semvec/pypi-packages huggingface dataset:
depthai-mock 0.0.3
The tool that allows you to record and playback the DepthAI generated frames
License: MIT
Keywords: depthai mock record tool development

# Depthai-Mock

This tool allows you to record the packets produced by DepthAI device into your disk
and then play them back again as they would be produced normally - but without actually running the DepthAI

## Installation

```
python3 -m pip install depthai-mock
```
## Usage

```
usage: depthai_mock [-h] [-nd] [-t TIME] [-ai] [-b BLOB] [-bc BLOB_CONFIG] [-p PATH] [-s STREAMS [STREAMS ...]]

optional arguments:
  -h, --help            show this help message and exit
  -nd, --no-display     Do not try display the incoming frames
  -t TIME, --time TIME  Limits the max time of the recording. Mandatory whenused with -nd (--no-display) option
  -ai, --enable-ai      Store also the nnet results
  -b BLOB, --blob BLOB  Path to nnet model .blob file
  -bc BLOB_CONFIG, --blob-config BLOB_CONFIG
                        Path to nnet model config .json file
  -p PATH, --path PATH  Path where to store the captured data
  -s STREAMS [STREAMS ...], --streams STREAMS [STREAMS ...]
                        Define which streams to enable Format: stream_name or stream_name,max_fps Example: -s metaout previewout Example: -s metaout previewout,10 depth_sipp,10
```

Having DepthAI connected, run
```
depthai_mock -s previewout
```

then, when `data` folder is there, you can unplug the DepthAI and run

```
cd depthai_mock
python3 test.py -p ../data
```
Dem 2.0
A python library to make using lists more easy
License: MIT

![https://pypi.org/project/Dem](https://img.shields.io/pypi/v/dem.svg)
![https://pypi.org/project/Dem](https://pypip.in/license/blackhole/badge.svg)

## Download

`pip install Dem`

## What is Dem

Dem is a python library to make using list more easy

## What dose it contain

Dem currently contains utilities to work with 2D lists(get_row, get_column, replace, find), convert 2d lists to 1d lists

## example

```python

import _2D
import convert._3D.to._1D

print(_2D.Replace([[1, 2, 3], [1, 2, 3], [1, 2, 3]], 3, 4))
print(_2D.Find([[1, 2, 3], [3, 2, 1], [3, 4, 5]], 2))
print(convert._3D.to._1D.RowMajor([[1, 2, 3], [3, 2, 1], [3, 4, 5]]))


```