https://github.com/darcyai/darcyai

Darcy AI Engine is a Python library for building AI apps
https://github.com/darcyai/darcyai

ai ai-pipeline computer-vision edge edge-computing edgeai iot open-source opencv python raspberry-pi

Last synced: 6 days ago
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Darcy AI Engine is a Python library for building AI apps

• Host: GitHub
• URL: https://github.com/darcyai/darcyai
• Owner: darcyai
• License: apache-2.0
• Created: 2022-02-15T00:25:51.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2023-09-05T23:01:12.000Z (about 1 year ago)
• Last Synced: 2024-09-17T00:24:21.855Z (2 months ago)
• Topics: ai, ai-pipeline, computer-vision, edge, edge-computing, edgeai, iot, open-source, opencv, python, raspberry-pi
• Language: Python
• Homepage: https://docs.darcy.ai
• Size: 53.3 MB
• Stars: 7
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Darcy AI Engine

![AI Engine Pipeline](https://github.com/darcyai/darcyai/raw/main/.assets/pipeline-example-visual%402x-100.jpg)

Darcy AI Engine is a Python library that makes building AI apps as easy as building any other type

of app. AI Engine exposes high-level constructs ([`InputStream`](https://darcyai.github.io/darcyai/input-streams/inputstream/),

[`Perceptor`](https://darcyai.github.io/darcyai/perceptors/perceptor/), `Callback`,

[`OutputStream`](https://darcyai.github.io/darcyai/output-streams/outputstream/))

that you assemble in a `Pipeline` with a few lines of Python.

To get started, see the [Build Guide](https://docs.darcy.ai/docs/guides/build/), look

at the [examples](https://github.com/darcyai/darcyai/tree/main/src/examples), and consult

the [Python reference docs](https://darcyai.github.io/darcyai/).

## Example

This code (from [basic.py](https://github.com/darcyai/darcyai/tree/main/src/examples/basic_pipeline/basic.py)) shows how easy it

is to create a minimal AI Engine pipeline:

```python

#Add the DarcyAI components that we need, particularly the InputStream, OutputStream, Pipeline, and PerceptorMock

from darcyai.tests.perceptor_mock import PerceptorMock

from darcyai.pipeline import Pipeline

from sample_input_stream import SampleInputStream

from sample_output_stream import SampleOutputStream

#Define a class to hold all of our operations

class SingleStreamDemo():

    def __init__(self):

        #Create an input stream and an output stream that we can use in our demo

        ping = SampleInputStream()

        output_stream = SampleOutputStream()

        #Give our class a pipeline property and instantiate it with a Darcy AI pipeline

        self.__pipeline = Pipeline(input_stream=ping,

                                   input_stream_error_handler_callback=self.__input_stream_error_handler_callback,

                                   universal_rest_api=True,

                                   rest_api_base_path="/pipeline",

                                   rest_api_port=8080)

        #Add our output stream to the pipeline

        self.__pipeline.add_output_stream("output", self.__output_stream_callback, output_stream)

        #Create a mock perceptor and add it to the pipeline

        p1 = PerceptorMock()

        self.__pipeline.add_perceptor("p1", p1, accelerator_idx=0, input_callback=self.__perceptor_input_callback)

    #Define a "run" method that just calls "run" on the pipeline

    def run(self):

        self.__pipeline.run()

    #Define an input callback for the mock perceptor that just sends the data onward with no manipulation

    def __perceptor_input_callback(self, input_data, pom, config):

        return input_data

    #Define an output stream callback that does not manipulate the data

    def __output_stream_callback(self, pom, input_data):

        pass

    #Define an input stream error handler callback that just continues onward

    def __input_stream_error_handler_callback(self, exception):

        pass

#In the main thread, start the application by instantiating our demo class and calling "run"

if __name__ == "__main__":

    single_stream = SingleStreamDemo()

    single_stream.run()

```

## Issues, Contributing, Discussion

If you discover issues with AI Engine, view the [issues](https://github.com/darcyai/darcyai/issues),

or create a new one. You can also submit a [Pull Request](https://github.com/darcyai/darcyai/pulls),

or join the [discussions](https://github.com/darcyai/darcyai/discussions).