Gradio のバージョンを 3.48.0 に

README.md

@@ -5,7 +5,7 @@ colorFrom: gray
 colorTo: blue
 sdk: gradio
 python_version: 3.10.13
-sdk_version: 4.8.0
+sdk_version: 3.48.0
 app_file: app.py
 pinned: false
 ---

app.py

@@ -24,7 +24,7 @@ else:
 if __name__ == "__main__":
     interface = Interface(
         fn=lambda modelName, image, threshold: infer(
-            input=np.array(PILImage.open(image)),
+            input=np.array(PILImage.open(image.name)),
             suffix=".png",
             threshold=float(threshold),
             configPath=Path(CONFIGS_PATH + modelName + ".yaml"),
@@ -39,7 +39,7 @@ if __name__ == "__main__":
                 label="Model",
             ),
             File(
-                type="filepath",
+                type="file",
                 label="Image",
                 file_count="single",
             ),

colab-application.py

@@ -1,69 +0,0 @@
-import argparse
-from pathlib import Path
-from gradio import Interface
-from gradio.components import Dropdown, Image, File, Textbox
-import numpy as np
-from PIL import Image as PILImage
-
-from lightning_inference import infer
-from pyngrok import ngrok
-ngrok.set_auth_token("2a1nQ7HUyDDykXm4lpq3J8Mne4j_6TaqHtHyEvnEkNV9jg4ad")
-
-# コマンドライン引数の解析
-parser = argparse.ArgumentParser()
-parser.add_argument("--colab", action="store_true")
-args = parser.parse_args()
-
-# This environment variable is set in the Dockerfile
-if args.colab:
-    CONFIGS_PATH = "/content/drive/MyDrive/anomaly-detection/huggingface/configs/"
-    MODELS_PATH = "/content/drive/MyDrive/anomaly-detection/huggingface/models/"
-else:
-    # Configured for Hugging Face environment
-    # See: https://huggingface.co/spaces/blanchon/MVTec_Padim_Anomalib_Test/blob/main/app.py
-    CONFIGS_PATH = "/home/user/app/configs/"
-    MODELS_PATH = "/home/user/app/models/"
-
-if __name__ == "__main__":
-    interface = Interface(
-        fn=lambda modelName, image: infer(
-            input=np.array(PILImage.open(image)),
-            suffix=".png",
-            configPath=Path(CONFIGS_PATH + modelName + ".yaml"),
-            weightsPath=Path(MODELS_PATH + modelName + ".ckpt"),
-        ),
-        inputs=[
-            Dropdown(
-                choices=[
-                    "fukazara",
-                    "asahachi_black",
-                    "fukazara_scoop_black",
-                ],
-                label="Model",
-            ),
-            File(
-                type="filepath",
-                label="Image",
-                file_count="single",
-            ),
-        ],
-        outputs=[
-            Image(
-                type="numpy",
-                label="Result",
-            ),
-            Image(
-                type="numpy",
-                label="Input",
-            ),
-            Textbox(
-              value="str",
-              type="text",
-              label="text_result"
-            ),
-        ],
-        title="Anomaly Detection with Anomalib",
-    )
-
-    url = interface.launch()
-    print("Interface URL:", url)