restful

app.py

@@ -7,73 +7,44 @@ from scripts.process_utils import initialize, process_image_as_base64
 from scripts.anime import init_model
 from scripts.generate_prompt import load_wd14_tagger_model
 
-import spaces
-
 # 初期化
 initialize(_use_local=False, use_gpu=True, use_dotenv=False)
 init_model(use_local=False)
 load_wd14_tagger_model()
 
-@spaces.GPU
 def process_image(input_image, mode, weight1, weight2):
     # 画像処理ロジック
     sotai_image, sketch_image = process_image_as_base64(input_image, mode, weight1, weight2)
-    
-    # Base64文字列をPIL Imageに変換
-    sotai_pil = Image.open(io.BytesIO(base64.b64decode(sotai_image)))
-    sketch_pil = Image.open(io.BytesIO(base64.b64decode(sketch_image)))
-    
-    return sotai_pil, sketch_pil
+    return sotai_image, sketch_image
 
-# サンプル画像のパスリスト
-sample_images = [
-  'images/sample1.png',
-  'images/sample2.png',
-#   'images/sample4.png',
-#   'images/sample5.png',
-#   'images/sample6.png',
-#   'images/sample7.png',
-#   'images/sample8.png',
-#   'images/sample10.png',
-#   'images/sample11.png',
-#   'images/sample15.png',
-#   'images/sample16.png',
-#   'images/sample18.png',
-#   'images/sample19.png',
-#   'images/sample20.png',
-#   'images/sample21.png',
-]
+def gradio_process_image(input_image, mode, weight1, weight2):
+    # Gradio用の関数：PILイメージを受け取り、Base64文字列を返す
+    input_image_bytes = io.BytesIO()
+    input_image.save(input_image_bytes, format='PNG')
+    input_image_base64 = base64.b64encode(input_image_bytes.getvalue()).decode('utf-8')
+    
+    sotai_base64, sketch_base64 = process_image(input_image_base64, mode, weight1, weight2)
+    return sotai_base64, sketch_base64
 
 # Gradio インターフェースの定義
-with gr.Blocks() as demo:
-    gr.Markdown("# Image2Body Demo")
-    
-    with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(type="pil", label="Input Image")
-            mode = gr.Radio(["original", "refine"], label="Mode", value="original")
-            with gr.Row():
-                weight1 = gr.Slider(0, 2, value=0.6, step=0.05, label="Weight 1 (Sketch)")
-                weight2 = gr.Slider(0, 1, value=0.05, step=0.025, label="Weight 2 (Body)")
-            process_btn = gr.Button("Process")
-        
-        with gr.Column():
-            sotai_output = gr.Image(type="pil", label="Sotai (Body) Image")
-            sketch_output = gr.Image(type="pil", label="Sketch Image")
-    
-    gr.Examples(
-        examples=[[path, "original", 0.6, 0.05] for path in sample_images],
-        inputs=[input_image, mode, weight1, weight2],
-        outputs=[sotai_output, sketch_output],
-        fn=process_image,
-        cache_examples=True,
-    )
-    
-    process_btn.click(
-        fn=process_image,
-        inputs=[input_image, mode, weight1, weight2],
-        outputs=[sotai_output, sketch_output]
-    )
+iface = gr.Interface(
+    fn=gradio_process_image,
+    inputs=[
+        gr.Image(type="pil", label="Input Image"),
+        gr.Radio(["original", "refine"], label="Mode", value="original"),
+        gr.Slider(0, 2, value=0.6, step=0.05, label="Weight 1 (Sketch)"),
+        gr.Slider(0, 1, value=0.05, step=0.025, label="Weight 2 (Body)")
+    ],
+    outputs=[
+        gr.Image(type="pil", label="Sotai (Body) Image"),
+        gr.Image(type="pil", label="Sketch Image")
+    ],
+    title="Image2Body API",
+    description="Upload an image and select processing options to generate body and sketch images."
+)
+
+# APIとして公開
+app = gr.mount_gradio_app(app, iface, path="/")
 
-# Spacesへのデプロイ設定
-demo.launch()
+# Hugging Face Spacesでデプロイする場合
+iface.queue().launch()