updated demo to create a single image, and changed order of inputs

app.py

@@ -67,11 +67,11 @@ ip_model = get_ip_model()
 app = FaceAnalysis(name="buffalo_l", providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
 app.prepare(ctx_id=0, det_size=(640, 640), det_thresh=0.2)
 
-def generate_images(img_filepath, prompt, n_images=3,
+def generate_images(prompt, img_filepath,
                     negative_prompt="monochrome, lowres, bad anatomy, worst quality, low quality, blurry",
                     img_prompt_scale=0.5,
                     num_inference_steps=30,
-                    seed=None):
+                    seed=None, n_images=1):
     print(prompt)
     image = cv2.imread(img_filepath)
     faces = app.get(image)
@@ -95,9 +95,8 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             demo_inputs = []
-            demo_inputs.append(gr.Image(type='filepath', label='image prompt'))
             demo_inputs.append(gr.Textbox(label='text prompt', value='headshot of a man, green moss wall in the background'))
-            demo_inputs.append(gr.Slider(maximum=3, minimum=1, value=3, step=1, label='number of images'))
+            demo_inputs.append(gr.Image(type='filepath', label='image prompt'))
             with gr.Accordion(label='Advanced options', open=False):
                 demo_inputs.append(gr.Textbox(label='negative text prompt', value="monochrome, lowres, bad anatomy, worst quality, low quality, blurry"))
                 demo_inputs.append(gr.Slider(maximum=1, minimum=0, value=0.5, step=0.05, label='image prompt scale'))
@@ -113,6 +112,6 @@ with gr.Blocks() as demo:
         'linkedin profile picture of a macdonalds worker',
         'LinkedIn profile picture of a beautiful man dressed in a suit, huge explosion in the background',
         ]
-    gr.Examples(sample_prompts, inputs=demo_inputs[1], label='Sample prompts')
+    gr.Examples(sample_prompts, inputs=demo_inputs[0], label='Sample prompts')
 
 demo.launch(share=True, debug=True)