add output size option

app_base.py

@@ -117,12 +117,13 @@ def create_demo() -> gr.Blocks:
                 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):
-                    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)
+                    guidance_scale = gr.Slider(minimum=0, maximum=20, value=1, step=0.5, label="Guidance Scale")
+                    input_size = gr.Number(label="Generate Size", value=1024)
+                    output_size = gr.Number(label="Output Size", value=512)
                     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=False)
-                    adapter_weights = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.1, label="Adapter Weights", visible=True)
+                    enhance_face = gr.Checkbox(label="Enhance Face", value=True)
+                    adapter_weights = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.1, label="Adapter Weights", visible=False)
             with gr.Column():
                 seed = gr.Number(label="Seed", value=8)
                 w1 = gr.Number(label="W1", value=2)
@@ -142,11 +143,11 @@ def create_demo() -> gr.Blocks:
         
         g_btn.click(
             fn=segment_image,
-            inputs=[input_image, category, generate_size, mask_expansion, mask_dilation],
+            inputs=[input_image, category, input_size, mask_expansion, mask_dilation],
             outputs=[origin_area_image, croper],
         ).success(
             fn=image_to_image,
-            inputs=[origin_area_image, input_image_prompt, edit_prompt,seed,w1, num_steps, start_step, guidance_scale, generate_size, adapter_weights, enhance_face],
+            inputs=[origin_area_image, input_image_prompt, edit_prompt,seed,w1, num_steps, start_step, guidance_scale, output_size, adapter_weights, enhance_face],
             outputs=[enhanced_image, generated_image, generated_cost],
         ).success(
             fn=restore_result,

inversion_run_base.py

@@ -114,6 +114,8 @@ def run(
         generator=generator,
         denoising_start=denoising_start,
         strength=0,
+        height=generate_size,
+        width=generate_size,
     )
 
     x_0_image = input_image

segment_utils.py

@@ -34,8 +34,8 @@ def restore_result(croper, category, generated_image):
 
     return restored_image, path
 
-def segment_image(input_image, category, generate_size, mask_expansion, mask_dilation):
-    mask_size = int(generate_size)
+def segment_image(input_image, category, input_size, mask_expansion, mask_dilation):
+    mask_size = int(input_size)
     mask_expansion = int(mask_expansion)
 
     image = mp.Image(image_format=mp.ImageFormat.SRGB, data=np.asarray(input_image))