Update app.py

app.py

@@ -275,7 +275,22 @@ css = """
     max-width: 960px;
 }
 """
-
+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
+...
+                        
+"""
 with gr.Blocks(css=css) as demo:
         gr.Markdown(f"""# IP Composer 🌅✚🖌️
 ### compose new images with visual concepts
@@ -292,19 +307,26 @@ following the algorithm proposed in [*IP-Composer: Semantic Composition of Visua
         with gr.Row():
             with gr.Column():
                 base_image = gr.Image(label="Base Image (Required)", type="numpy")
-                with gr.Tab("concept 1"):  
-                  with gr.Row():
+                with gr.Tab("concept 1"):      
                     with gr.Group():
                           concept_image1 = gr.Image(label="Concept Image 1", type="numpy")
                           concept_name1 = gr.Dropdown(concept_options, label="concept 1", value=None, info="concept type")
-                    gr.Markdown("💡 you can use a new concept by uploading a txt/csv file with text variations of your concept")
+                    gr.Markdown("💡 add a new concept 👇") 
+                    with gr.Accordion("example + instrcutions", 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. see file example for the concept 'emotions': ")
+                        gr.Markdown(example)
                     concept_file_1 = gr.File(label="concept variations", file_types=["text"])
                                                     
                 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")
-                    gr.Markdown("💡 you can use a new concept by uploading a txt/csv file with text variations of your concept")  
+                    gr.Markdown("💡 add a new concept 👇") 
+                    with gr.Accordion("example + instrcutions", 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. see file example for the concept 'emotions': ")
+                        gr.Markdown(example)
                     concept_file_2 = gr.File(label="concept variations", file_types=["text"])
                           
                 
@@ -312,7 +334,11 @@ following the algorithm proposed in [*IP-Composer: Semantic Composition of Visua
                     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")
-                    gr.Markdown("💡 you can use a new concept by uploading a txt/csv file with text variations of your concept") 
+                    gr.Markdown("💡 add a new concept 👇") 
+                    with gr.Accordion("example + instrcutions", 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. see file example for the concept 'emotions': ")
+                        gr.Markdown(example)
                     concept_file_3 = gr.File(label="concept variations", file_types=["text"])