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End to end object detection project using Faster RCNN, trained using TFOD1.14 framework and served as REST API via Flask App

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R-aryan/Cards_Detection_Using_FASTER-RCNN

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Cards Detection Using FASTER RCNN

Steps to run the application

Setting up virtual environment.

pip install -r requirements.txt

python app.py

  • After running the app.py the web app can be accessed at http:https://127.0.0.1:9000/ copy this url and paste it in your browser.
  • The UI will look like the following.

Sample UI

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

Sample Input

  • Sample Output

Sample output

  • The application logs can also be found here.

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End to end object detection project using Faster RCNN, trained using TFOD1.14 framework and served as REST API via Flask App

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