Our project MOODIFY is based on the idea of automating the interaction between the music player and its user by using openCV and other python libraries as humans have a tendency to listen to music in accordance to their mood. So our project would be helpful as it is “smart enough” to sort-out the music based on the current state of emotion the person is having.
At last we are giving Music Market place for minting NFT's .
- It is sometimes difficult for a person to choose which music to listen to from a vast array of available selections .
- While music genre is crucial in shaping and exhibiting social identity, the emotional expression of a song and, more significantly, its emotional impact on the listener is sometimes overlooked in the realm of music preferences .
- Locating NFTs that match a user's mood can be challenging, and searching for them in the marketplace can also be difficult .
- OUR IDEA IS A SYSTEM THAT CAN IDENTIFY THE USER'S FACIAL EXPRESSIONS AND EXTRACT FACIAL LANDMARKS BASED ON THOSE EXPRESSIONS, WHICH MAY THEN BE CATEGORIZED TO DETERMINE THE USER'S SENTIMENT .
- WE WILL BUILD AN APPLICATION THAT BLENDS FRONTEND AND BACKEND TECHNOLOGY TO PROVIDE RAPID RESULTS, ALLOWING USERS TO ACCESS DIFFERENT MUSIC MORE QUICKLY.
- WE ARE BUILDING A MUSICAL NFT MARKETPLACE. BASED ON THE USER'S MOODS WE RECOMMENDED THE MUSICAL NFT’S THAT HE/SHE LIKES MOST .
- MAKING THIS A REAL-TIME APPLICATION, SO THAT ACTUAL USERS CAN USE IT.
- REAL-TIME SONG EXTRACTION FROM A THIRD-PARTY API.
- DEPLOYING THIS APPLICATION ON ANY CLOUD PLATFORM, INCLUDING AZURE, GOOGLE APP ENGINE, AND OTHERS.
- INSTEAD OF RELYING SOLELY ON FACIAL EXPRESSIONS, ADDITIONAL PARAMETERS SUCH AS HEART RATE OR BODY TEMPERATURE MUST BE CONSIDERED FOR ACCURATE DETECTION OF FEAR AND DISGUST MOODS.
- NFTS CAN BE USED TO CREATE UNIQUE FAN EXPERIENCES, SUCH AS OFFERING EXCLUSIVE ACCESS TO CONCERTS, BACKSTAGE PASSES, OR MEET-AND-GREETS.
- Ethereum + Metamask + Solidity + Web3js + Truffle
- Reactjs + vite + Tailwind-css + Spotify Api