Given a HAADF-STEM Spectrum Image (SI) as .emd (Velox) file, I want to extract all individual HAADF-images from the stack.
I assume there is an easy way with hyperspy, but I am unable to identify it.
My code so far:
import hyperspy.api as hs
path = r'C:\Users\SI_File.emd'
s = hs.load(path)
Related
I have a problem and don't know how to solve:
I'm learning how to analyze DICOM files with Python and, so,
I got a patient exam, on single patient and one single exam, which is 200 DICOM files all of the size 512x512 each archive representing a different layer of him and I want to turn them into a single archive .npy so I can use in another tutorial that I found online.
Many tutorials try to convert them to jpg or png using opencv first, but I don't want this since I'm not interested in a friendly image to see right now, I need the array. Also, this step screw all the quality of images.
I already know that using:
medical_image = pydicom.read_file(file_path)
image = medical_image.pixel_array
I can grab the path, turn 1 slice in a pixel array and them use it, but the thing is, it doesn't work in a for loop.
The for loop I tried was basically this:
image = [] # to create an empty list
for f in glob.iglob('file_path'):
img = pydicom.dcmread(f)
image.append(img)
It results in a list with all the files. Until here it goes well, but it seems it's not the right way, because I can use the list and can't find the supposed next steps anywhere, not even answers to the errors that I get in this part, (so I concluded it was wrong)
The following code snippet allows to read DICOM files from a folder dir_path and to store them into a list. Actually, the list does not consist of the raw DICOM files, but is filled with NumPy arrays of Hounsfield units (by using the apply_modality_lut function).
import os
from pathlib import Path
import pydicom
from pydicom.pixel_data_handlers import apply_modality_lut
dir_path = r"path\to\dicom\files"
dicom_set = []
for root, _, filenames in os.walk(dir_path):
for filename in filenames:
dcm_path = Path(root, filename)
if dcm_path.suffix == ".dcm":
try:
dicom = pydicom.dcmread(dcm_path, force=True)
except IOError as e:
print(f"Can't import {dcm_path.stem}")
else:
hu = apply_modality_lut(dicom.pixel_array, dicom)
dicom_set.append(hu)
You were well on your way. You just have to build up a volume from the individual slices that you read in. This code snippet will create a pixelVolume of dimension 512x512x200 if your data is as advertised.
import dicom
import numpy
images = [] # to create an empty list
# Read all of the DICOM images from file_path into list "images"
for f in glob.iglob('file_path'):
image = pydicom.dcmread(f)
images.append(image)
# Use the first image to determine the number of rows and columns
repImage = images[0]
rows=int(repImage.Rows)
cols=int(repImage.Columns)
slices=len(images)
# This tuple represents the dimensions of the pixel volume
volumeDims = (rows, cols, slices)
# allocate storage for the pixel volume
pixelVolume = numpy.zeros(volumeDims, dtype=repImage.pixel_array.dtype)
# fill in the pixel volume one slice at a time
for image in images:
pixelVolume[:,:,i] = image.pixel_array
#Use pixelVolume to do something interesting
I don't know if you are a DICOM expert or a DICOM novice, but I am just accepting your claim that your 200 images make sense when interpreted as a volume. There are many ways that this may fail. The slices may not be in expected order. There may be multiple series in your study. But I am guessing you have a "nice" DICOM dataset, maybe used for tutorials, and that this code will help you take a step forward.
I need to replace a K words with K other words for every PDF file I have within a certain path file location and on top of this I need to replace every logo with another logo. I have around 1000 PDF files, and so I do not want to use Adobe Acrobat and edit 1 file at a time. How can I start this?
Replacing words seems at least doable as long as there is a decent PDF reader one can access through Python ( Note I want to do this task in Python ), however replacing an image might be more difficult. I will most likely have to find the dimension of the current image and resize the image being used to replace the current image dynamically, whilst the program runs through these PDF files.
Hi, so I've written down some code regarding this:
from pikepdf import Pdf, PdfImage, Name
import os
import glob
from PIL import Image
import zlib
example = Pdf.open(r'...\Likelihood.pdf')
PagesWithImages = []
ImageCodesForPages = []
# Grab all the pages and all the images in every page.
for i in example.pages:
if len(list(i.images.keys())) >= 1:
PagesWithImages.append(i)
ImageCodesForPages.append(list(i.images.keys()))
pdfImages = []
for i,j in zip(PagesWithImages, ImageCodesForPages):
for x in j:
pdfImages.append(i.images[x])
# Replace every single page using random image, ensure that the dimensions remain the same?
for i in pdfImages:
pdfimage = PdfImage(i)
rawimage = pdfimage.obj
im = Image.open(r'...\panda.jpg')
pillowimage = pdfimage.as_pil_image()
print(pillowimage.height)
print(pillowimage.width)
im = im.resize((pillowimage.width, pillowimage.height))
im.show()
rawimage.write(zlib.compress(im.tobytes()), filter=Name("/FlateDecode"))
rawimage.ColorSpace = Name("/DeviceRGB")
So just one problem, it doesn't actually replace anything. If you're wondering why and how I wrote this code I actually got it from this documentation:
https://buildmedia.readthedocs.org/media/pdf/pikepdf/latest/pikepdf.pdf
Start at Page 53
I essentially put all the pdfImages into a list, as 1 page can have multiple images. In conjunction with this, the last for loop essentially tries to replace all these images whilst maintaining the same width and height size. Also note, the file path names I changed here and it definitely is not the issue.
