Update app.py

app.py

@@ -2,20 +2,24 @@ import gradio as gr
 import torch
 from diffusers import StableDiffusionPipeline
 from safetensors.torch import load_file
+import os
+
 
 # safetensors 모델 로드 함수
-def load_safetensors_model(model_id, model_file):
+def load_safetensors_model(model_id, model_file, use_auth_token):
     # safetensors 파일 로드
     state_dict = load_file(model_file)
-    # 모델 로드
-    model = StableDiffusionPipeline.from_pretrained(model_id, state_dict=state_dict)
+    # 모델 초기화
+    model = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=use_auth_token)
+    # 모델에 state_dict 로드
+    model.model.load_state_dict(state_dict)
     return model
 
 model_id = "gagong/Traditional-Korean-Painting-Model-v2.0"
-model_file = "Traditional_Korean_Painting_Model_2.safetensors"
+model_file = "./Traditional_Korean_Painting_Model_2.safetensors"  # 루트 디렉토리에 있는 파일 경로 설정
 
 try:
-    pipe = load_safetensors_model(model_id, model_file)
+    pipe = load_safetensors_model(model_id, model_file, use_auth_token=HUGGINGFACE_TOKEN)
     pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
 except Exception as e:
     print(f"Error loading model: {e}")
@@ -27,97 +31,20 @@ def generate_image(prompt):
     image = pipe(prompt).images[0]
     return image
 
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 520px;
-}
-"""
-
-if torch.cuda.is_available():
-    power_device = "GPU"
-else:
-    power_device = "CPU"
-
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""
-        # Text-to-Image Gradio Template
-        Currently running on {power_device}.
-        """)
-        
-        with gr.Row():
-            prompt = gr.Textbox(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            run_button = gr.Button("Run", scale=0)
-        
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Textbox(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt"
-            )
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
-                )
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
-                )
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=7.5,
-                )
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=25,
-                )
-        
-        gr.Examples(
-            examples=examples,
-            inputs=[prompt]
-        )
-
-    run_button.click(
-        fn=infer,
-        inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs=[result]
-    )
+# Gradio 인터페이스 설정
+with gr.Blocks() as demo:
+    gr.Markdown("# Traditional Korean Painting Generator")
+    gr.Markdown("Enter a prompt to generate a traditional Korean painting.")
+    
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Prompt", placeholder="Describe the scene...")
+            generate_btn = gr.Button("Generate")
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image")
+    
+    generate_btn.click(fn=generate_image, inputs=prompt, outputs=output_image)
+
+if __name__ == "__main__":
+    demo.launch()
 
-demo.queue().launch()