Computer Vision based Automated Spare Part Finder App.pptx
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The document describes a computer vision based mobile app that can identify automotive spare parts from images and provide suppliers where the part can be purchased. The app was created to make identifying spare parts easier for car owners by allowing them to take a photo of the part and get information. It uses a deep learning model trained on a custom dataset to detect and classify images. Web scraping is then used to generate a list of websites where the identified part can be bought. The results showed the app could accurately identify parts and provide supplier information to users.
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- 1. INTERNATIONAL CONFERENCE ON APPLIED ARTIFICIAL INTELLIGENCE AND COMPUTING (ICAAIC 2022) COMPUTER VISION BASED AUTOMATED SPARE PART FINDER APP CHINIAH AATISH, GEERISHRAJ JUGROOP, PARISH SEEGOLUM, BAICHOO BIBI HUMAรRA UNIVERSITY OF MAURITIUS
- 2. CONTENTS โข Introduction โข Aims and Objectives โข The System โข Tools used โข Results โข Conclusion
- 3. INTRODUCTION โข Identifying/finding spare parts for cars can be quite time consuming as it requires technical knowledge about mechanics. โข The main issues that car owners have are: little information about the name of spare part, make and model of car and where to obtain the parts from and also no online comparator available for spare parts as there are for plane tickets or car insurance. โข Given the recent uptake of websites for business, car owners would need to browse through different shops and go through the complicated search to find the desired products. โข Our solution, a mobile app, provides identification of a spare part information through image processing using the camera of smartphone and a deep learning model. Once the metadata of the spare part required is obtained, web mining technique is used to obtain a list of websites from where the spare part can be purchased.
- 4. AIMS AND OBJECTIVES โข To implement a mobile application that would enable the identification of a spare part using its image which will be used to generate a list of suppliers. โข To conduct a detailed analysis of similar existing object detection system. โข To build a dataset of spare parts. โข To train a neural network model to detect and classify images of spare parts. โข To create a mobile app and deploy model. โข To create a web scrapper to display a list of website from where spare part can be purchased.
- 5. THE SYSTEM
- 6. TOOLS USED โข Flutter SDK 2.2.3 โข Labelimg โข Roboflow โข TensorFlow โข Android Studio โข TFLite flutter plugin
- 7. RESULTS Scraper Results View After Image Selection
- 9. ACCURACY OF TEST RESULTS
- 13. PERFORMANCE EVALUATION Before running App While using App
- 14. CONCLUSION โขIn this work, we demonstrate that how several technologies could be brought together to solve real-life issues. Using Computer Vision, our implementation is capable of identifying spare parts using a custom built dataset. A list of websites from where to buy the specific spare part is then presented to the user as links.
- 15. Thank you for your kind attention!