48 lines
1.4 KiB
Markdown
48 lines
1.4 KiB
Markdown
# Body Measurement Using Computer Vision
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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.
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## Setup
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### Requirements
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- Docker
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- Mediapipe
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### Install Docker
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Follow the instructions on the [official Docker website](https://docs.docker.com/get-docker/) to install Docker on your system.
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## How to Run the Code
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### Using Docker
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1. **Build the Docker image:**
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```sh
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docker build -t <docker_image> .
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```
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2. **Run the Docker container:**
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```sh
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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>
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```
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### Command Line Arguments
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- `--front`: Path to the front image.
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- `--side`: Path to the side image.
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- `--pose_detection_confidence`: (Optional) Confidence score for pose detection (default: 0.5).
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- `--pose_tracking_confidence`: (Optional) Confidence score for pose tracking (default: 0.5).
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- `--person_height`: Height of the person in centimeters.
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- `--pixel_height`: (Optional) Pixel height of the person.
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- `--measurement`: (Optional) Type of measurement.
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- `--yaml_file`: Path to the YAML file containing landmarks.
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### Example Command
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```sh
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docker run -it landmarks --front ./assets/aparna_front.jpg --side ./assets/aparna_side.jpg --person_height 157 --yaml_file config.yml
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```
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