Again Thank You
I have figured out what I was doing wrong. So for anyone that wants to actually replace an image with another image in place on a PDF file what you do is:
from pikepdf import Pdf, PdfImage, Name
from PIL import Image
import zlib
example = Pdf.open(filepath, allow_overwriting_input=True)
PagesWithImages = []
ImageCodesForPages = []
# Grab all the pages and all the images in every page.
for i in example.pages:
imagelists = list(i.images.keys())
if len(imagelists) >= 1:
for x in imagelists:
rawimage = i.images[x]
pdfimage = PdfImage(rawimage)
rawimage = pdfimage.obj
pillowimage = pdfimage.as_pil_image()
im = Image.open(imagePath)
im = im.resize((pillowimage.width, pillowimage.height))
rawimage.write(zlib.compress(im.tobytes()), filter=Name("/FlateDecode"))
rawimage.ColorSpace = Name("/DeviceRGB")
rawimage.Width, rawimage.Height = pillowimage.width, pillowimage.height
example.save()
Essentially, I changed the arguements in the first line, such that I specify that I can overwrite. In conjunction, I also added the last line which actually allows me to save.
I have created a definition that loads every image from a called folder. I am now trying to create a code that will either 1) load a specific image when indexed, and/or 2) load an image at random. I have attached two screenshots of my code and the error I am receiving.
https://i.stack.imgur.com/nQKrV.png
https://i.stack.imgur.com/toXkI.png
It looks like you need to concatenate the directory path with the file name:
with open(os.path.join(rat110_GF_path, random_filename)) as file
lines = file.readlines()
I'm working on a project that involves Python. I've NEVER used it along with OpenCV. The objective is to take a 16x16 section of an video, I'm practicing with a single Image, and get it's RBG value. I'm suppose to run this for thousands of frame on a video, which i dont know how to loop. Once I have it ([ 71 155 90]) for example, I want to save it to a notepad, excel sheet, or some simple way or referring to my results.
I've tried looking up tutorials on how to export values, but they've used so many different terms that I don't know where to start.
import numpy as np
import cv2
img = cv2.imread('dog.jpg', cv2.IMREAD_COLOR)
px = img[16,16]
print(px)
The only thing I get is the RBG output [ 71 155 90] in the terminal. I don't know where to do from there. I don't know how to export the value.
you can use openpyxl or
import numpy as np import cv2
img = cv2.imread('dog.jpg', cv2.IMREAD_COLOR)
px = img[16,16]
import pandas as px
df = pd.DataFrame(px)
df.to_excel('filename.xlsx')
You'll need to open a file and then write the results to that file, here is one possible way to do this (although perhaps not the most optimal):
fp = open('output.csv', 'w')
fp.write('{},{},{}'.format(px[0],px[1],px[2])
# write more values here
fp.close() # do this at the end of your writes
I am currently working on something similar, instead of videos I am working with images so I went around searching for tutorials on how to do bulk export of images/ frames from a folder and saving the data into a numpy array.
This is a sample of my code *not sure how much errors are inside but it is able to load and save image frames into an array. I use tqdm to show a simple progress bar so I know what is the status of the image loading when I call this function.
def img_readph(path):
readph =[i for i in listdir(path) if isfile(join(path,i))]
img = np.empty(len(readph), dtype=object)
for j in tqdm(range(0, len(readph))):
img[j] = cv2.imread(join(path,readph[j]))
return img
In order to load and work on the images that are currently saved in a numpy array stack, I use this set of code to do the extraction, perform a basic psnr calculation and save the data to a .txt (learning how to convert the result to a .csv that I can load/save/append in python for future edits as well).
for index in tqdm(range(len(img))):
(psnr, meanerror) = calculate_psnr(imgGT[index], imgSR[index])
print('Image No.{} has average mean square error of {} and the average PSNR is {}'.format(index,meanerror,psnr))
Doing it this way lets me loop every video frame I have in the previous numpy array to perform my operation to calculate psnr.
What you could do is to try write your code to get the RGB values into a function using,
txtfilename = input("enter filename: ")
with open(str(txtfilename)+".txt","w") as results:
for index in tqdm(range(0, len(img))) #the array from imread
img = cv2.imread('img', cv2.IMREAD_COLOR)
px = img[width, height]
print("The RBG values are {}".format(px), file=results)
Something along the lines of this I guess, hope it helps.
I have written a python script to Delta compress an image. The image file format is .tif which contains 8 images. When I use the normal code ...
org_Image = Image.open(image)
org_Data = org_Image.load()
... I can only access the first image. How do I go about accessing the other ones?
You use org_Image.seek(org_Image.tell() + 1) to get the next one.
In PIL seek moves you to a given frame, (with an IO_Error if it doesn't exist), and tell reports the current frame number.