Initial Commit

model

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+import gradio as gr
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+import numpy as np
+
+# Load the model
+model = load_model('best_model.h5')
+
+def classify_image(inp):
+    inp = inp.reshape((-1, 224, 224, 3))
+    inp = preprocess_input(inp)
+    prediction = model.predict(inp).flatten()
+    return {f"Class {i}": float(prediction[i]) for i in range(2)}
+
+image = gr.inputs.Image(shape=(224, 224))
+label = gr.outputs.Label(num_top_classes=2)
+
+gr.Interface(fn=classify_image, inputs=image, outputs=label, capture_session=True).launch()