Update app.py

app.py

@@ -2,9 +2,8 @@ import streamlit as st
 from io import BytesIO
 import base64
 import os
-from PIL import Image
 from replicate import Client
-
+from PIL import Image
 
 illuse = Client(api_token=os.getenv('REPLICATE'))
 model_name = "andreasjansson/illusion:75d51a73fce3c00de31ed9ab4358c73e8fc0f627dc8ce975818e653317cb919b"
@@ -13,36 +12,37 @@ example_image = "https://replicate.delivery/pbxt/hHJNV9QteKX8DK2ckkUeXsqbEIKNGFX
 def generate(prompt, negative_prompt, qr_content, pattern_image, num_inference_steps, guidance_scale, width, height, seed, num_outputs, controlnet_conditioning_scale, border, qrcode_background):
     try:
         inputs = {
-                'prompt': prompt,
-                'negative_prompt': negative_prompt,
-                'qr_code_content': qr_content,
-                'num_inference_steps': num_inference_steps,
-                'guidance_scale': guidance_scale,
-                'width': width,
-                'height': height,
-                'seed': seed,
-                'num_outputs': num_outputs,
-                'controlnet_conditioning_scale': controlnet_conditioning_scale,
-                'border': border,
-                'qrcode_background': qrcode_background
-            }
+            'prompt': prompt,
+            'negative_prompt': negative_prompt,
+            'qr_code_content': qr_content,
+            'num_inference_steps': num_inference_steps,
+            'guidance_scale': guidance_scale,
+            'width': width,
+            'height': height,
+            'seed': seed,
+            'num_outputs': num_outputs,
+            'controlnet_conditioning_scale': controlnet_conditioning_scale,
+            'border': border,
+            'qrcode_background': qrcode_background
+        }
         if pattern_image is not None:
             image = Image.open(pattern_image)
             image_bytes = BytesIO()
             image.save(image_bytes, format='PNG')
             inputs['image'] = image_bytes
 
-        result = illuse.run(
+        result_uris = illuse.run(
             model_name,
             input=inputs
         )
-        return result
+
+        return result_uris
+
     except Exception as e:
         print(e)
         st.error(str(e))
         return
 
-        
 st.title("Illusion Diffusion Fast Demo powered by replicate")
 
 prompt = st.text_input("Prompt")
@@ -65,9 +65,9 @@ border = st.slider("border", min_value=0, max_value=4, step=1, value=4)
 qrcode_background = st.selectbox("qrcode_background", options=['gray', 'white'], index=1)
 
 if st.button("Run"):
-    result = generate(prompt, negative_prompt, qr_content, pattern_input, num_inference_steps, guidance_scale, width, height, seed, num_outputs, controlnet_conditioning_scale, border, qrcode_background)
-    if result:
-        st.image(result[0]['output'])
-
+    result_uris = generate(prompt, negative_prompt, qr_content, pattern_input, num_inference_steps, guidance_scale, width, height, seed, num_outputs, controlnet_conditioning_scale, border, qrcode_background)
+    for uri in result_uris:
+        st.image(uri)
 
 st.image(example_image, caption='Example Image', use_column_width=True)
+st.markdown("powered with ❤️ by aiconvert")