semvec/pypi-packages huggingface dataset:
linkedin-jobs-pyscraper 1.0.0
Scrape public jobs postings from LinkedIn in native python without selenium or any headless browser.
Requires Python: >=3.6

# Linkedin Jobs PyScraper

## Install Package from Pypi
1. Install it using pip.
```bash
pip install linkedin-jobs-pyscraper
```
## Example Usage
2. Use it in your code
```python
from linkedin_jobs_pyscraper.models.search.searcher import Searcher
from linkedin_jobs_pyscraper.models.filters import filters
from linkedin_jobs_pyscraper.linkedin_jobs_scraper import LinkedInJobsPyScraper

## create searach query with configurations
searcher = Searcher(
    search_pages_per_search_term = 4,
    search_terms = ['data analyst', 'data scientist'],
    batch_size = 5,
    output_filepath = 'out.csv',
    location = 'Germany'
    )

search_filter = filters.Filters(
    experience= filters.ExperienceLevelFilters.INTERNSHIP,
    job_type= filters.TypeFilters.INTERNSHIP,
    relevance= filters.RelevanceFilters.RECENT,
    time= filters.TimeFilters.MONTH
    )
scraper = LinkedInJobsPyScraper(searcher= searcher, filters=search_filter) 
scraper.start()
```
rembg-greenscreen 2.1.10
Rembg Virtual Green Screen
Requires Python: >=3.8, <4
Keywords: remove,background,u2net,greenscreen,green screen,matte

# Rembg Virtual Greenscreen Edition (Dr. Tim Scarfe)


Rembg Virtual Greenscreen Edition is a tool to create a green screen matte for videos

<p style="display: flex;align-items: center;justify-content: center;">
  <img src="https://raw.githubusercontent.com/ecsplendid/rembg/master/examples/greenscreen.png" width="100%" />
</p>

## Video Virtual Green Screen Edition

[15th Jan 2021 -- made a new YouTube explainer](https://www.youtube.com/watch?v=4NjqR2vCV_k)

* Take any  video file and convert it to an alpha matte to apply for a virtual green screen
* It runs end-to-end non-interactively 
* You need ffmpeg installed and on your path
* There is also a powershell script `./remove-bg.ps1` which will do the job in a manual way i.e. first create frames, then run the `rembg -p ...` command and then run ``ffmpeg`` to create the matte movie. This was my first approach to solve this problem but then I migrated onto just making a new version of rembg.  

If you have any ideas for speeding this up further, please let us know. We have tried quite a few things at this stage and are a bit stuck on how to proceed from here. See some of the "evolution" in  the [Whimsical notes](https://whimsical.com/ffmpeg-virtial-greenscreen-tS2T9uthKdCWhxvBAFUcy).

Usage;

```
pip install rembg-greenscreen

greenscreen -g "path/video.mp4"
```

Experimental parallel green screen version;

```
greenscreen --parallelgreenscreen "path/video.mp4" --workernodes 3 --gpubatchsize 5
```

The command above will produce a `video.matte.mp4` in the same folder, also works with `mov` and `avi` extensions. Uses ffmpeg under the hood to stream and re-encode the frames into a grayscale matte video. 

Be careful with the default parameters, my 11GB GPU is already pretty much maxed with 3 instances of the NN with 5 image gpu batches in forward pass. 

You can see how much free GPU ram you have with 

```
nvidia-smi
```

## CLI interface

<p style="display: flex;align-items: center;justify-content: center;">
  <img src="https://raw.githubusercontent.com/ecsplendid/rembg/master/examples/greenscreen_cli.png" width="65%" />
</p>

## Important notes

* Don't use VBR videos, it will run forever -- use Handbrake to convert them to CFR

### References

- https://arxiv.org/pdf/2005.09007.pdf
- https://github.com/NathanUA/U-2-Net (thanks to these folks for making the semantic segmentation model and publishing online)

### License

 - Copyright (c) 2020-present [Daniel Gatis](https://github.com/danielgatis)
 - Copyright (c) 2020-present [Dr. Tim Scarfe](https://github.com/ecsplendid)
 - Copyright (c) 2020-present [Lucas Nestler](https://github.com/ClashLuke) (Making it go faster and more stuff running on the GPU, thanks Lucas!)

Licensed under [MIT License](./LICENSE.txt)