|
|
import gradio as gr |
|
|
from deepface import DeepFace |
|
|
import random |
|
|
|
|
|
|
|
|
playlists = { |
|
|
"happy": ["Happy - Pharrell Williams", "Can't Stop the Feeling - Justin Timberlake", "Good Vibrations - The Beach Boys"], |
|
|
"sad": ["Someone Like You - Adele", "Fix You - Coldplay", "Stay With Me - Sam Smith"], |
|
|
"angry": ["Break Stuff - Limp Bizkit", "Killing In The Name - Rage Against The Machine", "Duality - Slipknot"], |
|
|
"surprise": ["Surprise Yourself - Jack Garratt", "Suddenly I See - KT Tunstall", "Unexpected - Anna Clendening"], |
|
|
"fear": ["Fear of the Dark - Iron Maiden", "Disturbia - Rihanna", "Creep - Radiohead"], |
|
|
"disgust": ["Dirty Laundry - Don Henley", "Toxic - Britney Spears", "Bad Blood - Taylor Swift"], |
|
|
"neutral": ["Let It Be - The Beatles", "Imagine - John Lennon", "Bohemian Rhapsody - Queen"] |
|
|
} |
|
|
|
|
|
def analyze_mood(image): |
|
|
try: |
|
|
analysis = DeepFace.analyze(image, actions=['emotion'], enforce_detection=False) |
|
|
dominant_emotion = analysis[0]['dominant_emotion'] |
|
|
recommended_playlist = playlists.get(dominant_emotion, playlists["neutral"]) |
|
|
return f"Detected Mood: {dominant_emotion.capitalize()}\n\nRecommended Playlist:\n- " + "\n- ".join(random.sample(recommended_playlist, 3)) |
|
|
except Exception as e: |
|
|
return f"An error occurred: {str(e)}" |
|
|
|
|
|
iface = gr.Interface( |
|
|
fn=analyze_mood, |
|
|
inputs=gr.Image(type="filepath", label="Upload Your Selfie"), |
|
|
outputs="text", |
|
|
title="MoodMuse 🎵", |
|
|
description="Upload a selfie, and MoodMuse will analyze your facial expression to recommend a playlist that matches your mood." |
|
|
) |
|
|
|
|
|
iface.launch() |
|
|
|
