With Roboflow Inference, you can deploy
Classification
models on a wide range of compute hardware devices, from NVIDIA Jetsons to T4 GPUs to AI PCs. You can connect
Lucid Vision Labs
cameras to your compute hardware and run inference with your model in real time.
In this guide, we are going to talk about how you can deploy computer vision models with Roboflow Inference and
Lucid Vision Labs
cameras.
Roboflow Workflows is a low-code, web-based computer vision application builder. WIth Workflows, you can build computer vision applications in an afternoon, then deploy them to your own edge hardware with custom cameras.
Below is an example of a Workflow that identifies common objects in images with the SAHI inference technique, which improves performance on small object detection.
This Workflow, like any Roboflow Workflow, can be deployed on your own hardware and infer on frames from
Lucid Vision Labs
cameras.
Roboflow Workflows is powered by Inference, an open source computer vision inference server. With Inference, you can run a wide variety of fine-tuned and foundation models, including:
- YOLOv5, YOLOv8, YOLOv9, and YOLOv10 object detection models
- YOLOv7 and YOLOv8 image segmentation models
- YOLOv8 keypoint detection models
- Florence-2
- SAM-2
- PaliGemma
You can deploy all of these models with frames retrieved from a
Lucid Vision Labs
camera.
YOLO models supported in Inference can run at dozens of frames per second on GPU hardware. Foundation models like PaliGemma and Florence-2 can run in close to real time.
The Roboflow
Lucid Vision Labs
integration is only available to Enterprise customers.
To learn more about our integrations with popular cameras, contact the Roboflow sales team.
You can deploy the Workflow above on your camera with any edge hardware in a few lines of Python code.
To deploy your system, first install Inference:
Then, create a new Python file and add the following code:
Above, set your Roboflow API key, your workspace name, and your Workflow ID.
Learn how to retrieve your API key and Workflow ID information.
To learn more about deploying computer vision models with Inference, refer to the Roboflow Inference documentation.