R-aryan/Chess_Piece_Detection_Using_SSD

End to End object detection project using SSD, and serving it as REST API using Flask framework

Chess Piece Detection Using SSD

• End to end object detection project using SSD(Single Shot Detection).
• The training is done using TFOD2.0(Tensorflow object detection) framework.
• The application is served as an REST API using Flask.

Steps to run the application

Setting up virtual environment.

• What is Virtual Environment in python ?
• Create virtual environment in python
• Create virtual environment Anaconda
• create a virtual environment and install requirements.txt

pip install -r requirements.txt

• After setting up the virtual environment download the trained weights from here.
• After downloading the trained weights place it under the directory services/chess_piece_detector/application/ai/weights/
• After performing the above steps go to services/chess_piece_detector/api and run app.py

python app.py

• After running the app.py the web app can be accessed at http://127.0.0.1:8000/ copy this url and paste it in your browser.
• The UI will look like the following.

• The picture can be uploaded using the upload button and after uploading the image click on predict to perform inference.
• Sample Input

• Sample Output

• The application logs can also be found here.