Update app.py

app.py

@@ -39,17 +39,14 @@ MAX_IMAGE_SIZE = 1216
 
     
 @spaces.GPU
-def infer(image: PIL.Image.Image, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps) -> PIL.Image.Image:
+def infer(use_image, image: PIL.Image.Image, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps) -> PIL.Image.Image:
     # Check if the input image is a valid PIL Image and is not empty
-    if isinstance(image, PIL.Image.Image) :
-        use_image = True
+    if use_image :
         width, height = image['composite'].size
         ratio = np.sqrt(1024. * 1024. / (width * height))
         new_width, new_height = int(width * ratio), int(height * ratio)
         image = image['composite'].resize((new_width, new_height))
         print(image)
-    else:
-        use_image = False
 
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
@@ -112,6 +109,8 @@ with gr.Blocks(css=css) as demo:
         image = gr.ImageEditor(type="pil", image_mode="L", crop_size=(512, 512))
         result = gr.Image(label="Result", show_label=False)
 
+        gradio_en = True
+        
         with gr.Accordion("Advanced Settings", open=False):
 
             negative_prompt = gr.Text(
@@ -167,7 +166,7 @@ with gr.Blocks(css=css) as demo:
 
     run_button.click(lambda x: None, inputs=None, outputs=result).then(
         fn=infer,
-        inputs=[image, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+        inputs=[gradio_en, image, prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
         outputs=[result]
     )