| Name | ekyc JSON |
| Version |
0.1.15
JSON |
| download |
| home_page | None |
| Summary | A library for electronic Know Your Customer (eKYC) verification |
| upload_time | 2024-09-05 06:34:50 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.13,>=3.9 |
| license | MIT License Copyright (c) [2024] [PrabhjeevanSingh] Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
ekyc
verification
identity
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
Flask
numpy
dlib
deepface
paddleocr
scikit-learn
opencv-python-headless
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Juara eKYC Library
Juara eKYC is a Python library for electronic Know Your Customer (eKYC) verification, including document verification, face processing, liveness detection, and face matching.
## Features
- Document verification
- Face processing
- Liveness check
- Face matching
- Flask-based API for eKYC verification
## Prerequisites
- Python 3.7+
- OpenCV
- NumPy
- scikit-learn
- deepface
- paddleocr
- Flask
- dlib
## Installation
### For Windows Users:
1. Ensure you have CMake installed. You can download it from [cmake.org](https://cmake.org/download/).
2. Uninstall any previous versions:
```
pip uninstall ekyc
```
3. Clear pip cache:
```
pip cache purge
```
4. Install the package:
```
pip install path/to/ekyc-0.0.4-py3-none-any.whl
```
Note: This will automatically install the correct dlib version for your Python installation.
5. You may need to install PaddleOCR and PaddlePaddle separately:
```
pip install paddlepaddle
pip install paddleocr
```
### For Other Operating Systems:
You can install the eKYC library using pip:
pip install juara_ekyc
## Usage
Here's a basic example of how to use the Juara eKYC library:
python
from juara_ekyc import process_id_verification
result, message = process_id_verification('path/to/image.jpg')
print(f"Verification result: {result}")
print(f"Message: {message}")
## Development
1. Clone the repository:
```
git clone https://github.com/yourusername/juara_ekyc.git
cd juara_ekyc
```
2. Create a virtual environment:
```
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. Install the development dependencies:
```
pip install -r requirements.txt
```
4. Run the tests:
```
python -m unittest discover tests
```
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License - see the LICENSE file for details.
Raw data
{
"_id": null,
"home_page": null,
"name": "ekyc",
"maintainer": null,
"docs_url": null,
"requires_python": "<3.13,>=3.9",
"maintainer_email": null,
"keywords": "eKYC, verification, identity",
"author": null,
"author_email": "Prabhjeevan Singh <prabhjeevan@juarapartners.com>",
"download_url": "https://files.pythonhosted.org/packages/50/ef/45fbae219f54ccfc46629fbff0b77098afb6b411cd647468e4759b9f3e76/ekyc-0.1.15.tar.gz",
"platform": null,
"description": "# Juara eKYC Library\n\nJuara eKYC is a Python library for electronic Know Your Customer (eKYC) verification, including document verification, face processing, liveness detection, and face matching.\n\n## Features\n\n- Document verification\n- Face processing\n- Liveness check\n- Face matching\n- Flask-based API for eKYC verification\n\n## Prerequisites\n\n- Python 3.7+\n- OpenCV\n- NumPy\n- scikit-learn\n- deepface\n- paddleocr\n- Flask\n- dlib\n\n## Installation\n\n### For Windows Users:\n\n1. Ensure you have CMake installed. You can download it from [cmake.org](https://cmake.org/download/).\n\n2. Uninstall any previous versions:\n ```\n pip uninstall ekyc\n ```\n\n3. Clear pip cache:\n ```\n pip cache purge\n ```\n\n4. Install the package:\n ```\n pip install path/to/ekyc-0.0.4-py3-none-any.whl\n ```\n\n Note: This will automatically install the correct dlib version for your Python installation.