Create app.py

app.py

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+import gradio as gr
+from fastai.learner import load_learner
+from PIL import Image
+
+# Load the learner
+learn_inf = load_learner("LuisCe/Practica03")
+
+# Define the prediction function
+def predict_image(img):
+    # Convert the PIL image to a format that fastai expects
+    img_fastai = Image.fromarray(img.astype('uint8'), 'RGB')
+    # Make prediction
+    pred, _, _ = learn_inf.predict(img_fastai)
+    # Return prediction
+    return pred
+
+# Create Gradio interface
+gr.Interface(predict_image, 
+              inputs="image", 
+              outputs="text", 
+              title="Grape Segmentation",
+              description="Segment grapes in the image.",
+              theme="compact",
+              allow_flagging=False).launch()