Create app.py

app.py

@@ -0,0 +1,20 @@
+# Import the libraries
+import numpy as np
+import pandas as pd
+from sklearn.preprocessing import LabelEncoder
+from tensorflow.keras.models import load_model # type: ignore
+from tensorflow.keras.preprocessing.image import load_img, img_to_array # type: ignore
+from tensorflow.keras.applications.convnext import preprocess_input # type: ignore
+import gradio as gr
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=make_prediction,           # Function to be called for predictions
+    inputs=gr.Image(type="pil"),  # Input type: Image (PIL format)
+    outputs="html",               # Output type: HTML for formatting
+    title="Amazon arboreal species classification",
+    description="Upload an image to classify the species."
+)
+
+# Launch the Gradio interface
+interface.launch()