Update app.py

app.py

@@ -46,7 +46,7 @@ def predict(input_image_path, prompt, negative_prompt, controlnet_scale):
     resize_base_image = resize_image_aspect_ratio(base_image)
     generator = torch.manual_seed(0)
     last_time = time.time()
-    prompt = "masterpiece, best quality, monochrome, greyscale, lineart, white background, " + prompt
+    prompt = "masterpiece, best quality, monochrome, greyscale, lineart, white background, star-shaped pupils, " + prompt
     execute_tags = ["realistic", "nose", "asian"]
     prompt = execute_prompt(execute_tags, prompt)
     prompt = remove_duplicates(prompt)        
@@ -100,7 +100,7 @@ class Img2Img:
                 with gr.Column():
                     self.input_image_path = gr.Image(label="Input image", type='filepath')
                     self.prompt = gr.Textbox(label="Prompt", lines=3)
-                    self.negative_prompt = gr.Textbox(label="Negative prompt", lines=3, value="sketch, lowres, error, extra digit, fewer digits, cropped, worst quality,low quality, normal quality, jpeg artifacts, blurry")
+                    self.negative_prompt = gr.Textbox(label="Negative prompt", lines=3, value="nose, asian, realistic, lowres, error, extra digit, fewer digits, cropped, worst quality,low quality, normal quality, jpeg artifacts, blurry")
                     prompt_analysis_button = gr.Button("Prompt analysis")
                     self.controlnet_scale = gr.Slider(minimum=0.4, maximum=1.0, value=0.55, step=0.01, label="Photp fidelity")                 
                     generate_button = gr.Button(value="Generate", variant="primary")