Update app.py

app.py

@@ -62,6 +62,17 @@ def on_queue_update(update):
         for log in update.logs:
            print(log["message"])
 
+
+
+def get_status(flower_name):
+    """Return the endangerment status of a given flower name."""
+    # Normalize input for dictionary lookup
+    normalized_name = flower_name.title()
+    return flowers_endangerment.get(normalized_name, "Flower not found in database.")
+
+
+
+
 # Main function to process the uploaded image
 def process_image(img):
     # Classify the image
@@ -71,7 +82,10 @@ def process_image(img):
     # Get Wikipedia link
     wiki_url = search_terms_wikipedia.get(predicted_class, "No Wikipedia entry found.")
     
-    # Generate artistic interpretation by calling the Flux API
+    # Get endangerment status
+    endangerment_status = get_status(predicted_class)
+
+    # Generate artistic interpretation
     result = fal_client.subscribe(
         "fal-ai/flux/schnell",
         arguments={
@@ -82,21 +96,24 @@ def process_image(img):
         on_queue_update=on_queue_update,
     )
     
-    # Get the generated image
+    # Retrieve image
     image_url = result['images'][0]['url']
     response = requests.get(image_url)
     generated_image = Image.open(io.BytesIO(response.content))
     
-    return classification_results, generated_image, wiki_url
+    return classification_results, generated_image, wiki_url, endangerment_status
+
 
 # Function to clear all outputs
 def clear_outputs():
     return {
         label_output: None,
         generated_image: None,
-        wiki_output: None
+        wiki_output: None,
+        status_output: None  # ← NEW
     }
 
+
 # Load the AI model
 learn = load_learner('resnet50_30_categories.pkl')
 
@@ -107,33 +124,35 @@ with gr.Blocks() as demo:
         input_image = gr.Image(height=230, width=230, label="Upload Image for Classification", type="pil")
     
     # Output section
+   # Output section
     with gr.Row():
         with gr.Column():
             label_output = gr.Label(label="Classification Results")
             wiki_output = gr.Textbox(label="Wikipedia Article Link", lines=1)
+            status_output = gr.Textbox(label="Endangerment Status", lines=1)  # ← NEW
         generated_image = gr.Image(label="AI Generated Interpretation")
-    
+
     # Add example images using local paths
     gr.Examples(
-        examples=example_images,
-        inputs=input_image,
-        examples_per_page=6,
-        fn=process_image,
-        outputs=[label_output, generated_image, wiki_output]
-    )
-    
-    # Set up what happens when an image is uploaded or removed
+    examples=example_images,
+    inputs=input_image,
+    examples_per_page=6,
+    fn=process_image,
+    outputs=[label_output, generated_image, wiki_output, status_output]  # ← UPDATED
+)
+
     input_image.change(
         fn=process_image,
         inputs=input_image,
-        outputs=[label_output, generated_image, wiki_output]
-    )
-    
+        outputs=[label_output, generated_image, wiki_output, status_output]  # ← UPDATED
+)
+
     input_image.clear(
         fn=clear_outputs,
         inputs=[],
-        outputs=[label_output, generated_image, wiki_output]
-    )
+        outputs=[label_output, generated_image, wiki_output, status_output]  # ← UPDATED
+)
+
 
 # Start the application
 demo.launch(inline=False)