We've provided some examples in Jupyter Notebooks to focus on ease of use, and some examples in Python apps to provide a more robust and complete experience.
If you have a cool app that uses the Landing AI SDK and you would like to have it featured here, please let us know.
|Poker Card Suit Identification||This notebook shows how to use an object detection model from LandingLens to detect suits on playing cards. A webcam is used to take photos of playing cards.||Jupyter Notebook|
|Door Monitoring for Home Automation||This notebook shows how to use an object detection model from LandingLens to detect whether a door is open or closed. An RTSP camera is used to acquire images.||Jupyter Notebook|
|Satellite Images and Post-Processing||This notebook shows how to use a Visual Prompting model from LandingLens to identify different objects in satellite images. The notebook includes post-processing scripts that calculate the percentage of ground cover that each object takes up.||Jupyter Notebook|
|License Plate Detection and Recognition||This notebook shows how to extract frames from a video file and use a object detection model and OCR from LandingLens to identify and recognize different license plates.||Jupyter Notebook|
|Streaming Video||This application shows how to continuously run inference on images extracted from a streaming RTSP video camera feed.||Python application|
Run Examples Locally
All the examples in this repo can be run locally.
To give you some guidance, here's how you can run the
rtsp-capture example locally in a shell environment:
- Clone the repo to local:
- Install the library (to see how to install
poetry, go here):
- Activate the virtual environment:
- Run: python landingai-python/examples/capture-service/run.py