Update app.py

app.py

@@ -62,20 +62,16 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     return seed
 
 
-@spaces.GPU(duration=600)
+@spaces.GPU(duration=180)
 def generate_img(
-    np_image: np.ndarray,  # rgb image
+    pil_image,
     edit_prompt: str,
     sample_steps,
     scale,
     image_guidance_scale,
     seed,
     progress=gr.Progress(track_tqdm=True),
-):
-    # pipeline.pipe.to("cuda").to(pipeline.weight_dtype)
-    
-    pil_image = PILImage.fromarray(np_image)
-
+):    
     edited_image = pipeline.generate_edited_image(
         instruction=edit_prompt,
         conditioning_image=pil_image,
@@ -84,9 +80,8 @@ def generate_img(
         guidance_scale=scale,
         image_guidance_scale=image_guidance_scale,
         seed=seed,
-    )[0]
-    result_image = np.asarray(edited_image)
-    return result_image
+    )
+    return edited_image
 
 
 if __name__ == "__main__":
@@ -96,15 +91,10 @@ if __name__ == "__main__":
     image_dir = pathlib.Path('images')
     examples = [[path.as_posix(), "let this case swim in the river", 20, 4.5, 1.2, 42] for path in sorted(image_dir.glob('*.png'))]
 
-    # generate_fn = partial(
-    #     generate_img,
-    #     pipeline=editor_pipeline
-    # )
-
     demo = gr.Interface(
         fn=generate_img,
         inputs=[
-            gr.Image(label="Input", type="numpy"),
+            gr.Image(label="Input", type="pil"),
             Textbox(label="Prompt", placeholder="Please enter your prompt. \n"),
             gr.Slider(label="Sample Steps", minimum=1, maximum=100, value=20, step=1),
             gr.Slider(
@@ -125,12 +115,10 @@ if __name__ == "__main__":
                 value=42,
             ),
         ],
-        outputs=[
-            Image(type="numpy", label="Img"),
-        ],
+        outputs = [gr.Gallery(label="Result", show_label=False, type="pil")]
         title="",
         description=DESCRIPTION,
         examples=examples,
     )
 
-    demo.queue(max_size=15).launch()
+    demo.queue(max_size=100).launch()