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The social interaction cloud has many components available for you to speed up creating social interactions with the robot’s.

Service

Command

Source

Demo filefiles

Install

Dialogflow for creating conversational agents using google’s framework. This provides a flow chart like dialog management and speech recognition.

run-dialogflow

dialogflow Extra dependencies need to be installed:

demo_desktop_microphone_dialogflow.py or demo_nao_dialogflow.py

pip install social-interaction-cloud[dialogflow]

Face detection using OpenCV’s cascading classifier, which is very fast and can run on a laptop CPU

run-face-detection

face_detection

demo_desktop_camera_facedetection.py

None, no extra dependencies are needed

DNN Face detection using a YOLOv7 neural network for accurate detection, and detection of small faces.

run-face-detection-dnn

face_detection_dnn

DNN Face recognition using a resnet50 network to extract face embeddings and assign an id based on automatic clustering.

run-face-recognition --model xxx.pt --cascadefile xxx.xml

face_recognition_dnn

demo_desktop_camera_facerecognition.py

pip install social-interaction-cloud[face-recognition]

OpenAI ChatGPT a text based large language model that provides a very capable dialog agent. Requires a credit card.

run-gpt

gpt

demo_openai_gpt.py

pip install social-interaction-cloud[openai-gpt]

OpenAI Whisper a powerful speech to text model, capable of running both local and in the cloud. Cloud usage requires a credit card. Start and end recognition is performed using python’s https://pypi.org/project/SpeechRecognition/

run-whisper

whisper_speech_to_text

demo_desktop_microphone_whisper.py

pip install social-interaction-cloud[whisper-speech-to-text]

Google Text to speech using google cloud API. Requires a credit card.

text2speech

Templates for creating your own components

templates

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