Update app.py

app.py

@@ -277,17 +277,19 @@ css = """
 """
 example = """
 Emotion Description
+
 a photo of a person feeling joyful
+
 a photo of a person feeling sorrowful
+
 a photo of a person feeling enraged
+
 a photo of a person feeling astonished
+
 a photo of a person feeling disgusted
+
 a photo of a person feeling terrified
-a photo of a person feeling thrilled
-a photo of a person feeling nervous
-a photo of a person feeling tranquil
-a photo of a person feeling perplexed
-a photo of a person feeling resolute
+
 ...
                         
 """
@@ -296,6 +298,10 @@ with gr.Blocks(css=css) as demo:
 ### compose new images with visual concepts
 following the algorithm proposed in [*IP-Composer: Semantic Composition of Visual Concepts* by Dorfman et al.](https://arxiv.org/pdf/2502.13951)
 
+#### 1. upload a base image
+#### 2. upload 1-3 concept images
+#### 3. select concept type to extract from each concept image
+
 [[project page](https://ip-composer.github.io/IP-Composer/)] [[arxiv](https://arxiv.org/pdf/2502.13951)]
         """)
         concpet_from_file_1 = gr.State()
@@ -314,30 +320,30 @@ following the algorithm proposed in [*IP-Composer: Semantic Composition of Visua
                     with gr.Accordion("💡 add a new concept 👇", open=False):
                         gr.Markdown("1. upload a file with text variations of your concept (e.g. ask an LLM)")
                         gr.Markdown("2. prefereably with > 100 variations.")
-                        with gr.Accordion("file example for the concept 'emotions'"):
+                        with gr.Accordion("file example for the concept 'emotions'", open=False):
                             gr.Markdown(example)
                         concept_file_1 = gr.File(label="concept variations", file_types=["text"])
                                                     
-                with gr.Tab("concept 2 - optional"):            
+                with gr.Tab("concept 2 (optional)"):            
                     with gr.Group():    
                           concept_image2 = gr.Image(label="Concept Image 2", type="numpy")
                           concept_name2 = gr.Dropdown(concept_options, label="concept 2", value=None, info="concept type")
                     with gr.Accordion("💡 add a new concept 👇", open=False):
                         gr.Markdown("1. upload a file with text variations of your concept (e.g. ask an LLM)")
                         gr.Markdown("2. prefereably with > 100 variations.")
-                        with gr.Accordion("file example for the concept 'emotions'"):
+                        with gr.Accordion("file example for the concept 'emotions'", open=False):
                             gr.Markdown(example)
                         concept_file_2 = gr.File(label="concept variations", file_types=["text"])
                           
                 
-                with gr.Tab("concept 3 - optional"):
+                with gr.Tab("concept 3 (optional)"):
                     with gr.Group(): 
                           concept_image3 = gr.Image(label="Concept Image 3", type="numpy")
                           concept_name3 = gr.Dropdown(concept_options, label="concept 3", value= None, info="concept type")
                     with gr.Accordion("💡 add a new concept 👇", open=False):
                         gr.Markdown("1. upload a file with text variations of your concept (e.g. ask an LLM)")
                         gr.Markdown("2. prefereably with > 100 variations.")
-                        with gr.Accordion("file example for the concept 'emotions'"):
+                        with gr.Accordion("file example for the concept 'emotions'", open=False):
                             gr.Markdown(example)
                         concept_file_3 = gr.File(label="concept variations", file_types=["text"])