require

app.py

@@ -3,6 +3,8 @@ import cv2
 import numpy as np
 from anomalib.deploy import OpenVINOInferencer
 from huggingface_hub import hf_hub_download
+from anomalib import TaskType
+from PIL import Image
 
 # Load the model
 model_path = hf_hub_download(repo_id="suidinpa/bottle-anomaly-detection", filename="model.bin")

requirements.txt

@@ -1,11 +1,12 @@
 gradio==3.30.0
-torch==1.13.1  # If your model uses PyTorch
+torch==2.5.1
+torchvision==0.20.1
 opencv-python-headless==4.7.0.72  # OpenCV for image processing (headless for better compatibility with Hugging Face)
 numpy==1.23.0
-anomalib==0.2.0  # For anomaly detection
+anomalib==1.2.0  # For anomaly detection
 huggingface-hub==0.14.1  # For model uploading and interaction with Hugging Face
 openvino==2022.3.0  # OpenVINO for model inference
 Pillow==9.2.0  # PIL for image manipulation
 matplotlib==3.5.3  # For plotting, if needed
-gdown==4.4.0  # For downloading from Google Drive (if necessary)
-loguru==0.6.0  # For logging (optional)
+gdown==5.2.0  # For downloading from Google Drive (if necessary)
+loguru==0.7.2  # For logging (optional)