOM and manipulate the header information. Also, I have tried using the save_as function in pydicom to save to TIFF, but I would rather use the save function in PIL to properly set the compression of the TIFF. I think the problem is that I can't/don't understand how to extract the actual image data from a DICOM and place it in a new image.Any Help would be greatly appreciated ... Cheers
Python 2.7
PIL 1.1.7
Pydicom 0.9.6
Found an answer online to the same query sometime back, although I don't remember the site but as I applied it to my code, sharing it here for others as well :
import pylab
import dicom
ImageFile=dicom.read_file(<SourceFilePath>) #Path to "*.dcm" file
pylab.imshow(ImageFile.pixel_array,cmap=pylab.cm.bone) #to view image
or if you want to save the image then instead use:
pylab.imsave('<DestinationFilePath>',ImageFile.pixel_array,cmap=pylab.cm.bone)
The imsave will by default save the image in .png format though. You can specify the desired format in the imsave() if it is supported.
Hope it is useful.
If you know how to use PIL to save image data as .tiff, this example should help you to pass image data from pydicom to PIL (there is more here in the comments).
Does anyone know a way get the pixel data from a PythonMagick.Image instance without having to write it to disk first?
For instance, I can read in an image using:
import PythonMagick
im = PythonMagick.Image('image.jp2')
I would now like to be able to get the uncompressed image data so that I can use it in something else like NumPy or matplotlib, but I can't seem to find any way to do this. I would just use matplotlib or PIL directly but the image format I'm reading in is JPEG 2000 which is only supported by PythonMagick as far as I know.
Any suggestions?
Disclaimer: I don't have PythonMagick built where I am right now and am no expert, so (1) any or all of the following may be wrong, (2) it will certainly be less specific than you'd like, and (3) if someone else knows better I hope they won't be put off by seeing an answer already here. Anyway:
From a quick look at the code, it looks as if you can read pixel values one by one using the pixelColor method on the Image class. This returns a PythonMagick.Color value, from which you can extract R,G,B components. The underlying C++ library supports reading out lots of pixels at a time using Image::writePixels, which is also present in PythonMagick.Image; but I think the proper use of that method depends on other things that aren't implemented in PythonMagick. That's a pity, because I bet it would have been much much more efficient than reading one pixel at a time.
Alternatively and probably better, it looks as if you can write the contents of the image to a PythonMagick.Blob object in memory, which basically does the same as writing to a file only without the file :-). You can choose what format it should write in, just as you do when writing to a file. There seems to be something called get_blob_data for extracting the contents of a Blob. Something like this:
im = PythonMagick.Image('image.jp2')
blob = PythonMagick.Blob()
im.write(blob, "png")
data = PythonMagick.get_blob_data(blob)
The resulting data is, I think, a Python string whose bytes are the binary representation of the image. (I'm assuming you're using Python 2.x, where the string type is 8-bit. I don't know whether PythonMagick works with 3.x.) I think there are some formats that are basically raw pixel data; try "RGB". You can then extract the contents via lots of struct.unpack or whatever.