Temp files are given unique name and deleted after dcm pdf is created. Removed stone web viewer.
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2110aac355
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@ -68,62 +68,3 @@ $('#instance').live('pageshow', function() {
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}
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});
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});
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$('#study').live('pagebeforecreate', function() {
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var b = $('<a>')
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.attr('data-role', 'button')
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.attr('href', '#')
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.attr('data-icon', 'search')
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.attr('data-theme', 'e')
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.text('Stone Web Viewer (for mammography)');
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b.insertBefore($('#study-delete').parent().parent());
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b.click(function() {
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if ($.mobile.pageData) {
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$.ajax({
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url: '../studies/' + $.mobile.pageData.uuid,
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dataType: 'json',
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cache: false,
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success: function(study) {
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var studyInstanceUid = study.MainDicomTags.StudyInstanceUID;
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window.open('../mammography-viewer/index.html?study=' + studyInstanceUid);
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}
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});
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}
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});
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});
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$('#series').live('pagebeforecreate', function() {
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var b = $('<a>')
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.attr('data-role', 'button')
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.attr('href', '#')
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.attr('data-icon', 'search')
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.attr('data-theme', 'e')
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.text('Stone Web Viewer (for mammography)');
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b.insertBefore($('#series-delete').parent().parent());
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b.click(function() {
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if ($.mobile.pageData) {
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$.ajax({
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url: '../series/' + $.mobile.pageData.uuid,
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dataType: 'json',
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cache: false,
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success: function(series) {
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$.ajax({
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url: '../studies/' + series.ParentStudy,
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dataType: 'json',
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cache: false,
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success: function(study) {
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var studyInstanceUid = study.MainDicomTags.StudyInstanceUID;
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var seriesInstanceUid = series.MainDicomTags.SeriesInstanceUID;
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window.open('../mammography-viewer/index.html?study=' + studyInstanceUid +
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'&series=' + seriesInstanceUid);
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}
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});
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}
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});
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}
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});
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});
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@ -4,9 +4,10 @@ from pydicom.dataset import FileMetaDataset
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from pydicom.uid import MediaStorageDirectoryStorage, EncapsulatedPDFStorage, generate_uid
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import matplotlib
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matplotlib.use("Agg") # Use non-GUI backend to avoid Tkinter issues
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import matplotlib.pyplot as plt # Now import pyplot
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import matplotlib.pyplot as plt
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from reportlab.pdfgen import canvas
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from datetime import datetime, date
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import os
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def extract_measurements(sr):
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@ -28,10 +29,10 @@ def extract_measurements(sr):
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return measurements, probabilities
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def overlay_measurements(image, measurements, probabilities):
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def overlay_measurements(dcm_image_pixels, measurements, probabilities, image_path):
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"""Overlays extracted measurements onto the mammography image."""
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fig, ax = plt.subplots()
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ax.imshow(image, cmap='gray')
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ax.imshow(dcm_image_pixels, cmap='gray')
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# Draw each polyline
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for i in range(0, len(measurements), 1):
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@ -44,11 +45,11 @@ def overlay_measurements(image, measurements, probabilities):
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ax.axis("off")
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# Save the overlay as an image
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plt.savefig("temp.png", bbox_inches='tight', pad_inches=0)
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plt.savefig(image_path, bbox_inches='tight', pad_inches=0)
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plt.close(fig)
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def create_pdf(temp_image_path, measurements, sr, pdf_path):
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def create_pdf(image_path, measurements, sr, pdf_path):
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"""Creates a PDF with the mammography image and extracted measurements."""
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c = canvas.Canvas(pdf_path)
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@ -63,7 +64,7 @@ def create_pdf(temp_image_path, measurements, sr, pdf_path):
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# Reset font for other text
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c.setFont("Helvetica", 12)
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# Add patient info to the PDF
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# Add patient and study info to the PDF
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c.drawString(70, 800, f"Patient ID: {sr.PatientID}")
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c.drawString(70, 785, f"Patient name: {sr.PatientName}")
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c.drawString(70, 770, f"Patient birth date: {formateted_datetime(sr.PatientBirthDate)}")
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@ -73,13 +74,13 @@ def create_pdf(temp_image_path, measurements, sr, pdf_path):
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c.drawString(70, 700, f"Referring physician: {sr.ReferringPhysicianName}")
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# Add the image to the PDF
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c.drawImage(temp_image_path, 70, 300)
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c.drawImage(image_path, 70, 300)
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c.save()
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# Convert DICOM date
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def formateted_datetime(dicom_date, dicom_time = None):
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def formateted_datetime(dicom_date, dicom_time = None):
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"""Convert DICOM date and time format."""
