Update app.py

app.py

@@ -6,51 +6,8 @@ import os
 
 from utils.gradio_helpers import parse_outputs, process_outputs
 
-inputs = []
-inputs.append(gr.Textbox(
-    label="Prompt", info='''Describe the subject. Include clothes and hairstyle for more consistency.'''
-))
-
-inputs.append(gr.Textbox(
-    label="Negative Prompt", info='''Things you do not want to see in your image'''
-))
-
-inputs.append(gr.Image(
-    label="Subject", type="filepath"
-))
-
-inputs.append(gr.Slider(
-    label="Number Of Outputs", info='''The number of images to generate.''', value=3,
-    minimum=1, maximum=20, step=1,
-))
-
-inputs.append(gr.Slider(
-    label="Number Of Images Per Pose", info='''The number of images to generate for each pose.''', value=1,
-    minimum=1, maximum=4, step=1,
-))
-
-inputs.append(gr.Checkbox(
-    label="Randomise Poses", info='''Randomise the poses used.''', value=True
-))
-
-inputs.append(gr.Dropdown(
-    choices=['webp', 'jpg', 'png'], label="output_format", info='''Format of the output images''', value="webp"
-))
-
-inputs.append(gr.Number(
-    label="Output Quality", info='''Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.''', value=80
-))
-
-inputs.append(gr.Number(
-    label="Seed", info='''Set a seed for reproducibility. Random by default.''', value=None
-))
-
 names = ['prompt', 'negative_prompt', 'subject', 'number_of_outputs', 'number_of_images_per_pose', 'randomise_poses', 'output_format', 'output_quality', 'seed']
 
-outputs = []
-outputs.append(gr.Gallery())
-
-expected_outputs = len(outputs)
 def predict(request: gr.Request, *args, progress=gr.Progress(track_tqdm=True)):
     headers = {'Content-Type': 'application/json'}
 
@@ -82,10 +39,7 @@ def predict(request: gr.Request, *args, progress=gr.Progress(track_tqdm=True)):
         if(outputs[0].get_config()["name"] == "json"):
             return json_response["output"]
         predict_outputs = parse_outputs(json_response["output"])
-        processed_outputs = process_outputs(predict_outputs)
-        difference_outputs = expected_outputs - len(processed_outputs)
-
-        
+        processed_outputs = process_outputs(predict_outputs)        
         return tuple(processed_outputs) if len(processed_outputs) > 1 else processed_outputs[0]
     else:
         if(response.status_code == 409):
@@ -93,15 +47,63 @@ def predict(request: gr.Request, *args, progress=gr.Progress(track_tqdm=True)):
         raise gr.Error(f"The submission failed! Error: {response.status_code}")
 
 title = "Demo for consistent-character cog image by fofr"
-model_description = "Create images of a given character in different poses"
-
-app = gr.Interface(
-    fn=predict,
-    inputs=inputs,
-    outputs=outputs,
-    title=title,
-    description=model_description,
-    allow_flagging="never",
-)
-app.launch(share=False)
+model_description = "Create images of a given character in different poses • running cog image by fofr"
+
+with gr.Blocks() as app:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML(f"""
+        <h2 style="text-align: center;">Consistent Character Workflow</h2>
+        <p style="text-align: center;">{description}</p>
+        """)
+
+        with gr.Row():
+            with gr.Column():
+                prompt = gr.Textbox(
+                    label="Prompt", info='''Describe the subject. Include clothes and hairstyle for more consistency.'''
+                )
+        
+                subject = gr.Image(
+                    label="Subject", type="filepath"
+                )
+
+                submit_btn = gr.Button("Submit")
+
+                with gr.Accordion(label="Advanced Settings", open=false):
+                    negative_prompt = gr.Textbox(
+                        label="Negative Prompt", info='''Things you do not want to see in your image'''
+                    )
+
+                    number_of_outputs = gr.Slider(
+                        label="Number Of Outputs", info='''The number of images to generate.''', value=3,
+                        minimum=1, maximum=20, step=1,
+                    )
+                    
+                    number_of_images_per_pose = gr.Slider(
+                        label="Number Of Images Per Pose", info='''The number of images to generate for each pose.''', value=1,
+                        minimum=1, maximum=4, step=1,
+                    )
+                    
+                    randomise_poses = gr.Checkbox(
+                        label="Randomise Poses", info='''Randomise the poses used.''', value=True
+                    )
+                    
+                    output_format = gr.Dropdown(
+                        choices=['webp', 'jpg', 'png'], label="output_format", info='''Format of the output images''', value="webp"
+                    )
+                    
+                    output_quality = gr.Number(
+                        label="Output Quality", info='''Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.''', value=80
+                    )
+                    
+                    seed = gr.Number(
+                        label="Seed", info='''Set a seed for reproducibility. Random by default.''', value=None
+                    )
+
+            with gr.Column():
+                consistent_results = gr.Gallery(label="Consistent Results")
+
+    inputs = [prompt, negative_prompt, subject, number_of_outputs, number_of_images_per_pose, randomise_poses, output_format, output_quality, seed]
+    outputs = [consistent_results]
+
+app.queue().launch(share=False)