S.21Machine learningApril – May 2025shipped

Age & Gender Detection

A transfer-learning pipeline with no training required

Real-time face detection predicting gender and age bracket from images or webcam video, built entirely on OpenCV's DNN module with pre-trained Caffe models.

Age buckets
8
0–2 through 60–100
Training required
None
Caffe Model Zoo weights
Input
Image or webcam

The pipeline locates faces with OpenCV's DNN face detector, then runs each detected region through two separate CNNs — one for gender, one for age — bucketing predictions into eight ranges: 0–2, 4–6, 8–12, 15–20, 25–32, 38–43, 48–53 and 60–100. Results are drawn onto the source image or video frame.

Everything runs on pre-trained Caffe Model Zoo weights with no training step, which is the point: it is a demonstration of an end-to-end transfer-learning pipeline for facial attribute prediction, assembled rather than trained.

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