https://github.com/omonimus1/plant_classification

🌿 Flower Classifier implementation and Django Web App with integrated ML model.
https://github.com/omonimus1/plant_classification

cnn-classification cnn-keras django flutter honours-project plant-classification tensorflow

Last synced: 2 months ago
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🌿 Flower Classifier implementation and Django Web App with integrated ML model.

• Host: GitHub
• URL: https://github.com/omonimus1/plant_classification
• Owner: omonimus1
• Created: 2021-11-12T16:46:47.000Z (over 3 years ago)
• Default Branch: development
• Last Pushed: 2022-09-05T06:21:54.000Z (over 2 years ago)
• Last Synced: 2024-05-02T02:38:52.150Z (about 1 year ago)
• Topics: cnn-classification, cnn-keras, django, flutter, honours-project, plant-classification, tensorflow
• Language: Jupyter Notebook
• Homepage: https://linktr.ee/davidepollicino
• Size: 2.13 GB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 8
• Metadata Files:
  • Readme: README.md

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README

        
# Flower Classifier 🍃

[![Test](https://github.com/omonimus1/plant_classification/actions/workflows/test.yml/badge.svg)](https://github.com/omonimus1/plant_classification/actions/workflows/test.yml)

[![codecov](https://codecov.io/gh/omonimus1/plant_classification/branch/dev/graph/badge.svg?token=MXVI6OEXK9)](https://codecov.io/gh/omonimus1/plant_classification)

The current repository contains Davide Pollicino' Honours Project. The project (still under evolution), is the result of three research questions:

* What are possible approaches to feature enginnering for the implementation of a classifier able to distinguish flower variants incredibly similar between them, even at differnt life stages and growth locations;

* Which CNN architecture would offer best performances 

* Is is possible to integrate a machine learning model within a django App, without that this model would first be deployed in a cloud service and exploses via endpoint? 

## Technologies

       

![GitHub Actions](https://img.shields.io/badge/github%20actions-%232671E5.svg?style=for-the-badge&logo=githubactions&logoColor=white)

![CodeCov](https://img.shields.io/badge/codecov-%23ff0077.svg?style=for-the-badge&logo=codecov&logoColor=white)

## Web application functionalities

The machine learning model, is the the integrated and used in a Django Web APP, where user are able to:

* Classify a flower

* Leave a feedback related to the prediction

* Save a prediction as favourite

* Register, Login, and gets the user's favourite position. 

## Apply for a mentorship session with me (get a 7 days free trial)

  

#### How to run the project

```

# create virtual environemnt

python3 -m venv venv

# install project requirements

source venv/bin/activate

pip3 install -r requirements.txt

# run migrations

python3 manage.py makemigrations

python3 manage.py migrate

# create superuser

python3 manage.py creatersuper

# run application

python3 manage.py runserver

```

(Note: manage.py may be located inside the webappClassifier folder :) )

#### Coding style checks adopted

* Coding style: Black

* Python Lint: Flake8, flake8-todos

* mypy (for english type checking)

```

# format folder

black folder_name

# Remote all white spaces from project files

trim .

# Format file to improve syntax in according to flake8 (yes -> 2 times --aggressive)

autopep8 --in-place --aggressive --aggressive filename.py

```