change to img2img

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 
-from app_haircolor_inpaint import create_demo as create_demo_haircolor
+from app_haircolor import create_demo as create_demo_haircolor
 
 with gr.Blocks(css="style.css") as demo:
     with gr.Tabs():

app_haircolor.py

@@ -24,7 +24,7 @@ from controlnet_aux import (
 BASE_MODEL = "stabilityai/sdxl-turbo"
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
-DEFAULT_EDIT_PROMPT = "a woman, blue hair, high detailed"
+DEFAULT_EDIT_PROMPT = "blue hair"
 DEFAULT_NEGATIVE_PROMPT = "worst quality, normal quality, low quality, low res, blurry, text, watermark, logo, banner, extra digits, cropped, jpeg artifacts, signature, username, error, sketch ,duplicate, ugly, monochrome, horror, geometry, mutation, disgusting, poorly drawn face, bad face, fused face, ugly face, worst face, asymmetrical, unrealistic skin texture, bad proportions, out of frame, poorly drawn hands, cloned face, double face"
 
 DEFAULT_CATEGORY = "hair"
@@ -53,12 +53,7 @@ adapters = MultiAdapter(
             "TencentARC/t2i-adapter-canny-sdxl-1.0",
             torch_dtype=torch.float16,
             varient="fp16",
-        ),
-        T2IAdapter.from_pretrained(
-            "TencentARC/t2i-adapter-sketch-sdxl-1.0",
-            torch_dtype=torch.float16,
-            varient="fp16",
-        ),
+        )
     ]
 )
 adapters = adapters.to(torch.float16)
@@ -86,20 +81,17 @@ def image_to_image(
     generate_size: int,
     lineart_scale: float = 1.0,
     canny_scale: float = 0.5,
-    sketch_scale:float = 0.5,
 ):
     run_task_time = 0
     time_cost_str = ''
     run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
-    lineart_image = lineart_detector(input_image, 384, generate_size)
-    run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
-    canny_image = canndy_detector(input_image, 384, generate_size)
+    lineart_image = lineart_detector(input_image, int(generate_size*0.375), generate_size)
     run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
-    sketch_image = pidinet_detector(input_image, 512, generate_size)
+    canny_image = canndy_detector(input_image, int(generate_size*0.375), generate_size)
     run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
 
-    cond_image = [lineart_image, canny_image, sketch_image]
-    cond_scale = [lineart_scale, canny_scale, sketch_scale]
+    cond_image = [lineart_image, canny_image]
+    cond_scale = [lineart_scale, canny_scale]
 
     generator = torch.Generator(device=DEVICE).manual_seed(seed)
     generated_image = basepipeline(
@@ -136,18 +128,17 @@ def create_demo() -> gr.Blocks:
         with gr.Row():
             with gr.Column():
                 edit_prompt = gr.Textbox(lines=1, label="Edit Prompt", value=DEFAULT_EDIT_PROMPT)
-                generate_size = gr.Number(label="Generate Size", value=512)
+                generate_size = gr.Number(label="Generate Size", value=1024)
                 seed = gr.Number(label="Seed", value=8)
                 category = gr.Textbox(label="Category", value=DEFAULT_CATEGORY, visible=False)
             with gr.Column():
-                num_steps = gr.Slider(minimum=1, maximum=100, value=10, step=1, label="Num Steps")
-                guidance_scale = gr.Slider(minimum=0, maximum=30, value=5, step=0.5, label="Guidance Scale")
-                mask_expansion = gr.Number(label="Mask Expansion", value=50, visible=True)
+                num_steps = gr.Slider(minimum=1, maximum=100, value=5, step=1, label="Num Steps")
+                guidance_scale = gr.Slider(minimum=0, maximum=30, value=2.5, step=0.5, label="Guidance Scale")
+                mask_expansion = gr.Number(label="Mask Expansion", value=20, visible=True)
             with gr.Column():
                 mask_dilation = gr.Slider(minimum=0, maximum=10, value=2, step=1, label="Mask Dilation")
                 lineart_scale = gr.Slider(minimum=0, maximum=5, value=1, step=0.1, label="Lineart Scale")
                 canny_scale = gr.Slider(minimum=0, maximum=5, value=0.7, step=0.1, label="Canny Scale")
-                sketch_scale = gr.Slider(minimum=0, maximum=5, value=1, step=0.1, label="Sketch Scale")
                 g_btn = gr.Button("Edit Image")
                 
         with gr.Row():
@@ -166,7 +157,7 @@ def create_demo() -> gr.Blocks:
             outputs=[origin_area_image, croper],
         ).success(
             fn=image_to_image,
-            inputs=[origin_area_image, edit_prompt,seed, num_steps, guidance_scale, generate_size, lineart_scale, canny_scale, sketch_scale],
+            inputs=[origin_area_image, edit_prompt,seed, num_steps, guidance_scale, generate_size, lineart_scale, canny_scale],
             outputs=[generated_image, generated_cost],
         ).success(
             fn=restore_result,