Transcendental (π)
Artificial Intelligence image recognition.
Learn from input data and generate model, predict from previous generated model
Disclaimer
This is testing project purpose so it's currently in development and features are minimal don't juge me :)
Features
- Recognize cats
- Recognize dogs
Install
$ pip install transcendental
Usage
trans-predict
This command allow you to recognize an image passed in argument.
Predict take exactly one argument who is the image to predict
$ trans-predict --help
usage: trans-predict [-h] image
Recognize cat and dogs
positional arguments:
image an image to analyze
optional arguments:
-h, --help show this help message and exit
$ trans-predict ./image.png
trans-train
This command allow you to train your IA.
This command generate models automaticaly used by predict at launch
Currently in development!
Requires
- python 2.7+
- keras
- tensorflow
- Pillow
- h5py
Resources
- https://becominghuman.ai/building-an-image-classifier-using-deep-learning-in-python-totally-from-a-beginners-perspective-be8dbaf22dd8
- https://drive.google.com/drive/folders/1XaFM8BJFligrqeQdE-_5Id0V_SubJAZe
- https://machinelearningmastery.com/save-load-keras-deep-learning-models/
- https://www.quora.com/How-do-artificial-neural-networks-work
- http://torch.ch/blog/2015/11/13/gan.html
1 maintainer
Metadata
1 maintainer
Release files for transcendental 0.5.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| transcendental-0.5.5.tar.gz | 15.7 MB | Without provenance | Details for transcendental-0.5.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| transcendental-0.5.5-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details for transcendental-0.5.5-py2.py3-none-any.whl |
Total release size: 30.7 MB
Release files / transcendental-0.5.5.tar.gz
| Download URL | transcendental-0.5.5.tar.gz |
|---|---|
| Size | 15.7 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
59331289312a434de8c7aa5d2280a1d8392a7907de666ab50d2d9ec26db2839f
|
|
BLAKE2b-256 checksum How to use checksums |
7f7101aa53a7e554c5ce7d78570787afed2d9c43a296b52049247313973e2bc9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / transcendental-0.5.5-py2.py3-none-any.whl
| Download URL | transcendental-0.5.5-py2.py3-none-any.whl |
|---|---|
| Size | 14.9 MB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
0b439fab7022c79ed8d27363a47210d53cdaee4fcfb2cb0e3c87c6be02fd8722
|
|
BLAKE2b-256 checksum How to use checksums |
ebd0d810a59fd8eb349b0fb20149cfd06fdfdeb9b3174c077c92d7f64c67bb2c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for transcendental 0.5.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
