Create app.py

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+
+learn = load_learner('resnet.pkl')
+
+categories = ('Leão', 'Tigre')
+
+# Function to classify the image using the selected model
+def classify_image(img):
+    _, _, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# Define input and output components
+image = gr.Image()
+label = gr.Label()
+
+# Examples for testing
+examples = ['Lion.jpg','Tiger.jpg','L2.jpeg','T2.jpg','P1.png','T3.png','king.png']
+
+# Create Gradio Interface
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+
+# Launch the Gradio interface
+intf.launch(inline=False)