The end-product serves as a middleware that would preprocess images received from a mobile app and run human face detection, face shape detection, personality analysis, search engine for fashion items, and product recommendation system on the given image and would return a response based on the detections.
- Utilized Flask as a web framework to develop the backend of machine learning models as APIs.
- Used scikit-learn for feature extraction and dataset splitting in the machine learning models.
- Employed TensorFlow for facial landmark models and image preprocessing in the machine learning models.
- Used Pandas for preprocessing tabular data in the machine learning models.