app.py

# app.py

import gradio as gr
import librosa
import numpy as np

def estimate_genre(filepath):
    print(f"[DEBUG] Filepath received: {filepath}")

    try:
        y, sr = librosa.load(filepath, duration=30)
    except Exception as e:
        return {"Error": f"Failed to load audio: {str(e)}"}

    try:
        # Tempo
        tempo_array, _ = librosa.beat.beat_track(y=y, sr=sr)
        tempo = float(tempo_array)

        # Spectral centroid (brightness)
        centroid = librosa.feature.spectral_centroid(y=y, sr=sr)
        centroid_mean = float(np.mean(centroid))
        centroid_std = float(np.std(centroid))

        # Chroma
        chroma = librosa.feature.chroma_stft(y=y, sr=sr)
        chroma_mean = float(np.mean(chroma))
        chroma_std = float(np.std(chroma))

        # Zero crossing rate
        zcr = librosa.feature.zero_crossing_rate(y)
        zcr_mean = float(np.mean(zcr))

        # RMS (energy)
        rms = librosa.feature.rms(y=y)
        rms_mean = float(np.mean(rms))

    except Exception as e:
        return {"Error": f"Feature extraction failed: {str(e)}"}

    # Heuristic genre rules (updated)
    if tempo > 140 and centroid_mean > 2500 and rms_mean > 0.05:
        genre = "Electronic / Dance"
    elif tempo < 90 and chroma_mean < 0.3 and zcr_mean > 0.1:
        genre = "Hip Hop / Trap"
    elif 100 < tempo < 130 and centroid_mean > 2200 and chroma_std > 0.5:
        genre = "Pop / Rock"
    elif centroid_mean < 1800 and chroma_mean > 0.9 and rms_mean < 0.05:
        genre = "Jazz / Soul"
    else:
        genre = "Unknown"

    return {
        "Predicted Genre": genre,
        "Tempo (BPM)": round(float(tempo), 1),
        "Brightness (Centroid Mean)": round(centroid_mean, 1),
        "Brightness (Centroid Std)": round(centroid_std, 1),
        "Chroma Mean": round(chroma_mean, 3),
        "Chroma Std": round(chroma_std, 3),
        "Zero Crossing Rate": round(zcr_mean, 4),
        "RMS Energy": round(rms_mean, 4),
    }

gr.Interface(
    fn=estimate_genre,
    inputs=gr.Audio(type="filepath", label="Upload audio file"),
    outputs=gr.JSON(),
    title="🎶 Smarter Genre Estimator",
    description="Estimates genre based on tempo, brightness, energy, and harmonic content using librosa features."
).launch()