Update app.py

app.py

@@ -167,8 +167,7 @@ def update_selection(selected_state: gr.SelectData, sdxl_loras, face_strength, i
         selected_state
     )
 
-def center_crop_image_as_square(images):
-    img = images[0]
+def center_crop_image_as_square(img):
     square_size = min(img.size)
     
     left = (img.width - square_size) / 2
@@ -177,7 +176,7 @@ def center_crop_image_as_square(images):
     bottom = (img.height + square_size) / 2
     
     img_cropped = img.crop((left, top, right, bottom))
-    return (img_cropped, None)
+    return img_cropped
     
 def check_selected(selected_state):
     if not selected_state:
@@ -209,6 +208,7 @@ def merge_incompatible_lora(full_path_lora, lora_scale):
 def run_lora(images, prompt, negative, lora_scale, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, sdxl_loras, progress=gr.Progress(track_tqdm=True)):
     global last_lora, last_merged, last_fused, pipe
     face_image = images[0]
+    face_image = center_crop_image_as_square(face_image)
     face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))
     face_info = sorted(face_info, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])[-1] # only use the maximum face
     face_emb = face_info['embedding']
@@ -390,12 +390,6 @@ with gr.Blocks(css="custom.css") as demo:
         inputs=[selected_state],
         queue=False,
         show_progress=False
-    ).success(
-        fn=center_crop_image_as_square,
-        inputs=[photo],
-        outputs=[photo],
-        queue=False,
-        show_progress=False,
     ).success(
         fn=run_lora,
         inputs=[photo, prompt, negative, weight, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, gr_sdxl_loras],
@@ -406,12 +400,6 @@ with gr.Blocks(css="custom.css") as demo:
         inputs=[selected_state],
         queue=False,
         show_progress=False
-    ).success(
-        fn=center_crop_image_as_square,
-        inputs=[photo],
-        outputs=[photo],
-        queue=False,
-        show_progress=False,
     ).success(
         fn=run_lora,
         inputs=[photo, prompt, negative, weight, selected_state, face_strength, image_strength, guidance_scale, depth_control_scale, gr_sdxl_loras],