semvec/pypi-packages huggingface dataset:
thetestEyesOnIt 0.2.0
Easy computer vision
License: MIT
Requires Python: >=3.8

# EYESONIT Python SDK #

EyesOnIt makes advanced computer vision easy for anyone without data science 
or computer programming skills. Even without these skills, you can apply
cutting edge computer vision to your video streams and start receiving
alerts by text message in just a few minutes. If you have basic programming
skills, you can quickly enable endless scenarios like these:

- Motion-based detection: trigger computer vision after motion is detected
- Event recording: capture and store your own data about detections
- Image categorization: categorize a collection of images according to the contents

Traditional computer vision involves a complex process to train and tune
a computer vision model. This process typically requires weeks or months
of time from experts with an advanced and specialized skillset. The cost
for this process is often $50,000 to $100,000 USD or more. EyesOnIt is
different. With EyesOnIt, you describe what you want to detect with English
text. EyesOnIt compares your text to your image or video and tells you if
it detected what you described.


See this guide for running the EyesOnIt container:
https://www.eyesonit.us/userguide


### Installation ###

The python SDK can be installed with PIP

```
pip install eyesonit_python_sdk
```


### Usage ###

```
from EyesOnIt import EyesOnItSDK
from data.elements.eoi_prompt import EOIPrompt
from data.elements.eoi_region import EOIRegion
from data.elements.eoi_alerting import EOIAlerting

prompt_one = EOIPrompt(text='person', background_prompt=False, threshold=90)
prompt_two = EOIPrompt(text='trees', background_prompt=True)
prompts = [prompt_one, prompt_two]

region_one = EOIRegion(top_left_x=4, top_left_y=9, width=500, height=300)
regions = [region_one]


app = EyesOnItSDK('http://127.0.0.1:8000')

result = app.process_image(prompts=prompts, regions=regions, image="my_image.jpg")
print(result.success)
print(result.message)

```

### Questions? ###

email us at info@eyesonit.us
SpatialDE-SO 1.1.5.1
Spatial and Temporal DE test. This is a fork containing some bug fixes.
License: MIT

 # SpatialDE

This package wraps SpatialDE so it can be installed and used using PyPI after fixing some bugs.

All SpatialDE credit goes to the SpatialDE authors. Please check the original publication for more details: [Nature Methods](https://www.nature.com/articles/nmeth.4636).

If you use this package, please cite the original SpatialDE publication.