Update app.py

app.py

@@ -61,16 +61,26 @@ def predict(image_np):
     
     return result_pil_img
 
+def predict2(pilimg):
 
+    image_np = pil_image_as_numpy_array(pilimg)
+    return predict2(image_np)
+    
 detection_model = load_model()
-# pil_image = Image.open(image_path)
-# image_arr = pil_image_as_numpy_array(pil_image)
 
-# predicted_img = predict(image_arr)
-# predicted_img.save('predicted.jpg')
+ Specify paths to example images
+example_image_paths = ["test1.jpg"]
+
+# Create a list of example inputs and outputs using a for loop
+example_inputs = [Image.open(path) for path in example_image_paths]
+example_outputs = [predict2(input_image) for input_image in example_inputs]
+
+# Create the Gradio interface with examples using a for loop
+examples = [[example_inputs[i], example_outputs[i]] for i in range(len(example_inputs))]
 
 iface = gr.Interface(fn=predict,
              inputs=gr.Image(label='Upload an expressway image', type="pil"),
              outputs=gr.Image(type="pil"),
-             title='Blue and Yellow Taxi detection using live traffic conditions along expressways (data.gov.sg)'
+             title='Blue and Yellow Taxi detection using live traffic conditions along expressways (data.gov.sg)',
+             example=examples
              ).launch(share=True)