update model stable

app.py

@@ -49,7 +49,7 @@ blip_generator = BlipForConditionalGeneration.from_pretrained(
 pipe.to(accelerator.device)
 blip_generator.to(accelerator.device)
 
-def colorize_single_image(image, positive_prompt, negative_prompt, caption_generate):
+def colorize_image_sdxl(image, positive_prompt=None, negative_prompt=None, caption_generate=True, seed=123, infer_steps=5):
     image = PIL.Image.fromarray(image)
 
     torch.cuda.empty_cache()
@@ -63,13 +63,13 @@ def colorize_single_image(image, positive_prompt, negative_prompt, caption_gener
     prompt = [positive_prompt + ", " + caption]
     
     colorized_image = pipe(prompt=prompt,
-                           num_inference_steps=5, 
-                           generator=torch.manual_seed(0),
+                           num_inference_steps=infer_steps, 
+                           generator=torch.manual_seed(seed),
                            image=control_image,
                            negative_prompt=negative_prompt).images[0]
     result_image = apply_color(control_image, colorized_image)
     result_image = result_image.resize(original_size)
-    return result_image, caption if caption_generate else gr.update(visible=False)
+    return result_image, caption
 
 # Hàm load models cho autoencoder và gan
 def load_autoencoder_model(auto_model_path):