add segment checkbox

app.py

@@ -25,7 +25,7 @@ def base64str_to_PILImage(base64str):
     bytesObj = io.BytesIO(base64bytes)
     return ImageOps.exif_transpose(Image.open(bytesObj))
 
-def get_results(image, prompt):
+def get_results(image, prompt,segment):
     threshold = 0.5
     
     # Convert the NumPy array to PIL image
@@ -37,8 +37,12 @@ def get_results(image, prompt):
         base64str = base64.b64encode(output.getvalue()).decode("utf-8")
 
     # Prepare the payload (Adjust this part according to the API requirements)
-    payload = json.dumps({"base64str": base64str, "classes": prompt})
-
+    #payload = json.dumps({"base64str": base64str, "classes": prompt})
+    payload = {
+        "base64str": base64str,
+        "classes": prompt,
+        "segment": "1" if segment else "0"  # 1 if checkbox is selected, 0 if not
+    }
     # Send the request to the API
     response = requests.put(api_key, data=payload)
 
@@ -137,16 +141,18 @@ with gr.Blocks() as demo:
     # Define the output component and add it to the layout
     with gr.Row():
         text_input = gr.inputs.Textbox(label="Prompt")
+    with gr.Row():
+        segment_checkbox = gr.inputs.Checkbox(label="Segment", default=False)
     with gr.Row():
         button = gr.Button("Run")
         
     # Define the event listener that connects the input and output components and triggers the function
-    button.click(fn=get_results, inputs=[image_input, text_input], outputs=output, api_name="get_results")
+    button.click(fn=get_results, inputs=[image_input, text_input, segment_checkbox], outputs=output, api_name="get_results")
     # Add the description below the layout
     gr.Examples(
             fn=get_results,
             examples=examples,
-            inputs=[image_input, text_input],
+            inputs=[image_input, text_input,segment_checkbox],
             outputs=[output]
         )
     gr.Markdown(description_html)