This project utilizes computer vision techniques to estimate body measurements from front and side images of a person. It uses OpenCV and Mediapipe for landmark detection.

Setup

Requirements

Docker
Mediapipe

Install Docker

Follow the instructions on the official Docker website to install Docker on your system.

How to Run the Code

Using Docker

Build the Docker image:
```
docker build -t <docker_image> .
```

Run the Docker container:

docker run -it <docker_image> --front <path/to/front_image.jpg> --side <path/to/side_image.jpg> --person_height <height_in_cm> --yaml_file <pth/to/config.yml>    ```

Command Line Arguments

--front: Path to the front image.
--side: Path to the side image.
--pose_detection_confidence: (Optional) Confidence score for pose detection (default: 0.5).
--pose_tracking_confidence: (Optional) Confidence score for pose tracking (default: 0.5).
--person_height: Height of the person in centimeters.
--pixel_height: (Optional) Pixel height of the person.
--measurement: (Optional) Type of measurement.
--yaml_file: Path to the YAML file containing landmarks.

Example Command

docker run -it landmarks --front ./assets/aparna_front.jpg --side ./assets/aparna_side.jpg --person_height 157 --yaml_file config.yml