Added app.py, sample sound recordings and readme.

README.md

@@ -1,13 +1 @@
----
-title: Music Genre Classifier
-emoji: 🏆
-colorFrom: pink
-colorTo: pink
-sdk: gradio
-sdk_version: 4.7.1
-app_file: app.py
-pinned: false
-license: apache-2.0
----
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+import librosa
+from transformers import pipeline
+
+pipe = pipeline("audio-classification", model="Shamik/whisper-base.en-finetuned-gtzan")
+
+title = """Music Genre Classifier"""
+description = """
+Next time you think of how Shazam <img src="shzam.png" width=200px> finds the name of the song,
+well it might certainly be classifying the genre of the music too. This tool classifies music based
+on pre-defined genre from the [GTZAN](https://huggingface.co/datasets/marsyas/gtzan) dataset, 
+which contains music from the following genres:
+`blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, and rock`.
+"""
+
+def classify_audio(filepath):
+    audio, sampling_rate = librosa.load(filepath, sr=16_000)
+    preds = pipe(audio)
+    outputs = {}
+    for p in preds:
+        outputs[p["label"]] = p["score"]
+    return outputs
+
+
+label = gr.outputs.Label()
+
+demo = gr.Interface(fn=classify_audio,
+                     inputs=gr.Audio(type="filepath"),
+                       outputs=label,
+                       title=title,
+                       description=description,
+                         examples=[["song1.ogg"], ["song2.ogg"], ["song3.ogg"], ["song4.ogg"]],)
+demo.launch()