semvec/pypi-packages huggingface dataset:
nely-df2d 0.14
2D pose estimation pipeline for tethered Drosophila.

# Drosophila 2D Pose

- Load the model.
```python
from model import Drosophila2DPose
from parser import create_parser

checkpoint_path = '/home/user/Desktop/DeepFly3D/weights/sh8_deepfly.tar'
args = create_parser().parse_args('')
model = Drosophila2DPose(checkpoint_path=checkpoint_path, **args.__dict__).cuda()
```

- Load the data.
```python
from inference import path2inp
from dataset import Drosophila2Dataset
from torch.utils.data import DataLoader

image_path = '/home/user/Desktop/DeepFly3D/data/test/'
inp = path2inp(image_path) # extract list of images under the folder
dat = DataLoader(Drosophila2Dataset(inp), batch_size=8)
```

- Do the inference.
```python
from inference import inference
points2d = inference(model, dat)
```
dj-ratelimit 0.1.5
Redis backed library implementing a django ratelimit

dj-ratelimit is a redis backed ratelimit for django requests. To use set the following
environment variables in your django settings:

    - ENVIRONMENT: default 'local'
    - DJ_RATELIMIT_REDIS_ADDRESS: default 'localhost'
    - DJ_RATELIMIT_REDIS_PORT: default '6379'

For more information see project github page 'py-ratelimit'
ampscz-anonymize-dicom 0.0.15
AMP-SCZ Dicom anonymizer
Requires Python: >=3.7

# AMP-SCZ Dicom Anonymizer

## Contents

Introduction
Dependencies
Installation
How to run AMP-SCZ Dicom Anonymizer


## Introduction


## Dependencies

#### Tested on osx
- xquartz (https://www.xquartz.org)
- `python` (3) with `pip` accessible in the shell



## Installation

Installation through `pypi`

```
$ pip install ampscz_anonymize_dicom
```


## How to run AMP-SCZ Dicom Anonymizer

```
$ ampscz_anonymize_dicom
```
1. Drag the root of the dicom directory
2. Drag the output directory
3. Edit the AMP-SCZ ID
4. Enter the session number
5. Click "Run deidentification"