add num_inference_steps

app.py

@@ -71,7 +71,7 @@ concept_options = list(CONCEPTS_MAP.keys())
 
 
 examples = [
-    ['./IP_Composer/assets/objects/mug.png', './IP_Composer/assets/patterns/splash.png', 'patterns (including color)', None, None, None, None, 80, 30, 30, None,1.0,0]
+    ['./IP_Composer/assets/objects/mug.png', './IP_Composer/assets/patterns/splash.png', 'patterns (including color)', None, None, None, None, 80, 30, 30, None,1.0,0, 50]
     
 ]
 
@@ -80,13 +80,13 @@ def generate_examples(base_image,
                       concept_image2, concept_name2,
                       concept_image3, concept_name3,
                       rank1, rank2, rank3, 
-                      prompt, scale, seed):
+                      prompt, scale, seed, num_inference_steps):
     return process_and_display(base_image, 
                       concept_image1, concept_name1,
                       concept_image2, concept_name2,
                       concept_image3, concept_name3,
                       rank1, rank2, rank3, 
-                      prompt, scale, seed)
+                      prompt, scale, seed, num_inference_steps)
 
 
 
@@ -117,7 +117,8 @@ def process_images(
     rank1=10, rank2=10, rank3=10,
     prompt=None, 
     scale=1.0,
-    seed=420
+    seed=420,
+    num_inference_steps=50,
 ):
     """Process the base image and concept images to generate modified images"""
     # Process base image
@@ -186,6 +187,7 @@ def process_images(
         scale=scale, 
         num_samples=1, 
         seed=seed
+        num_inference_steps=num_inference_steps
     )
     
     return modified_images[0]
@@ -196,7 +198,7 @@ def process_and_display(
     concept_image2=None, concept_name2=None,
     concept_image3=None, concept_name3=None,
     rank1=30, rank2=30, rank3=30,
-    prompt=None, scale=1.0, seed=0
+    prompt=None, scale=1.0, seed=0, num_inference_steps=50,
 ):
     if base_image is None:
         raise gr.Error("please upload a base image")
@@ -213,7 +215,7 @@ def process_and_display(
         concept_image2, concept_name2,
         concept_image3, concept_name3,
         rank1, rank2, rank3, 
-        prompt, scale, seed
+        prompt, scale, seed, num_inference_steps
     )
     
     return modified_images
@@ -255,6 +257,7 @@ following the algorithm proposed in [*IP-Composer: Semantic Composition of Visua
             
                 with gr.Accordion("Advanced options", open=False):
                     prompt = gr.Textbox(label="Guidance Prompt (Optional)", placeholder="Optional text prompt to guide generation")
+                    num_inference_steps = gr.Slider(minimum=1, maximum=50, value=50, step=1, label="num steps")
                     with gr.Row():
                         scale = gr.Slider(minimum=0.1, maximum=2.0, value=1.0, step=0.1, label="Scale")
                         randomize_seed = gr.Checkbox(value=True, label="Randomize seed")
@@ -275,7 +278,7 @@ following the algorithm proposed in [*IP-Composer: Semantic Composition of Visua
                 concept_image2, concept_name2,
                 concept_image3, concept_name3,
                 rank1, rank2, rank3, 
-                prompt, scale, seed],
+                prompt, scale, seed, num_inference_steps],
         outputs=[output_image],
         fn=generate_examples,
         cache_examples=False
@@ -292,7 +295,7 @@ following the algorithm proposed in [*IP-Composer: Semantic Composition of Visua
                 concept_image2, concept_name2,
                 concept_image3, concept_name3,
                 rank1, rank2, rank3, 
-                prompt, scale, seed
+                prompt, scale, seed, num_inference_steps
             ],
             outputs=[output_image]
         )