AOI_Lab(Visual Inspection)

Versione 1.1 (7,41 MB) da Fred Liu
Visual Insepction (include Anomaly Detect & Text Detection & OCR & BarCode Read)
13 download
Aggiornato 26 lug 2023

AOI Lab(影像辨識與檢測)

Bulit on 2023/07 by Fred Liu
update 2024/02/20 (anomalydetection)

版本:MATALB: 2023a ~ 最新版本
需要工具箱: Deeplearning , Image Processing, Computer Vision, Parallel Computing
需要支援包: Computer Vision Toolbox Model for Text Detection,
Computer Vision Toolbox OCR Language Data,
Computer Vision Toolbox Automated Visual Inspection Library

Thanks for Alex Taylor Support anomaly detection

1.TextDetection

針對影像中的文字檢測並且標記,利用detectTextCRAFT模型。

AOI_TextDetection.mlx

image

2.OCR

針對文字做辨識,在2023a後的版本中,OCR的裡面的模型改為是Tesseract 5.0,演算法核心Deep Learning base, 架構為CNN+LSTM,所以整體精準度都有提高,目前也有62種語言與數字顯示器的辨識模型,並且可以在

AOI_DeepOCR.mlx
AOI_TrainDeepOCR.mlx
AOI_QuantizeOCR.mlx

image

3.BarCodeRead

針對一維與二維條碼,進行檢測與辨識。

AOI_BardcodeRead.mlx

image

4.Anomaly Detection

影像異常偵測與缺陷辨識,2022b之後的版本更新了三種異常偵測的演算法,分別是:

FCDD_Train.mlx
FastFlow_Train.mlx
PatchCore_Train.mlx

Network Function Notes
FCDD fcddAnomalyDetector
trainFCDDAnomalyDetector
.Light-weight model
.Fully convolutional
.Supports tiled training / full size inference workflow
FastFlow fastFlowAnomalyDetector
trainFastFlowAnomalyDetector
.State-of-the-Art model
.Fully convolutional
.Supports tiled training / full size inference workflow
.Relatively Memory intensive
PatchCore patchCoreAnomalyDetector
trainPatchCoreAnomalyDetector
.State-of-the-Art model
.Feature similarity based(no gradient descent training involved)
.Few-shot training
.Fixed image size at train and test
.Relatively Memory intensive(Supports compression)

image

5.Vit (Vision Transformer)

利用ViT網路進行影像辨識(Classification)

ViT.mlx

Vision Transformer Model有三種Pretrain Model

  • base
  • small
  • tiny
    image

Cita come

Fred Liu (2024). AOI_Lab(Visual Inspection) (https://github.com/MoonUsagi/AOI_Lab/releases/tag/v1.1), GitHub. Recuperato .

Compatibilità della release di MATLAB
Creato con R2023b
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux
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Versione Pubblicato Note della release
1.1

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.