update

app.py

@@ -57,8 +57,10 @@ IMAGE_PROCESS_TRANSFORM = transforms.Compose([
 ])
 
 @spaces.GPU
-def generate_image(ref_image, ref_image2, prompt, height=512, width=512, num_steps=25, guidance_scale=3.5, seed=0, ip_scale=1.0):
-    print(f"ref_image: {ref_image.size}, prompt: {prompt}, height: {height}, width: {width}, num_steps: {num_steps}, guidance_scale: {guidance_scale}, ip_scale: {ip_scale}")
+def generate_image(ref_image, ref_image2=None, prompt="", height=512, width=512, num_steps=25, guidance_scale=3.5, seed=0, ip_scale=1.0):
+    print(f"ref_image: {ref_image.size if ref_image is not None else None}, "
+          f"ref_image2: {ref_image2.size if ref_image2 is not None else None}, "
+          f"prompt: {prompt}, height: {height}, width: {width}, num_steps: {num_steps}, guidance_scale: {guidance_scale}, ip_scale: {ip_scale}")
     with torch.no_grad():
         image_refs = map(torch.stack, [
             [IMAGE_PROCESS_TRANSFORM(i) for i in [ref_image, ref_image2] if i is not None]
@@ -95,7 +97,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         gr.Markdown("""
 ## Character Consistancy Image Generation based on Flux
-- This model is continuously improving until it meets high standards for open-sourcing, currently good enough at generating consistent images of single human subject. 
+- This model is currently only good at generating consistent images of single human subject, multi-subjects and common object are not as satisfactory, but it will improved soon
 """)
 
     with gr.Row():
@@ -141,8 +143,7 @@ with gr.Blocks() as demo:
 ### Tips:
 - Images with human subjects tend to perform better than other categories.
 - Images where the subject occupies most of the frame with a clean, uncluttered background yield improved results.
-- Including multiple subjects of the same category may cause blending issues (this is being improved).
-- Despite these factors, most image inputs still produce reasonable and satisfactory results.
+- Including multiple subjects of the same category may cause blending issues.
 """)    
     # When the button is clicked, pass all inputs to generate_image
     generate_btn.click(