add lora

app_base.py

@@ -114,18 +114,18 @@ def create_demo() -> gr.Blocks:
                 edit_prompt = gr.Textbox(lines=1, label="Edit Prompt", value=DEFAULT_EDIT_PROMPT)
                 category = gr.Textbox(label="Category", value=DEFAULT_CATEGORY, visible=False)
             with gr.Column():
-                num_steps = gr.Slider(minimum=1, maximum=100, value=5, step=1, label="Num Steps")
-                start_step = gr.Slider(minimum=1, maximum=100, value=1, step=1, label="Start Step")
-                guidance_scale = gr.Slider(minimum=0, maximum=20, value=2.5, step=0.5, label="Guidance Scale")
+                num_steps = gr.Slider(minimum=1, maximum=100, value=20, step=1, label="Num Steps")
+                start_step = gr.Slider(minimum=1, maximum=100, value=15, step=1, label="Start Step")
                 with gr.Accordion("Advanced Options", open=False):
-                    generate_size = gr.Number(label="Generate Size", value=512)
+                    guidance_scale = gr.Slider(minimum=0, maximum=20, value=0, step=0.5, label="Guidance Scale")
+                    generate_size = gr.Number(label="Generate Size", value=1024)
                     mask_expansion = gr.Number(label="Mask Expansion", value=50, visible=True)
                     mask_dilation = gr.Slider(minimum=0, maximum=10, value=2, step=1, label="Mask Dilation")
-                    enhance_face = gr.Checkbox(label="Enhance Face", value=True)
+                    enhance_face = gr.Checkbox(label="Enhance Face", value=False)
+                    adapter_weights = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.1, label="Adapter Weights", visible=True)
             with gr.Column():
                 seed = gr.Number(label="Seed", value=8)
-                w1 = gr.Number(label="W1", value=1.5)
-                adapter_weights = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.1, label="Adapter Weights", visible=False)
+                w1 = gr.Number(label="W1", value=2)
                 g_btn = gr.Button("Edit Image")
                 
         with gr.Row():

inversion_run_base.py

@@ -1,4 +1,5 @@
 import torch
+import os
 
 from diffusers import (
     DDPMScheduler,
@@ -55,7 +56,11 @@ pipeline.scheduler = DDPMScheduler.from_pretrained(
     subfolder="scheduler",
 )
 
-# pipeline.load_lora_weights("checkpoints/lora", weight_name="zy_AmateurStyle_v2.safetensors", adapter_name="zy_AmateurStyle_v2")
+os.makedirs('checkpoints/lora', exist_ok=True)
+if not os.path.exists('checkpoints/lora/perfection_style.safetensors'):
+    os.system("wget https://civitai.com/api/download/models/458257?type=Model&format=SafeTensor -O ./checkpoints/lora/perfection_style.safetensors")
+
+pipeline.load_lora_weights("checkpoints/lora", weight_name="perfection_style.safetensors", adapter_name="perfection_style")
 
 config = get_config(args)
 
@@ -79,7 +84,7 @@ def run(
     guidance_scale:float,
     adapter_weights:float,
 ):
-    # pipeline.set_adapters(["zy_AmateurStyle_v2"], adapter_weights=[adapter_weights])
+    pipeline.set_adapters(["perfection_style"], adapter_weights=[adapter_weights])
     generator = torch.Generator().manual_seed(seed)
 
     config.num_steps_inversion = num_steps