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if dicom_date is None or dicom_date == '':
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return ''
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@ -98,7 +99,8 @@ def formateted_datetime(dicom_date, dicom_time = None):
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# Combined datetime
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return f"{formatted_date} {formatted_time}"
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def create_dcm_pdf(sr, pdf_path):
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def create_dcm_pdf(sr, pdf_path, instance_uid):
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ds = Dataset()
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# Add general DICOM metadata
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@ -123,7 +125,7 @@ def create_dcm_pdf(sr, pdf_path):
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ds.Manufacturer = "MammographyAI"
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ds.ConversionType = "DI"
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ds.SOPInstanceUID = generate_uid()
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ds.SOPInstanceUID = instance_uid
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ds.SOPClassUID = EncapsulatedPDFStorage
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# Open the PDF file and read it as binary data
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@ -156,8 +158,23 @@ def create_dcm_pdf(sr, pdf_path):
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return ds
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def create(image, sr):
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def create(dcm_image_pixels, sr):
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instance_uid = generate_uid()
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temp_image_path = f"{instance_uid}.png"
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temp_pdf_path = f"{instance_uid}.pdf"
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measurements, probabilities = extract_measurements(sr)
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overlay_measurements(image, measurements, probabilities)
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create_pdf("temp.png", measurements, sr, "temp.pdf")
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return create_dcm_pdf(sr, "temp.pdf",)
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overlay_measurements(dcm_image_pixels, measurements, probabilities, temp_image_path)
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create_pdf(temp_image_path, measurements, sr, temp_pdf_path)
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dcm_pdf = create_dcm_pdf(sr, temp_pdf_path, instance_uid)
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print("Current Working Directory:", os.getcwd())
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if os.path.exists(temp_image_path):
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os.remove(temp_image_path)
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if os.path.exists(temp_pdf_path):
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os.remove(temp_pdf_path)
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return dcm_pdf
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@ -24,6 +24,7 @@
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import sys
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import json
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import orthanc
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import os
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config = json.loads(orthanc.GetConfiguration()).get('Mammography', {})
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venv = config.get('VirtualEnv')
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@ -32,61 +33,7 @@ if venv != None:
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# https://orthanc.uclouvain.be/book/plugins/python.html#working-with-virtual-environments
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sys.path.insert(0, venv)
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##
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## Install the Stone Web viewer
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##
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STONE_VERSION = '2024-08-31-StoneWebViewer-DICOM-SR'
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VIEWER_PREFIX = '/mammography-viewer/'
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import os
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SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
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VIEWER_DIR = os.path.join(SCRIPT_DIR, 'viewer')
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sys.path.append(os.path.join(SCRIPT_DIR, '..'))
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import download
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os.makedirs(VIEWER_DIR, exist_ok = True)
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download.get(os.path.join(VIEWER_DIR, '%s.zip' % STONE_VERSION),
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'https://github.com/jodogne/orthanc-mammography/raw/master/viewer/%s.zip' % STONE_VERSION,
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4815178, '86b52a17f86e4769d12e9ae680c4a99f')
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import zipfile
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stone_assets = zipfile.ZipFile(os.path.join(VIEWER_DIR, '%s.zip' % STONE_VERSION))
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MIME_TYPES = {
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'.css' : 'text/css',
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'.gif' : 'image/gif',
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'.html' : 'text/html',
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'.jpeg' : 'image/jpeg',
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'.js' : 'text/javascript',
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'.png' : 'image/png',
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}
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def serve_stone_web_viewer(output, uri, **request):
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if not uri.startswith(VIEWER_PREFIX):
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output.SendHttpStatusCode(404)
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elif request['method'] != 'GET':
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output.SendMethodNotAllowed('GET')
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else:
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try:
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path = '%s/%s' % (STONE_VERSION, uri[len(VIEWER_PREFIX):])
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extension = os.path.splitext(path) [1]
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if not extension in MIME_TYPES:
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mime = 'application/octet-stream'
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else:
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mime = MIME_TYPES[extension]
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with stone_assets.open(path) as f:
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output.AnswerBuffer(f.read(), mime)
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except:
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output.SendHttpStatusCode(500)
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orthanc.RegisterRestCallback('%s(.*)' % VIEWER_PREFIX, serve_stone_web_viewer)
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##
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## Load the deep learning model
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