<feat> change output to gallery.

app.py

@@ -104,6 +104,13 @@ def process_image_and_text(condition_image, target_prompt, condition_image_promp
     # set up the model
     global pipe, current_task
     if pipe is None or current_task != task:
+        if current_task is not None:
+            transformer.delete_adapters('default')
+            for n, m in transformer.named_modules():
+                if isinstance(m, peft.tuners.lora.layer.Linear):
+                    if hasattr(m, 'base_layer'):
+                        m.forward = m.base_layer.forward.__get__(m, type(m))
+
         current_task = task
 
         # insert LoRA
@@ -264,16 +271,19 @@ def process_image_and_text(condition_image, target_prompt, condition_image_promp
         frame_gap=48,
         mixup=True,
         mixup_num_imgs=2,
-        enhance_tp=task in ['subject_driven', 'style_transfer'],
+        enhance_tp=task in ['subject_driven'],
     ).frames
 
-    gen_img = gen_img[:, 0:1, :, :, :]
-    gen_img = gen_img.squeeze(0).squeeze(0).cpu().to(torch.float32).numpy()
-    gen_img = np.transpose(gen_img, (1, 2, 0))
-    gen_img = (gen_img * 255).astype(np.uint8)
-    gen_img = Image.fromarray(gen_img)
-
-    return gen_img
+    output_images = []
+    for i in range(10):
+        out = gen_img[:, i:i+1, :, :, :]
+        out = out.squeeze(0).squeeze(0).cpu().to(torch.float32).numpy()
+        out = np.transpose(out, (1, 2, 0))
+        out = (out * 255).astype(np.uint8)
+        out = Image.fromarray(out)
+        output_images.append(out)
+    
+    return output_images[1:] + [output_images[0]]
 
 def create_app():
     with gr.Blocks() as app:
@@ -312,12 +322,21 @@ def create_app():
                 submit_btn = gr.Button("Run", elem_id="submit_btn")
 
             with gr.Column(variant="panel", elem_classes="outputPanel"):
-                output_image = gr.Image(type="pil", elem_id="output")
+                # output_image = gr.Image(type="pil", elem_id="output")
+                output_images = gr.Gallery(
+                    label="Output Images",
+                    show_label=True,
+                    elem_id="output_gallery",
+                    columns=1,
+                    rows=10,
+                    object_fit="contain",
+                    height="auto",
+                )
 
         submit_btn.click(
             fn=process_image_and_text,
             inputs=[condition_image, target_prompt, condition_image_prompt, task, random_seed, inpainting, fill_x1, fill_x2, fill_y1, fill_y2],
-            outputs=output_image,
+            outputs=output_images,
         )
         
     return app