Practical 10

AIM: Using image data, predict the gender and age range of an individual in Python. Test the data science model using your own image. 

Theory:

OpenCV is a cross-platform library using which we can develop real-time computer vision applications. It mainly focuses on image processing, video capture and analysis including features like face detection and object detection.

Additional Python Libraries Required :

OpenCV pip install opencv-python 

argparse pip install argparse 

The contents of this Project :

opencv_face_detector.pbtxt

opencv_face_detector_uint8.pb

age_deploy.prototxt

age_net.caffemodel

gender_deploy.prototxt

gender_net.caffemodel

A few pictures to try the project on detect.py

For face detection, we have a .pb file- this is a protobuf file (protocol buffer); it holds the graph definition and the trained weights of the model. We can use this to run the trained model. And while a .pb file holds the protobuf in binary format, one with the .pbtxt extension holds it in text format. These are TensorFlow files. For age and gender, the .prototxt files describe the network configuration and the .caffemodel file defines the internal states of the parameters of the layers.

Usage :

• Download my Repository

• Open your Command Prompt or Terminal and change directory to the folder where all the files are present

• Detecting Gender and Age of face in Image Use Command : python detect.py --image <image_name>

Note: The Image should be present in same folder where all the files are present

• Detecting Gender and Age of face through webcam Use Command : python detect.py

• Press Ctrl + C to stop the program execution.

Entering Input

Showing age