<p align="center">
<a href="https://github.com/pydicom/pylibjpeg-openjpeg/actions?query=workflow%3Aunit-tests"><img alt="Build status" src="https://github.com/pydicom/pylibjpeg-openjpeg/workflows/unit-tests/badge.svg"></a>
<a href="https://codecov.io/gh/pydicom/pylibjpeg-openjpeg"><img alt="Test coverage" src="https://codecov.io/gh/pydicom/pylibjpeg-openjpeg/branch/main/graph/badge.svg"></a>
<a href="https://pypi.org/project/pylibjpeg-openjpeg/"><img alt="PyPI versions" src="https://img.shields.io/pypi/v/pylibjpeg-openjpeg"></a>
<a href="https://www.python.org/"><img alt="Python versions" src="https://img.shields.io/pypi/pyversions/pylibjpeg-openjpeg"></a>
<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
</p>
## pylibjpeg-openjpeg
A Python 3.8+ wrapper for
[openjpeg](https://github.com/uclouvain/openjpeg), with a focus on use as a plugin for [pylibjpeg](http://github.com/pydicom/pylibjpeg).
Linux, OSX and Windows are all supported.
### Installation
#### Dependencies
[NumPy](http://numpy.org)
#### Installing the current release
```bash
python -m pip install -U pylibjpeg-openjpeg
```
#### Installing the development version
Make sure [Python](https://www.python.org/), [Git](https://git-scm.com/) and [CMake](https://cmake.org/) are installed. For Windows, you also need to install
[Microsoft's C++ Build Tools](https://visualstudio.microsoft.com/thank-you-downloading-visual-studio/?sku=BuildTools&rel=16).
```bash
git clone --recurse-submodules https://github.com/pydicom/pylibjpeg-openjpeg
python -m pip install pylibjpeg-openjpeg
```
### Supported JPEG Formats
#### Decoding
| ISO/IEC Standard | ITU Equivalent | JPEG Format |
| --- | --- | --- |
| [15444-1](https://www.iso.org/standard/78321.html) | [T.800](https://www.itu.int/rec/T-REC-T.800/en) | [JPEG 2000](https://jpeg.org/jpeg2000/) |
#### Encoding
Encoding of NumPy ndarrays is supported for the following:
* Array dtype: bool, uint8, int8, uint16, int16, uint32 and int32 (1-24 bit-depth only)
* Array shape: (rows, columns) and (rows, columns, planes)
* Number of rows/columns: up to 65535
* Number of planes: 1, 3 or 4
### Transfer Syntaxes
| UID | Description |
| --- | --- |
| 1.2.840.10008.1.2.4.90 | JPEG 2000 Image Compression (Lossless Only) |
| 1.2.840.10008.1.2.4.91 | JPEG 2000 Image Compression |
| 1.2.840.10008.1.2.4.201 | High-Throughput JPEG 2000 Image Compression (Lossless Only) |
| 1.2.840.10008.1.2.4.202 | High-Throughput JPEG 2000 with RPCL Options Image Compression (Lossless Only) |
| 1.2.840.10008.1.2.4.203 | High-Throughput JPEG 2000 Image Compression |
### Usage
#### With pylibjpeg and pydicom
```python
from pydicom import dcmread
from pydicom.data import get_testdata_file
ds = dcmread(get_testdata_file('JPEG2000.dcm'))
arr = ds.pixel_array
```
#### Standalone JPEG decoding
You can also decode JPEG 2000 images to a [numpy ndarray][1]:
[1]: https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html
```python
from openjpeg import decode
with open('filename.j2k', 'rb') as f:
# Returns a numpy array
arr = decode(f)
# Or simply...
arr = decode('filename.j2k')
```
#### Standalone JPEG encoding
Lossless encoding of RGB with multiple-component transformation:
```python
import numpy as np
from openjpeg import encode_array
arr = np.random.randint(low=0, high=65536, size=(100, 100, 3), dtype="uint8")
encode_array(arr, photometric_interpretation=1) # 1: sRGB
```
Lossy encoding of a monochrome image using compression ratios:
```python
import numpy as np
from openjpeg import encode_array
arr = np.random.randint(low=-2**15, high=2**15, size=(100, 100), dtype="int8")
# You must determine your own values for `compression_ratios`
# as these are for illustration purposes only
encode_array(arr, compression_ratios=[5, 2])
```
Lossy encoding of a monochrome image using peak signal-to-noise ratios:
```python
import numpy as np
from openjpeg import encode_array
arr = np.random.randint(low=-2**15, high=2**15, size=(100, 100), dtype="int8")
# You must determine your own values for `signal_noise_ratios`
# as these are for illustration purposes only
encode_array(arr, signal_noise_ratios=[50, 80, 100])
```
See the docstring for the [encode_array() function][2] for full details.
