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# System prepended metadata

title: product-expectation - golf project

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Application functionalities
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Final product shall contains following properties:

- A compiled android and/or ios mobile application. As well as complete source code for that application(s)
- A deployed AI model in cloud and it's source code as well as the deployed context properties
- A developer document on how to extend each of the product mentioned above
- A best-effort user guide to help user of the application on how to navigate and use the functionalities
- Datasets used to train the AI model
- Design file of mobile application
- Access of all the third party services & resources if used any under any of the product mentioned above



Description of mobile application
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* A interface to allow user to import video file from their local storage in mobile phone
* A interface for user to customize trace line color, line weight, line type ( solid or dotted or glow )
* Submission of so said video to cloud server for product described in "Description of deployed AI Model" if provided Internet access
* A progress indicator
* Capabilities to play and download video output of "Description of AI model".
* Capabilities to share so said video or video link to social media using android/ios share functionalities.
* Interface to user login/signup if the users wants so but above mentioned functionalities will be accessable even without signing up
* Interface to reset user password with verification of email or phone
* Interface to share out videos in user profile
* Interface to add tags, title and description of so said video while adding to profile
* Interface to set the privacy of that video to public or private
* Interface to share all the public videos including own as well as other registered user



Description of deployed AI MODEL
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* A python based AI model with interface to specify input video, color, line weight, line type
* Model capable of  99% uptime deployed in cloud
* Capable of drawing a trace line tracking the golf fall ( if exists )
* Model will have accuracy rate of approaching 0.9 or greater out of 1.0



Description of deployed backend
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* A backend service to bridge between AI model and mobile application
* web interface to interact with AI model and persistent output format
* Another component to handle user singup/login and other user management.