# Industrial quality inspection

This is an object detection model released under the Apache-2.0 license, designed to identify and locate specific objects within images.

A vision model fine-tuned based on google/vit-base-patch16-224, achieving an F1 score of 0.9931 on the evaluation set

An object detection model implemented based on PyTorch, used for identifying and localizing objects in images.

A deep learning model for image segmentation tasks, capable of precisely segmenting different objects or regions in an image.

A general-purpose image classification model capable of recognizing and classifying objects in input images

A binary classification image classification model trained with AutoTrain, performing excellently on the validation set

A Vision Transformer model fine-tuned from google/vit-base-patch16-224-in21k, achieving 99.26% accuracy on the evaluation set

HKDB_SDFT_Unbalanced is a model for image classification tasks with high accuracy.

This is an image classification model built on PyTorch and HuggingPics, specifically designed to identify rust conditions in images.

This is an image classification model based on the PyTorch framework and generated using HuggingPics, specifically designed to identify rust and non-rust images.

A PyTorch-based image classification model for detecting anomalies in images.

This is a Bert model optimized for French, focusing on the quality domain, developed by the Multi2ConvAI project.