AI-Based Therapist – Real-Time Facial Emotion Recognition
Opencv AI Kit OakImageEmotion Recognition
Developed a real-time facial emotion recognition ML system that required precise labeling of facial images with emotion tags. Implemented preprocessing pipelines to curate and annotate datasets for training and evaluation purposes. Utilized OpenCV and Python to facilitate efficient labeling of facial data.
• Labeled facial images for emotions such as happiness, sadness, anger, and surprise.
• Ensured data privacy and integrity during the annotation process.
• Built and tested models using annotated image datasets.
• Enabled open-source collaboration through clear documentation of labeling standards.
Developed a real-time facial emotion recognition ML system that required precise labeling of facial images with emotion tags. Implemented preprocessing pipelines to curate and annotate datasets for training and evaluation purposes. Utilized OpenCV and Python to facilitate efficient labeling of facial data. • Labeled facial images for emotions such as happiness, sadness, anger, and surprise. • Ensured data privacy and integrity during the annotation process. • Built and tested models using annotated image datasets. • Enabled open-source collaboration through clear documentation of labeling standards.
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