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It is a webapp made using python and the cloudinary api which is able to tag images according to its type and also provides media analysis

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CamFind 📸

Link to the app

(https://pratyksha-22-camfind-app-qx0n3o.streamlit.app/)

About

This app can upload, store, and automatically tag images & videos using the Cloudinary API. It has been deployed using streamlit

The app is built with Streamlit where it displays an image gallery that can be filtered by tag, and also shows a Dashboard that analyzes all tags.

Software and Tool Requirements

  1. GithubAccount
  2. VScodeIDE
  3. GitCli
  4. Cloudinary
  5. streamlit

Installation

1.create a virtual environment

conda create -n envname 
conda activate envname 

2.Install the dependencies in your VScode

pip install -r requirements.txt

Configuration

Follow the quick start guide to create a .env file with the CLOUDINARY_URL

https://cloudinary.com/documentation/python_quickstart

CLOUDINARY_URL=cloudinary://<api_key>:<api_secret>@<cloud_name>

Implement the Cloudinary Service

The file cloudinary_service.py contains helper functions to upload, tag, and search images.

Prepare a folder with all the photos you want to upload, and then call the upload_folder()function inside the cloudinary_service.py to upload and tag all images.

Screenshots

ss1

ss2 ss3

Run the App

Run the following code in your VScode to run it locally

streamlit run app.py

About

It is a webapp made using python and the cloudinary api which is able to tag images according to its type and also provides media analysis

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