Name | hashtagger JSON |
Version |
0.1.2
JSON |
| download |
home_page | |
Summary | A hashtag generator using tensorflow and nltk |
upload_time | 2024-03-07 06:44:19 |
maintainer | |
docs_url | None |
author | Meet Jethwa |
requires_python | |
license | MIT |
keywords |
tagger
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
HASHTAGGER
===========
To generate tags for images using TensorFlow and OpenCV.
Using hashtagger, all of this can be done in just a few lines of code.
Installation
------------
You can install hashtagger using pip::
pip install hashtagger
Usage
-----
Here's an example of how to use hashtagger to generate tags for images::
from hashtagger import hashtagger
# Create an instance of YourLibrary
your_library = hashtagger()
# Specify the path to the image you want to process
image_path = "" # Replace with the path to your image
try:
# Use the recognize_objects method to recognize objects in the image
decoded_predictions = your_library.recognize_objects(image_path)
# Use the generate_tags method to generate tags for the recognized objects
tags = your_library.generate_tags(decoded_predictions)
print("Recognized objects and tags:")
for tag in tags:
print(tag)
except Exception as e:
print(f"An error occurred: {e}")
License
-------
This project is licensed under the MIT License - see the LICENSE.txt file for details.
Changelog
==========
0.1.1 (2023-10-09)
-------------------
- Added Initial release of the hashtagger library.
Raw data
{
"_id": null,
"home_page": "",
"name": "hashtagger",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "tagger",
"author": "Meet Jethwa",
"author_email": "meetjethwa3@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/1e/9e/c370a5e9c1c99a0878073c6d16f3ef6971473043287380b3e696f8981944/hashtagger-0.1.2.tar.gz",
"platform": null,
"description": "HASHTAGGER\r\n===========\r\n\r\nTo generate tags for images using TensorFlow and OpenCV.\r\n\r\nUsing hashtagger, all of this can be done in just a few lines of code.\r\n\r\nInstallation\r\n------------\r\n\r\nYou can install hashtagger using pip::\r\n\r\n pip install hashtagger\r\n\r\nUsage\r\n-----\r\n\r\nHere's an example of how to use hashtagger to generate tags for images::\r\n\r\n from hashtagger import hashtagger\r\n\r\n # Create an instance of YourLibrary\r\n your_library = hashtagger()\r\n\r\n # Specify the path to the image you want to process\r\n image_path = \"\" # Replace with the path to your image\r\n\r\n try:\r\n # Use the recognize_objects method to recognize objects in the image\r\n decoded_predictions = your_library.recognize_objects(image_path)\r\n\r\n # Use the generate_tags method to generate tags for the recognized objects\r\n tags = your_library.generate_tags(decoded_predictions)\r\n\r\n print(\"Recognized objects and tags:\")\r\n for tag in tags:\r\n print(tag)\r\n\r\n except Exception as e:\r\n print(f\"An error occurred: {e}\")\r\n\r\nLicense\r\n-------\r\n\r\nThis project is licensed under the MIT License - see the LICENSE.txt file for details.\r\n\r\n\r\nChangelog\r\n==========\r\n\r\n0.1.1 (2023-10-09)\r\n-------------------\r\n- Added Initial release of the hashtagger library.\r\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "A hashtag generator using tensorflow and nltk",
"version": "0.1.2",
"project_urls": null,
"split_keywords": [
"tagger"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "8b2df62a6c611ea66553362873fbda877fe36a5b6cf5ca61712c87298d59e074",
"md5": "38e41f5e0a5aebf04f16699a4a3a7c89",
"sha256": "886f2b8d4d276715d127739adcec8ae33b046777e55182194f1cac8bfa27c440"
},
"downloads": -1,
"filename": "hashtagger-0.1.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "38e41f5e0a5aebf04f16699a4a3a7c89",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 2639,
"upload_time": "2024-03-07T06:44:17",
"upload_time_iso_8601": "2024-03-07T06:44:17.059641Z",
"url": "https://files.pythonhosted.org/packages/8b/2d/f62a6c611ea66553362873fbda877fe36a5b6cf5ca61712c87298d59e074/hashtagger-0.1.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "1e9ec370a5e9c1c99a0878073c6d16f3ef6971473043287380b3e696f8981944",
"md5": "306b6d905f9a2aa48b3a957d50686977",
"sha256": "537b150ab6ae15c1567816ef93b378128424747cb6877acec87cea7a890c24f7"
},
"downloads": -1,
"filename": "hashtagger-0.1.2.tar.gz",
"has_sig": false,
"md5_digest": "306b6d905f9a2aa48b3a957d50686977",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 3616,
"upload_time": "2024-03-07T06:44:19",
"upload_time_iso_8601": "2024-03-07T06:44:19.398653Z",
"url": "https://files.pythonhosted.org/packages/1e/9e/c370a5e9c1c99a0878073c6d16f3ef6971473043287380b3e696f8981944/hashtagger-0.1.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-03-07 06:44:19",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "hashtagger"
}