[2]: https://github.com/pydicom/pylibjpeg-openjpeg/blob/main/openjpeg/utils.py#L429
Raw data
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"description": "<p align=\"center\">\n<a href=\"https://github.com/pydicom/pylibjpeg-openjpeg/actions?query=workflow%3Aunit-tests\"><img alt=\"Build status\" src=\"https://github.com/pydicom/pylibjpeg-openjpeg/workflows/unit-tests/badge.svg\"></a>\n<a href=\"https://codecov.io/gh/pydicom/pylibjpeg-openjpeg\"><img alt=\"Test coverage\" src=\"https://codecov.io/gh/pydicom/pylibjpeg-openjpeg/branch/main/graph/badge.svg\"></a>\n<a href=\"https://pypi.org/project/pylibjpeg-openjpeg/\"><img alt=\"PyPI versions\" src=\"https://img.shields.io/pypi/v/pylibjpeg-openjpeg\"></a>\n<a href=\"https://www.python.org/\"><img alt=\"Python versions\" src=\"https://img.shields.io/pypi/pyversions/pylibjpeg-openjpeg\"></a>\n<a href=\"https://github.com/psf/black\"><img alt=\"Code style: black\" src=\"https://img.shields.io/badge/code%20style-black-000000.svg\"></a>\n</p>\n\n\n## pylibjpeg-openjpeg\n\nA Python 3.8+ wrapper for\n[openjpeg](https://github.com/uclouvain/openjpeg), with a focus on use as a plugin for [pylibjpeg](http://github.com/pydicom/pylibjpeg).\n\nLinux, OSX and Windows are all supported.\n\n### Installation\n#### Dependencies\n[NumPy](http://numpy.org)\n\n#### Installing the current release\n```bash\npython -m pip install -U pylibjpeg-openjpeg\n```\n\n#### Installing the development version\n\nMake sure [Python](https://www.python.org/), [Git](https://git-scm.com/) and [CMake](https://cmake.org/) are installed. For Windows, you also need to install\n[Microsoft's C++ Build Tools](https://visualstudio.microsoft.com/thank-you-downloading-visual-studio/?sku=BuildTools&rel=16).\n```bash\ngit clone --recurse-submodules https://github.com/pydicom/pylibjpeg-openjpeg\npython -m pip install pylibjpeg-openjpeg\n```\n\n\n### Supported JPEG Formats\n#### Decoding\n\n| ISO/IEC Standard | ITU Equivalent | JPEG Format |\n| --- | --- | --- |\n| [15444-1](https://www.iso.org/standard/78321.html) | [T.800](https://www.itu.int/rec/T-REC-T.800/en) | [JPEG 2000](https://jpeg.org/jpeg2000/) |\n\n#### Encoding\n\nEncoding of NumPy ndarrays is supported for the following:\n\n* Array dtype: bool, uint8, int8, uint16, int16, uint32 and int32 (1-24 bit-depth only)\n* Array shape: (rows, columns) and (rows, columns, planes)\n* Number of rows/columns: up to 65535\n* Number of planes: 1, 3 or 4\n\n### Transfer Syntaxes\n| UID | Description |\n| --- | --- |\n| 1.2.840.10008.1.2.4.90 | JPEG 2000 Image Compression (Lossless Only) |\n| 1.2.840.10008.1.2.4.91 | JPEG 2000 Image Compression |\n| 1.2.840.10008.1.2.4.201 | High-Throughput JPEG 2000 Image Compression (Lossless Only) |\n| 1.2.840.10008.1.2.4.202 | High-Throughput JPEG 2000 with RPCL Options Image Compression (Lossless Only) |\n| 1.2.840.10008.1.2.4.203 | High-Throughput JPEG 2000 Image Compression |\n\n\n### Usage\n#### With pylibjpeg and pydicom\n\n```python\nfrom pydicom import dcmread\nfrom pydicom.data import get_testdata_file\n\nds = dcmread(get_testdata_file('JPEG2000.dcm'))\narr = ds.pixel_array\n```\n\n#### Standalone JPEG decoding\n\nYou can also decode JPEG 2000 images to a [numpy ndarray][1]:\n\n[1]: https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html\n\n```python\nfrom openjpeg import decode\n\nwith open('filename.j2k', 'rb') as f:\n # Returns a numpy array\n arr = decode(f)\n\n# Or simply...\narr = decode('filename.j2k')\n```\n\n#### Standalone JPEG encoding\n\nLossless encoding of RGB with multiple-component transformation:\n\n```python\n\nimport numpy as np\nfrom openjpeg import encode_array\n\narr = np.random.randint(low=0, high=65536, size=(100, 100, 3), dtype=\"uint8\")\nencode_array(arr, photometric_interpretation=1) # 1: sRGB\n```\n\nLossy encoding of a monochrome image using compression ratios:\n\n```python\n\nimport numpy as np\nfrom openjpeg import encode_array\n\narr = np.random.randint(low=-2**15, high=2**15, size=(100, 100), dtype=\"int8\")\n# You must determine your own values for `compression_ratios`\n# as these are for illustration purposes only\nencode_array(arr, compression_ratios=[5, 2])\n```\n\nLossy encoding of a monochrome image using peak signal-to-noise ratios:\n\n```python\n\nimport numpy as np\nfrom openjpeg import encode_array\n\narr = np.random.randint(low=-2**15, high=2**15, size=(100, 100), dtype=\"int8\")\n# You must determine your own values for `signal_noise_ratios`\n# as these are for illustration purposes only\nencode_array(arr, signal_noise_ratios=[50, 80, 100])\n```\n\nSee the docstring for the [encode_array() function][2] for full details.\n\n[2]: https://github.com/pydicom/pylibjpeg-openjpeg/blob/main/openjpeg/utils.py#L429\n\n",
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