I have this json file which has the image name(medical images-around 7500) and its corresponding medical reports.
It is of the format:
{"IMAGE_NAME1.png": "MEDICAL_REPORT1_IN_TEXT", "IMAGE_NAME2.png": "MEDICAL_REPORT2_IN_TEXT", ...and so on for all images ...}
What I want is all the image names in the JSON file so that I can take all the images(From a database of images which is a super set of the image names in the JSON file) and make its own folder. Can someone help me with this?
I think you're looking for the json library. I haven't tested this, but I am pretty confident it will work.
import json
with open("path/to/json.json", 'r') as file:
json_data = json.load(file)
to get image names from what you described the data to look like.
image_names = list(json_data.keys())
Related
I need to analyse a lot of CAN data and want to use python for that. I recently came across the python-can library and saw that it's possible to convert .blf to .asc files.
How do I convert .blf data of CAN to .asc using python This post helped a lot.
https://stackoverflow.com/users/13525512/tranbi Can #Tranbi or anyone else help me with some example code?
This is the part I have done till now:
import can
import os
fileList = os.listdir(".\inputFiles")
for i in range(len(fileList)):
with open(os.path.join(".\inputFiles", fileList[i]), 'rb') as f_in:
log_in = can.io.BLFReader(f_in)
with open(os.path.join(".\outputFiles", os.path.splitext(fileList[i])[0] + '.asc'), 'w') as f_out:
log_out = can.io.ASCWriter(f_out)
for msg in log_in:
log_out.on_message_received(msg)
log_out.stop()
I need to either directly read data from .blf files sequentially, or convert them to .asc, correct the timestamp using the file name, combine the files, convert them to .csv and then analyse in python. Would really help if I can get a shorter route?
I am writing an app, which takes a STL file as input. I want to get volume of the stl object without saving the stl file and use the volume to calculate a quote and post it back to browser. Right now I am using numpy-stl package, but I am stuck on how to create a mesh object for numpy-stl from the file I get with request.files['file'].read(). Any help is appreciated.
mycode:
what I get for filedata
what I get for error
You can try the following code:
import io
filedata = request.files['file'].read()
data = io.BytesIO(filedata)
tmp_mesh = mesh.Mesh.from_file("tmp.stl", fh=data)
You can use tmp_mesh object to do you interesting operation
suggestion to add error handle on something not expected
if request.files not contain 'file' keys
I am trying out the google vision API & for that I want to do some preparations. I have collected some images online with which I want to work with.
There are around 100 images and now I want to set up a .csv file where the first column has the names of the images inside, so that I can later go over them.
Example:
Name
Picture1.jpg
Picture2.jpg
etc.
Does someone know a Python way to achieve this? So that I can run the code and it puts those names into a .csv?
Thanks already and have a good one!
You can use glob in python to iterate on all the images in a directory and write the image names to a csv file.
Example:
import glob
import os
f = open('images.csv', 'w')
for file in glob.glob('*.png'):
f.write(os.path.basename(file))
f.close()
This is the form of my nested directory:
/data/patient_level/study_level/series_level/
For each patient_level folder, I need to read the ".dcm" files from the corresponding "series_level" folder.
How can I access the ".dcm" file in the "series_level" folders?
I need 3 features from a DICOM object.
This is my source code:
import dicom
record = dicom.read_file("/data/patient_level/study_level/series_level/000001.dcm")
doc = {"PatientID": record.PatientID, "Manufacturer": record.Manufacturer, "SeriesTime": record.SeriesTime}
Then, I will insert this doc to a Mongo DB.
Any suggestions is appreciated.
Thanks in advance.
It is not quite clear the problem you are trying to solve, but if all you want is to get a list of all .dcm files from that the data directory, you can use pathlib.Path():
from pathlib import Path
data = Path('/data')
list(data.rglob('*.dcm'))
To split a file in its components, you can use something like this:
dcm_file = '/patient_level/study_level/series_level/000001.dcm'
_, patient_level, study_level, series_level, filename = dcm_file.split('/')
Which would give you patient_level, study_level, series_level, and filename from dcm_file.
But it would be better to stick with Path() and its methods, like this:
dcm_file = Path('/patient_level/study_level/series_level/000001.dcm')
dcm_file.parts
Which would give you something like this:
('/', 'patient_level', 'study_level', 'series_level', '000001.dcm')
Those are just starting points anyway.
Hi i have a project were the user uploads a .c3d file to be able to display the data on charts, so i am making it for when the user uploads a the file it gets converted into a .csv file so i can get the values but i am having no luck trying to convert from the .c3d file to the .csv extension.
i have used the following documentation http://c3d.readthedocs.io/en/stable/
but there much isn't much information on this out there
this is the following code i use to print the data:
import c3d
reader = c3d.Reader(open('file.c3d', 'rb'))
for i, points, analog in reader.read_frames():
print('frame {}: {}'.format(i, points.round(2)))
The c3d library I suppose you use(https://pypi.python.org/pypi/c3d/0.2.1) includes a script for converting C3D data to CSV format (c3d2csv).