CatBot

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  Using camera to scan face

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  Analyzing neutral face

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  Neutral emotion conversation

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  Analyzing happy face

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  Happy emotion conversation

What we learned

Through the development of CatBot, we learned how to use the DeepFace library to integrate facial recognition technology, and we learned how. We also learned how to utilize Dialogflow ES to design and integrate a user interface that is able to talk to the user. We also gained valuable experience in creating chatbots that can communicate with users based on their emotional state.

What it does

CatBot is a chatbot that analyzes the user's facial expressions and detects their emotional state by using the DeepFace and OpenCV libraries. Once the emotion is detected, CatBot communicates with the user via Google’s DialogFlow ES, providing appropriate responses based on the user's emotional state.

How we built it

CatBot was built using a combination of Python, DialogFlow ES, DeepFace, and OpenCV. We used the OpenCV library to capture the user's face in real-time, and then used DeepFace to analyze the facial features and detect the user's emotion. We integrated the facial recognition feature with DialogFlow ES to allow CatBot to communicate with the user.

Challenges we ran into

One of the main challenges we faced was integrating the various technologies and libraries together. We had to ensure that the facial recognition feature was seamlessly integrated with DialogFlow ES to provide a smooth user experience. We also had to fine-tune and train our DialogFlow model to ensure accurate conversations. Additionally, just making a functional user interface was a challenge as much of it was new to us.

Accomplishments that we're proud of

We are proud of developing a chatbot that can analyze the user's emotions and respond appropriately. We are also proud of integrating multiple technologies and libraries, most of which we’ve never used before, to create a seamless user experience.

What we learned

Through the development of CatBot, we learned how to use the DeepFace library to integrate facial recognition technology, and we learned how to utilize the OpenCV library to capture the face of the user. We also learned how to utilize Google's Dialogflow ES to design and integrate a way for users to communicate with the bot as well as making user interfaces in Python by using Tkinter allowing for users to directly interact with it.

What's next for Cat Bot

We want to make Cat Bot to have deeper conversations that are more personalized and tailored to each user. Additionally, we also want to update the UI to make it a better overall experience to use Cat Bot.

Built With

• deepface
• google-dialogflowes
• opencv
• python