Abstract:

In this project we are detecting depression from users post, user can upload post in the form of text file, image file or audio file, this project can help peoples who are in depression by sending motivated messages to them. Now-a-days peoples are using online post services to interact with each other compare to human to human interaction. So by analysing users post this application can detect depression and send motivation messages to them. Administrator of this application will send motivation messages to all peoples who are in depression. To detect depression we are using SVM (support vector machine) algorithm which analyse users post and give result as negative or positive. If users express depression words in post then SVM detect it as a negative post else positive post.

Existing System:-

• detecting depression from users post, user can upload post in the form of text file, image file or audio file, this project can help peoples who are in depression by sending motivated messages to them. Now-a-days peoples are using online post services to interact with each other compare to human to human interaction.
• we aim to analyze Facebook data to  detect any factors that may reflect the depression of rel- evant Facebook’s users. Various machine learning techniques are employed for such purpose. Considering the key objective of this study, the following are subsequent research challenges addressed in paper.
• As users express their feeling as a post or comments in the Face-book platform, sometimes their posts and comments refer to as emotional state such as ‘joy’, ‘sadness’, ‘fear’, ‘anger’, or ‘surprise’ .

Proposed System :-

• To implement this project we are using python Speech Recognition API which will read text from audio files and then SVM will analyse that text to detect depression, user can also upload images via post and python Tesseract OCR (Optical Character Recognition) API can read text from uploaded image and then SVM will detect depression from that text, User can upload post in text file also.

        Advantages

• Security
•  Communication .

SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10

HARDWARE REQUIREMENTS:

 Processor : Core I3
 RAM Capacity : 2 GB
 Hard Disk : 250 GB
 Monitor : 15″ Color
 Mouse : 2 or 3 Button Mouse
 Key Board : Windows 08/10