READ.md updated

README.md

@@ -1,25 +1,140 @@
-# Instaknown
+# InstaKnow
 
-#### Flutter App Build usig machine Learning model which shows sentiments of instagram user by analysing their captions.
+### [`Front-end By @ketanchoyal`](https://github.com/ketanchoyal)
+### [`Back-end By @namas191297`](https://github.com/namas191297)
 
-#### I've used Provider + Get_it for State Management.
-### MVVM(Model-View-(View)Model) Architecture.
+# Front-end Application
 
-# Screenshots
+Flutter application that allows user to analyze sentiments of other users based on their captions. This application uses a Machine Learning NLP approach to analyze captions and provide positive, negative and neutral scores as the output.
 
-## HomeScreen
+The flutter application uses ```Provider``` + ```Get_it``` for State Management.
 
-<img src="https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/homeScreenDemo.gif" alt="HomeScreen"/>
+ MVVM(Model-View-(View)Model) Architecture has been used.
 
-## App UI Demo
+ ### `Note: In About Page url for server can be changed (because of free version URL may change after some time)`
 
-<img src="https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/UIDemo.gif" alt="UI Demo"/>
+## Screenshots
 
+### HomeScreen
 
-## Public Profile Analyzer
+![Home_Screen](https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/homeScreenDemo.gif)
 
-<img src="https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/public.png" alt="Public"/>
+### App UI Demo
 
-## Private Profile Analyzer
+![App_UI](https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/UIDemo.gif)
 
-<img src="https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/private.png" alt="Private"/>
+### Public Profile Analyzer
+
+![Analyzer](https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/public.png)
+
+### Private Profile Analyzer
+
+![PAnalyzer](https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/private.png)
+
+### Example 
+
+![Example](https://github.com/ketanchoyal/InstaKnow/raw/master/Screenshots/example.png)
+
+# Back-end
+
+InstaKnow is an open-source mobile application that allows you to analyse the sentiments of public and private profiles based on their post captions. 
+
+This repository is the backend/REST API for the application, where all requests from the application are received in the form of a JSON object. After the sentiment analysis is done, and the sentiments are evaluated, these results are sent in the form of JSON back to the application, where they are displayed.
+
+The backend has been made in python, where the REST API is served as a Flask web-application. The web-application  can be hosted temporarily using ngrok or any other viable option.
+
+The ML implementation is that of NLP (Natural Language Processing), where the captions are analysed using the ```Vader Sentiment Analysis``` library. Scores are received in the form of positive, negative, neutral and compound values, after which their mean is sent back to the front-end application where they are displayed.
+
+Public profiles do not require any authentication although if you want to view the sentiments of a private profile, you must provide credentials for an account that can access that private profile (follows it) for authenticated access in order to extract the captions. 
+
+## JSON
+
+As mentioned above, this repo is a REST API that communicates using JSON objects.
+
+**JavaScript Object Notation (JSON)** is an open-standard file format that uses human-readable text to transmit data objects consisting of attribute?value pairs and array data types (or any other serializable value). It is a very common data format, with a diverse range of applications. Such as serving as replacement for XML in AJAX systems.
+
+An example:
+
+```json
+{
+  "squadName": "Super hero squad",
+  "homeTown": "Metro City",
+  "formed": 2016,
+  "secretBase": "Super tower",
+  "active": true
+}
+```
+
+## Data Format
+
+The format in which data is transferred can be seen as follows:
+
+### Application to Server :
+
+* Public profile
+
+```json
+{
+  "type":"Public",
+  "login_id":"some_public_username"
+}
+```
+
+* Private profile
+
+```json
+{
+  "type":"Private",
+  "login_id":"some_private_username",
+  "login_username":"username_for_authentication",
+  "password":"password_for_authentication"
+}
+```
+
+### Server to Application:
+
+* Success:
+
+```json
+{
+  "type":"Success",
+  "Value":result,
+  "Picture":profile_picture_link,
+  "Name":full_name_of_profile
+}
+```
+
+* Fail:
+
+```json
+{
+  "type":"Fail",
+  "Value":error_message,
+}
+```
+
+## Installation and Execution
+
+Download or clone the repository in a directory and cd into folder containing the file ```app.py```.
+
+* Set the FLASK environment variable FLASK_APP to the name of the python file as follows in the terminal (for Windows):
+
+
+```python
+set FLASK_APP=app.py 
+```
+
+* Run the flask app using the following command:
+
+```python
+flask run 
+```
+
+## Prospective Changes
+
+* Adding encryption to ensure user security while analyzing private profiles
+
+* Analysis based on comments of other followers on the user's posts
+* Permanent deployment as a web-service on platforms like AWS instead of using ngrok.
+
+* Checking policies and ensuring that publishing this application to the playstore/appstore should not cause instagram policy-violation due to web-scraping.