\n\n5. You may need to install PaddleOCR and PaddlePaddle separately:\n ```\n pip install paddlepaddle\n pip install paddleocr\n ```\n\n### For Other Operating Systems:\n\nYou can install the eKYC library using pip:\n\npip install juara_ekyc\n\n\n## Usage\n\nHere's a basic example of how to use the Juara eKYC library:\n\npython\nfrom juara_ekyc import process_id_verification\nresult, message = process_id_verification('path/to/image.jpg')\nprint(f\"Verification result: {result}\")\nprint(f\"Message: {message}\")\n\n## Development\n\n1. Clone the repository:\n ```\n git clone https://github.com/yourusername/juara_ekyc.git\n cd juara_ekyc\n ```\n\n2. Create a virtual environment:\n ```\n python -m venv venv\n source venv/bin/activate # On Windows use `venv\\Scripts\\activate`\n ```\n\n3. Install the development dependencies:\n ```\n pip install -r requirements.txt\n ```\n\n4. Run the tests:\n ```\n python -m unittest discover tests\n ```\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n",
"bugtrack_url": null,
"license": "MIT License Copyright (c) [2024] [PrabhjeevanSingh] Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.",
"summary": "A library for electronic Know Your Customer (eKYC) verification",
"version": "0.1.15",
"project_urls": {
"Bug Tracker": "https://github.com/juaraprabhjeevan/juara_ekyc/issues",
"Homepage": "https://github.com/juaraprabhjeevan/juara_ekyc"
},
"split_keywords": [
"ekyc",
" verification",
" identity"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "487772a95ee0bfd8017a19abb664a31ed8356a7d3da9a3a1bdf4464e3a598f98",
"md5": "15883deb63f452933733341f901dd9a1",
"sha256": "692baa30cba642f94bde5c90896227a99d9eb57b7fe3db524c081cdd1b2c9f8f"
},
"downloads": -1,
"filename": "ekyc-0.1.15-py3-none-any.whl",
"has_sig": false,
"md5_digest": "15883deb63f452933733341f901dd9a1",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<3.13,>=3.9",
"size": 72377419,
"upload_time": "2024-09-05T06:34:32",
"upload_time_iso_8601": "2024-09-05T06:34:32.149420Z",
"url": "https://files.pythonhosted.org/packages/48/77/72a95ee0bfd8017a19abb664a31ed8356a7d3da9a3a1bdf4464e3a598f98/ekyc-0.1.15-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "50ef45fbae219f54ccfc46629fbff0b77098afb6b411cd647468e4759b9f3e76",
"md5": "91ce23c0aaf4666fbf19c0de0c6ff095",
"sha256": "ee471a10088b4497504217f7da68c3b921da7a4d474d42aa7a6c41a76c1ca706"
},
"downloads": -1,
"filename": "ekyc-0.1.15.tar.gz",
"has_sig": false,
"md5_digest": "91ce23c0aaf4666fbf19c0de0c6ff095",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<3.13,>=3.9",
"size": 89453179,
"upload_time": "2024-09-05T06:34:50",
"upload_time_iso_8601": "2024-09-05T06:34:50.403070Z",
"url": "https://files.pythonhosted.org/packages/50/ef/45fbae219f54ccfc46629fbff0b77098afb6b411cd647468e4759b9f3e76/ekyc-0.1.15.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-09-05 06:34:50",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "juaraprabhjeevan",
"github_project": "juara_ekyc",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"requirements": [
{
"name": "Flask",
"specs": [
[
"==",
"2.0.1"
]
]
},
{
"name": "numpy",
"specs": [
[
"==",
"1.21.0"
]
]
},
{
"name": "dlib",
"specs": [
[
"==",
"19.22.0"
]
]
},
{
"name": "deepface",
"specs": [
[
"==",
"0.0.93"
]
]
},
{
"name": "paddleocr",
"specs": [
[
"==",
"2.5.0.3"
]
]
},
{
"name": "scikit-learn",
"specs": [
[
"==",
"0.24.2"
]
]
},
{
"name": "opencv-python-headless",
"specs": [
[
"==",
"4.5.3.56"
]
]
}
],
"lcname": "ekyc"
}
