update readme file

Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY . /app
+
+RUN pip install --no-cache-dir -r requirements.txt
+RUN apt-get update && apt-get install ffmpeg libsm6 libxext6  -y
+
+ENTRYPOINT ["./entrypoint.sh"]

README.md

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+# Body Measurement Using Computer Vision
+
+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](https://docs.docker.com/get-docker/) to install Docker on your system.
+
+## How to Run the Code
+
+### Using Docker
+
+1. **Build the Docker image:**
+
+    ```sh
+    docker build -t <docker_image> .
+    ```
+
+2. **Run the Docker container:**
+
+    ```sh
+    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
+
+```sh
+docker run -it landmarks --front ./assets/aparna_front.jpg --side ./assets/aparna_side.jpg --person_height 157 --yaml_file config.yml
+```