task_categories:image-to-image task_categories:object-detection language:en license:cc-by-nc-nd-4.0 code medical region:us
The dataset contains a collection of frames extracted from videos captured within a
**hospital environment**. The **bounding boxes** are drawn around the **doctors, nurses,
and other people** who appear in the video footage.
The dataset can be used for **computer vision in healthcare settings** and *the
development of systems that monitor medical staff activities, patient flow, analyze
wait times, and assess the efficiency of hospital processes*.
@InProceedings{huggingface:dataset,
title = {medical-staff-people-tracking},
author = {TrainingDataPro},
year = {2023}
}
---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-to-image
- object-detection
tags:
- code
- medical
dataset_info:
- config_name: video_01
  features:
  - name: id
    dtype: int32
  - name: name
    dtype: string
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: shapes
    sequence:
    - name: track_id
      dtype: uint32
    - name: label
      dtype:
        class_label:
          names:
            '0': nurse
            '1': doctor
            '2': other_people
    - name: type
      dtype: string
    - name: points
      sequence:
        sequence: float32
    - name: rotation
      dtype: float32
    - name: occluded
      dtype: uint8
    - name: attributes
      sequence:
      - name: name
        dtype: string
      - name: text
        dtype: string
  splits:
  - name: train
    num_bytes: 27856
    num_examples: 64
  download_size: 23409734
  dataset_size: 27856
- config_name: video_02
  features:
  - name: id
    dtype: int32
  - name: name
    dtype: string
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: shapes
    sequence:
    - name: track_id
      dtype: uint32
    - name: label
      dtype:
        class_label:
          names:
            '0': nurse
            '1': doctor
            '2': other_people
    - name: type
      dtype: string
    - name: points
      sequence:
        sequence: float32
    - name: rotation
      dtype: float32
    - name: occluded
      dtype: uint8
    - name: attributes
      sequence:
      - name: name
        dtype: string
      - name: text
        dtype: string
  splits:
  - name: train
    num_bytes: 37214
    num_examples: 73
  download_size: 28155019
  dataset_size: 37214
---

# Medical Staff People Tracking

The dataset contains a collection of frames extracted from videos captured within a **hospital environment**. The **bounding boxes** are drawn around the **doctors, nurses, and other people** who appear in the video footage. 

The dataset can be used for **computer vision in healthcare settings** and *the development of systems that monitor medical staff activities, patient flow, analyze wait times, and assess the efficiency of hospital processes*.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F923816c1040f503bbe0cb20c8d1f2446%2Fezgif.com-optimize.gif?generation=1695376624951041&alt=media)

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=medical-staff-people-tracking) to discuss your requirements, learn about the price and buy the dataset.

# Dataset structure
The dataset consists of 2 folders with frames from the video from a hospital. 
Each folder includes:
- **images**: folder with original frames from the video,
- **boxes**: visualized data labeling for the images in the previous folder,
- **.csv file**: file with id and path of each frame in the "images" folder,
- **annotations.xml**: contains coordinates of the bounding boxes, created for the original frames

# Data Format

Each frame from `images` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the bounding boxes for people tracking. For each point, the x and y coordinates are provided.

### Classes:
- **doctor** - doctor in the frame
- **nurse** - nurse in the frame
- **others** - other people (not medical staff)

# Example of the XML-file 
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F778b3f19625b76cdc5454d58258fa0aa%2Fcarbon%20(1).png?generation=1695995011699193&alt=media)

# Object tracking might be made in accordance with your requirements.

## **[TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=medical-staff-people-tracking)** provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**