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Anomaly2

Developed by hafidber
This is an image classification model based on the PyTorch framework, specifically designed for anomaly detection tasks, automatically generated by the HuggingPics tool.
Image Classification
Transformers
#Industrial Quality Inspection#High-Precision Classification#Defect Detection
Downloads 31
Release Time : 4/7/2022

Model Overview

This model is primarily used for image classification tasks, especially for anomaly detection scenarios, capable of distinguishing between normal and abnormal samples.

Model Features

High Accuracy
Shows an accuracy rate of 1.0 in evaluation metrics, demonstrating excellent performance.
Automated Generation
Automatically generated by the HuggingPics tool, facilitating quick deployment.
PyTorch Framework
Developed based on the PyTorch framework, with strong compatibility.

Model Capabilities

Image Classification
Anomaly Detection

Use Cases

Industrial Inspection
Product Defect Detection
Detect whether products on the production line have defects.
Accurately identify abnormal products.
Medical Imaging
Medical Image Anomaly Detection
Identify abnormal areas in medical images.
Assist doctors in diagnosis.
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