semvec/pypi-packages huggingface dataset:
MedSim3D 0.0.1a3
Medical Simulation Framework in the 3D Environment
License: MIT
Requires Python: >=3.6, <4
Keywords: medical education,simulation,agent-based modeling,3D

## MedSim3D: Medical Simulation Framework in the 3D environment

The `MedSim3D` framework provides a general programmable platform for 3D modeling and simulation in medical education.

### Installation

```
    pip install MedSim3D
```

### Dependencies

tqdm, requests, numpy, cv2, shapely, quick-csv, pillow, pandas, pyntcloud, sklearn, matplotlib, scipy, skimage

### Examples

Example 1: Download datasets from [the Visible Human Project](https://www.nlm.nih.gov/databases/download/vhp.html). 

```python
from medsim3d.vhp.downloader import VHPDownloader
vhp_downloader=VHPDownloader()
vhp_downloader.download_datasets(
    gender="Male", # Male or Female
    body_part="head", 
    # Options: abdomen, head, legs, pelvis, thighs, thorax
    save_folder="datasets/male/head")
```

Example 2: Build human body part 3D models from colored slices

```python
from medsim3d.vhp.pipeline_bodypart import  *
# A pipeline to build body parts in a simple way
pipeline_pelvis=PipelineBodyPart(
    gender="Female",
    body_part="pelvis", 
    # Options: abdomen, head, legs, pelvis, thighs, thorax
    root_folder='../datasets/Female'
)
pipeline_pelvis.run(force_download=True)
```

Example 3: Build human full-body 3D models from CT images

```python
from medsim3d.vhp.pipeline_human import *
pipeline_human=PipelineHuman(
    gender='Male',
    ct_type='frozenCT', # normalCT
    root_path='../datasets/Male'
)
pipeline_human.run(force_download=True)
```

### Screenshots

(1) Medical image processing using the VHP data sets

![MedSim3D image processing](https://dhchenx.github.io/projects/MedSim3D/medsim3d-image-processing.png)


(2) 3D agent-based modeling in NetLogo using VHP data sets

![MedSim3D agent-based 3D modeing](https://dhchenx.github.io/projects/MedSim3D/medsim3d-agent-based-modeling.png)

### Credits

- [The NLM Visible Human Project](https://www.nlm.nih.gov/research/visible/visible_human.html)
- [Open3D](http://www.open3d.org/)

### License

The `MedSim3D` toolkit is provided by [Donghua Chen](https://github.com/dhchenx) with MIT License.
py2vision 1.0.3
A package to implement a stereo vision system trained with deep learning
License: MIT
Requires Python: >=3.6

# A package to do stereo vision using object detection

py2vision will allow you to determine the
homogeneous coordinates of a detected object with a neural network, in conjunction with stereo algorithms that allow you to find the disparity maps, to finally apply segmentation within each detection window and it is these segmented pixels that are used to find the real position of the object in 3D space.
These segmented pixels are used to find the actual position of the object in 3D space.

## **Installation**
Open a console and write this: 

`pip install py2vision`

**Note**: If you already have the opencv package installed, you have to uninstall it with pip uninstall opencv-python and install opencv-contrib-python version 4.6.0.66.

## **Application areas**
- Robotics
- Computer Vision
- Web apps with Object detection
- Surveillance

If you want to learn how to use it I recommend see inside tutorials folder because it have some tools and notebooks that can help you to understand how it's works.

Or you can see our documentation website here: https://corvus96.github.io/PyTwoVision/html/index.html