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Built during Girls Hoo Hack Hackathon 2020. Won 1st for the Best Use of Google Cloud and won Best Overall for the entire hackathon.

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Hasama-Twins/Posetivity

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Posetivity

Posetivity Demo Video

Youtube Demo: https://youtu.be/M-KAYfoawNI

Every day women across the globe feel self-conscious or insecure about their body image. As females ourselves active on several image-based social media apps, we both have felt dissatisfied with our appearances. This lack of contentment has fueled us to promote change in our own lives and the lives of others. Through our experiences with yoga, we have learned to appreciate and become aligned with our bodies, and we wanted to share this opportunity with others. We dream of a world where one day all women love their bodies to the fullest and feel empowered to embrace their differences and diversity!

Therefore, we were inspired to create Posetivity, an iOS mobile application that cultivates a positive relationship between women and their bodies through low-intensity strengthening yoga poses. This application provides a host of beginner to advanced poses that women can perform in order to better appreciate what their bodies are capable of. In order to provide women with accurate feedback on their performance, Posetivity operates a custom machine learning detection model that can take images provided by the user to determine whether or not the user’s pose matches the pose they selected. In addition, this application also provides women with records of their poses, so they can reflect on their personal journey toward a body-positive mindset. To provide women with a network of support that can accompany them on the app, Posetivity contains a safe space for women to post their poses and give and receive encouragement through likes. Ultimately, we hope that with all of these features Posetivity can guide women toward the self-love and empowerment that many females around the world seek.

Posetivity’s future plans include incorporating comments in the community, so women can provide more meaningful encouragement for each other. In addition, as with any machine learning model, the accuracy of Posetivity’s machine learning model can be improved by adding more images and training it for longer. We also plan to reorganize our file and document storage in order to improve its efficiency and processing time.

Posetivity was created on XCode with Swift as an iOS Application project. We used Google Firebase Cloud Firestore to store our documents and Google Firebase Cloud Storage for our images. We also incorporated Google AutoML Vision Edge and Tensor Flow Lite to train and deploy a classification model that labels a couple of poses from images taken from the iPhone gallery and camera.

After two days of coding, we have learned so much at our first Hackathon. Thank you to everyone who made this online event possible.

Link to Hackathon: https://girlshoohack2020.hackerearth.com/

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Built during Girls Hoo Hack Hackathon 2020. Won 1st for the Best Use of Google Cloud and won Best Overall for the entire hackathon.

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