Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/josugoar/digit-recognizer
Digit recognizer full stack web app and classifier
https://github.com/josugoar/digit-recognizer
flask jquery opencv scikit-learn
Last synced: 14 days ago
JSON representation
Digit recognizer full stack web app and classifier
- Host: GitHub
- URL: https://github.com/josugoar/digit-recognizer
- Owner: josugoar
- License: gpl-3.0
- Created: 2020-01-21T20:24:34.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2024-12-15T20:19:13.000Z (about 1 month ago)
- Last Synced: 2024-12-26T06:13:08.511Z (21 days ago)
- Topics: flask, jquery, opencv, scikit-learn
- Language: Jupyter Notebook
- Homepage:
- Size: 8.83 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING
- License: LICENSE
Awesome Lists containing this project
README
# digit-recognizer
HTML, CSS (SCSS/Sass) and JavaScript (jQuery) interactve and responsive front-end UI on top of a Python (Flask, Flask-RESTful, Flask-Caching, Flask-FlatPages, Flask-SQLAlchemy) back-end API and database*, implementing Python (numpy, sklearn, opencv) machine learning model building** and image recognition preprocessing*** via asyncronous encoded requests. Integrated with Git source control.
* \* Database automatically clears itself up only when the application is booted, therefore it is not adviced to delete stored files whilist the processes are still running.
* ** Predictions are carried out by analyzing individual pixels, which might negatively impact accuracy. More advanced techniques (hog features, stroke sequence...) would result in improved performance.
* *** Preprocessing does not scale image with stroke width, which leads to poorer results as the image size increases.
Popup screen |Prediction result
:---------------------------------------:|:---------------------------------------:
|
## Installation
1. Install [Python >= 3.6](https://www.python.org/downloads/)
2. Install package manager [pip](https://pip.pypa.io/en/stable/)
3. Install [virtualenv](https://virtualenv.pypa.io/en/latest/userguide/)
```sh
$ pip install virtualenv
```
4. Create an environment
```sh
$ virtualenv ENV
```
5. Activate the environment
```sh
(Posix)
$ source /path/to/ENV/bin/activate
```
```sh
(Windows)
$ \path\to\ENV\Scripts\activate
```
6. Install [requirements.txt](requirements.txt)
```sh
$ /path/to/ENV/bin/pip install -r requirements.txt
```
## Usage
1. Run [run.py](run.py) **in root**
```sh
$ python run.py
```
2. Open localhost port server link
See [info.html](src/static/pages/info.html) for further details.