Upload inference.py

inference.py

@@ -0,0 +1,17 @@
+# inference.py
+import tensorflow as tf
+import numpy as np
+
+# Load the model
+model = tf.keras.models.load_model("SoilNet.keras")
+
+# Define Hugging Face inference interface
+def predict(payload):
+    try:
+        # Expect input format: {"features": [values]}
+        features = np.array(payload["features"]).reshape(1, -1)
+        prediction = model.predict(features)
+        predicted_class = int(np.argmax(prediction, axis=1)[0])  # or use class_names if available
+        return {"prediction": predicted_class}
+    except Exception as e:
+        return {"error": str(e)}