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app.py

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+import gradio as gr
+import numpy as np
+import tensorflow as tf
+from PIL import Image
+
+# LOAD MODEL (.h5) ✅
+model = tf.keras.models.load_model("lite_model.h5", compile=False)
+
+# LABELS
+class_names = [
+    "Didgeridoo", "Tambourine", "Xylophone", "acordian", "alphorn",
+    "bagpipes", "banjo", "bongo drum", "casaba", "castanets",
+    "clarinet", "clavichord", "concertina", "drums", "dulcimer",
+    "flute", "guiro", "guitar", "harmonica", "harp",
+    "marakas", "ocarina", "piano", "saxaphone", "sitar",
+    "steel drum", "trombone", "trumpet", "tuba", "violin"
+]
+
+IMG_SIZE = (224, 224)
+
+def preprocess_image(image):
+    image = image.convert("RGB")
+    image = image.resize(IMG_SIZE)
+    image = np.array(image) / 255.0
+    image = np.expand_dims(image, axis=0)
+    return image
+
+def predict(image):
+    img = preprocess_image(image)
+    preds = model.predict(img)[0]
+    return {class_names[i]: float(preds[i]) for i in range(len(class_names))}
+
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=3),
+    title="🎵 Musical Instrument Classifier",
+    description="Upload an image to predict the instrument",
+)
+
+interface.launch()

labels.txt

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+Didgeridoo
+Tambourine
+Xylophone
+acordian
+alphorn
+bagpipes
+banjo
+bongo drum
+casaba
+castanets
+clarinet
+clavichord
+concertina
+drums
+dulcimer
+flute
+guiro
+guitar
+harmonica
+harp
+marakas
+ocarina
+piano
+saxaphone
+sitar
+steel drum
+trombone
+trumpet
+tuba
+violin

lite_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a0289284e1aebe443c99970f0595da798db889931384222fca2e2d11825be90d
+size 105276552

requirements.txt

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+tensorflow
+gradio
+numpy
+Pillow