Bewertung von Technische Zeichnungen
Table of Contents
- Dataset
- Data Augmentation
- Clustering for Exploratory Data Analysis
- Computer Vision Operations
- Image Classification
- Image Segmentation
- Feedbacksystem Module
1.DATASET
4 different types of Technical Drawings along with their respective Evaluation Table:- a) Schraube b) Baugruppen c) Toleranz d) Gussaufgabe
2.DATA AUGMENTATION
a). Increasing the the dataset by implementating various data Augmentation Techniques: Scale variation , Brightness and Contrast , Rotation etc.
b). Adding noise and reconstruction using Variational AutoEncoders
3.CLUSTERING
Appling k-means Clustering algorithm on the dataset.
a) Clustering on Corrected and Not-Corrected Images
b) Clustering on Entire Dataset
4.COMPUTER VISION OPERATIONS:
a). Canny Edge Detection:
b). SIFT feature Matching and Homography Matrix Calculations:
5.IMAGE CLASSIFICATION:
-> Classification of the images based on the drawing type:
Finetuning ResNet50 , EfficicentNet Models on this custom Dataset. Models along with the Training Scripts are uploaded in Image Classification directory.
6.IMAGE SEGMENTATION:
-> Segementing the drawing and the text box on the Image.
Trained a yolov8 model on custom dataset.
7.FEEDBACK SYSTEM MODULE:
a). Overview of the system Architecture
b). Dataset Preparation:
c). Model Fusion:
-Combining Visual Features with Text Analysis along with Domain Knowledge to generate feedback on the drawing. -Training the fusion Model on the custom annotated Dataset for 1000 Epochs.
d). Output:
-> Deployment using FASTAPI on local host for inference check
Contact Author: [email protected]
Institut für Konstruktionstechnik und Technisches Design https://www.iktd.uni-stuttgart.de