UI controls

app.py

@@ -37,7 +37,6 @@ MODELS = {
     "RealVisXL V5.0 Lightning": "SG161222/RealVisXL_V5.0_Lightning",
     "Playground v2.5": "playgroundai/playground-v2.5-1024px-aesthetic",
     "Juggernaut XL Lightning": "RunDiffusion/Juggernaut-XL-Lightning",
-    "LEOSAM HelloWorld XL": "Leosam/HelloWorld-SDXL-Lightning",
 }
 
 DEFAULT_MODEL = "DreamShaper XL Turbo"
@@ -65,15 +64,27 @@ def load_pipeline(model_name):
 
 current_model = DEFAULT_MODEL
 pipe = load_pipeline(current_model)
+lora_loaded = False
 
 
 @spaces.GPU(duration=24)
-def fill_image(prompt, negative_prompt, image, model_selection, paste_back):
-    global pipe, current_model
+def fill_image(prompt, negative_prompt, image, model_selection, paste_back, guidance_scale, num_steps, use_detail_lora, detail_lora_weight):
+    global pipe, current_model, lora_loaded
 
     if model_selection != current_model:
         pipe = load_pipeline(model_selection)
         current_model = model_selection
+        lora_loaded = False
+
+    if use_detail_lora and not lora_loaded:
+        pipe.load_lora_weights("LyliaEngine/add-detail-xl", adapter_name="add-detail-xl")
+        lora_loaded = True
+
+    if lora_loaded:
+        if use_detail_lora:
+            pipe.set_adapters(["add-detail-xl"], adapter_weights=[detail_lora_weight])
+        else:
+            pipe.set_adapters(["add-detail-xl"], adapter_weights=[0.0])
 
     (
         prompt_embeds,
@@ -98,8 +109,8 @@ def fill_image(prompt, negative_prompt, image, model_selection, paste_back):
         control_image=[cnet_image],
         controlnet_conditioning_scale=[1.0],
         control_mode=[7],
-        num_inference_steps=8,
-        guidance_scale=1.5,
+        num_inference_steps=int(num_steps),
+        guidance_scale=guidance_scale,
         callback_on_step_end=callback_cfg_cutoff,
         callback_on_step_end_tensor_inputs=[
             "prompt_embeds",
@@ -149,6 +160,13 @@ with gr.Blocks() as demo:
         with gr.Column():
             paste_back = gr.Checkbox(True, label="Paste back original")
 
+    with gr.Row():
+        guidance_scale = gr.Slider(minimum=0.0, maximum=10.0, value=1.5, step=0.1, label="Guidance Scale")
+        num_steps = gr.Slider(minimum=1, maximum=50, value=8, step=1, label="Number of Steps")
+    with gr.Row():
+        use_detail_lora = gr.Checkbox(False, label="Add Detail XL LoRA")
+        detail_lora_weight = gr.Slider(minimum=0.0, maximum=2.0, value=1.1, step=0.1, label="Detail LoRA Weight")
+
     with gr.Row():
         input_image = gr.ImageMask(
             type="pil",
@@ -182,7 +200,7 @@ with gr.Blocks() as demo:
         outputs=use_as_input_button,
     ).then(
         fn=fill_image,
-        inputs=[prompt, negative_prompt, input_image, model_selection, paste_back],
+        inputs=[prompt, negative_prompt, input_image, model_selection, paste_back, guidance_scale, num_steps, use_detail_lora, detail_lora_weight],
         outputs=result,
     ).then(
         fn=lambda: gr.update(visible=True),
@@ -200,7 +218,7 @@ with gr.Blocks() as demo:
         outputs=use_as_input_button,
     ).then(
         fn=fill_image,
-        inputs=[prompt, negative_prompt, input_image, model_selection, paste_back],
+        inputs=[prompt, negative_prompt, input_image, model_selection, paste_back, guidance_scale, num_steps, use_detail_lora, detail_lora_weight],
         outputs=result,
     ).then(
         fn=lambda: gr.update(visible=True),