| Name | hashtagger JSON |
| Version |
0.2.1
JSON |
| download |
| home_page | None |
| Summary | A hashtag generator using TensorFlow and NLTK |
| upload_time | 2024-07-05 12:49:43 |
| maintainer | None |
| docs_url | None |
| author | Meet Jethwa |
| requires_python | None |
| license | MIT |
| keywords |
tagger
tensorflow
nltk
|
| 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.
0.1.4 (2024-03-07)
-------------------
- Added more hashtags to hashtagger library.
0.1.5 (2024-07-05)
-------------------
- Added more hashtags to hashtagger library.
0.2.0 (2024-07-05)
-------------------
- Added more hashtags to hashtagger library.
0.2.1 (2024-07-05)
-------------------
- Removed all nltk and download errors
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