https://github.com/rampal-punia/django-object-detection

Django object detection app using yolov5. Upload new custom model or use any of the yolov5 pre-trained model.
https://github.com/rampal-punia/django-object-detection

django django-application dropzonejs machine-learning machine-learning-library object object-detection object-detector python yolov5 yolov5-django

Last synced: about 1 month ago
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Django object detection app using yolov5. Upload new custom model or use any of the yolov5 pre-trained model.

• Host: GitHub
• URL: https://github.com/rampal-punia/django-object-detection
• Owner: rampal-punia
• License: apache-2.0
• Created: 2022-08-04T12:49:46.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2023-12-07T19:23:23.000Z (11 months ago)
• Last Synced: 2024-09-28T16:40:12.895Z (about 2 months ago)
• Topics: django, django-application, dropzonejs, machine-learning, machine-learning-library, object, object-detection, object-detector, python, yolov5, yolov5-django
• Language: Python
• Homepage:
• Size: 6.52 MB
• Stars: 50
• Watchers: 2
• Forks: 23
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: license

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README

        
# Django Object Detection With YoloV5

## Demo of the WebApp

### A project to demonstrate easy integration of YoloV5 in Django WebApp

Note: This is not a full-fledged production ready app though can be scaled to work as one.

## Features of the WebApp

- Create/Edit ImageSets.

- Upload multiple images with dropzonejs to the selected ImageSet.

- Convert uploaded image size to 640 x 640. (For faster detection)

- Upload/update a custom pre-trained model.(If you have offline files of a model)

- YoloV5 models will download upon selection. (Active internet connection required for this step.)

- Detect object on an image with YoloV5/custom pre-trained model.

### Note

An image with the name **default.png** in media folder is required for user-profile. Create media folder and add any image file with this name 'default.png'.

## Steps to use locally

```bash

clone the repo locally

create virtual environment

# install dependencies

pip install django

pip install django-crispy-forms

pip install crispy-bootstrap4

pip install django-cleanup

pip install django-debug-toolbar

pip install celery

pip install yolov5

# migrate

python manage.py migrate

# create super user

python manage.py createsuperuser # (it may show an error page if no 'default.png' in media folder. See note above.)

# run

python manage.py runserver

login

# Login at the web address 127.0.0.1:8000 using the superuser credentials.

Create ImageSet

# create an ImageSet first and then upload images into the ImageSet from ImageSet detail page.

# On images list page click on detect object.

# select a YoloV5 model

# the YoloV5 dependencies and pre-trained model will start downloading.

```

## Apps

- Detectobj

- images

- modelmanager

- users

## Javascript library

- dropzonejs

- ekko-lightbox

## Django starter template used

[DjangoAdvancedBoilerplate](https://github.com/CodingMantras/DjangoAdvancedBoilerplate)