Convert DICOM to JPEG2000 via Python Cloud API
Transform DICOM into JPEG2000 using native Python Cloud APIs without needing any image editor or 3rd-party libraries.
Get StartedHow to Convert DICOM to JPEG2000 Using Python Cloud API
Aspose.Imaging.Cloud for Python API which is a feature-rich, powerful and easy to use image manipulation and conversion Cloud API for Python platform. You can download its latest version directly from pypi.org or install it from pip command line.
Command Prompt
> pip install aspose-imaging-cloud
Steps to Convert DICOM to JPEG2000 via Python Cloud API
Developers can easily load & convert DICOM files to JPEG2000 in just a few lines of code.
- Load DICOM file as stream
- Create & set the instance of CreateConvertedImageRequest
- Call the CreateConvertedImage method
- Get converted image from response stream
System Requirements
Aspose.Imaging Cloud for Python is supported on all major operating systems. Just make sure that you have the following prerequisites.
- Python 2.7 or later.
Convert DICOM to JPEG2000 - Cloud
import os | |
import asposeimagingcloud.models.requests as requests | |
IMAGE_FILE_NAME= 'example_image.dicom'; | |
IMAGES_FOLDER = 'ExampleImages'; | |
CLOUD_FOLDER = 'CloudImages'; | |
OUTPUT_FOLDER = 'Output'; | |
# Get ClientId and ClientSecret from https://dashboard.aspose.cloud/ | |
# or use on-premise version (https://docs.aspose.cloud/imaging/getting-started/how-to-run-docker-container/) | |
_imaging_api = ImagingApi(client_secret, client_id, 'https://api.aspose.cloud') | |
def convert_image_from_storage(self): | |
"""Convert an image to another format""" | |
input_image = os.path.join(IMAGES_FOLDER, IMAGE_FILE_NAME) | |
upload_file_request = requests.UploadFileRequest(os.path.join(CLOUD_FOLDER, IMAGE_FILE_NAME), input_image) | |
result = self._imaging_api.upload_file(upload_file_request) | |
if result.errors: | |
print('Uploading errors count: ' + str(len(result.errors))) | |
# Please refer to | |
# https://docs.aspose.cloud/imaging/supported-file-formats/#convert | |
# for possible output formats | |
format = 'jpeg2000' # Resulting image format | |
folder = CLOUD_FOLDER # Input file is saved at the desired folder in the storage | |
storage = None # We are using default Cloud Storage | |
request = requests.ConvertImageRequest(IMAGE_FILE_NAME, format, folder, storage) | |
converted_image = self._imaging_api.convert_image(request) | |
# Save the image file to output folder | |
filename_part, extension = os.path.splitext(IMAGE_FILE_NAME) | |
new_file_name = filename_part + '.' + 'jpeg2000' | |
path = os.path.abspath(os.path.join(OUTPUT_FOLDER, new_file_name)) | |
shutil.copy(converted_image, path) | |
def create_converted_image_from_request(self): | |
"""Convert an image to another format. Image data is passed in a request stream""" | |
# Please refer to | |
# https://docs.aspose.cloud/imaging/supported-file-formats/#convert | |
# for possible output formats | |
format = 'jpeg2000' # Resulting image format | |
storage = None # We are using default Cloud Storage | |
out_path = None # Path to updated file (if this is empty, response contains streamed image) | |
input_stream = os.path.join(IMAGES_FOLDER, IMAGE_FILE_NAME) | |
request = requests.CreateConvertedImageRequest(input_stream, format, out_path, storage) | |
converted_image = self._imaging_api.create_converted_image(request) | |
# Save the image file to output folder | |
filename_part, extension = os.path.splitext(IMAGE_FILE_NAME) | |
new_file_name = filename_part + '.' + 'jpeg2000' | |
path = os.path.abspath(os.path.join(OUTPUT_FOLDER, new_file_name)) | |
shutil.copy(converted_image, path) |
About Aspose.Imaging Cloud API for Python
Aspose.Imaging Cloud API is an image processing solution to process images (photos) within your cloud or web applications. It offers: cross-platform Image processing, including but not limited to conversions between various image formats (including uniform multi-page or multi-frame image processing), transformations (resize, crop, flip&rotate, grayscale, adjust), advanced image manipulation features (filtering, deskewing), AI features (i.e. object detection and reverse image search). It’s a Cloud API and does not depend on any software for image operations. One can easily add high-performance image conversion features with Cloud APIs within projects. Flexible integrations options including SDKs for various languages (Python, Ruby, .NET, Java, NodeJS, PHP) and the use of the REST API allow to make the integration easy.
Convert DICOMs via Online App
Convert DICOM to JPEG2000 documents by visiting our Live Demos website. The live demo has the following benefits
DICOM What is DICOM File Format
DICOM is the acronym for Digital Imaging and Communications in Medicine and pertains to the field of Medical Informatics. DICOM is the combination of file format definition and a network communications protocol. DICOM uses the .DCM extension. .DCM exist in two different formats i.e. format 1.x and format 2.x. DCM Format 1.x is further available in two versions normal and extended. DICOM is used for the integration of medical imaging devices like printers, servers, scanners etc from various vendors and also contains identification data of each patient for uniqueness. DICOM files can be shared between two parties if they are capable of receiving image data in DICOM format. The communication part of DICOM is application layer protocol and uses TCP/IP to communicate between entities. HTTP and HTTPS protocols are used for the web services of DICOM. Versions supported by web services are 1.0, 1.1, 2 or later.
Read MoreJPEG2000 What is JPEG2000 File Format
JPEG 2000 (JP2) is an image coding system and state-of-the-art image compression standard. Designed, using wavelet technology JPEG 2000 can code lossless content in any quality at once. Moreover, without any substantial penalty in coding efficiency, JPEG 2000 have the capability to access and decode the same content efficaciously into a variety of other resolutions and qualities. The code streams in JPEG 2000 is significantly scalable having regions of interest that provide the facility for spatial random access. Possessing Up to 16384 diverse components with the dimensions in terapixels, and precision that can be high as 38 bits/sample.
Read MoreOther Supported Conversions
Using Python Cloud API, one can easily convert different formats including.