Run Your First Model
Let's run a fine-tuned computer vision model to play rock paper scissors.
The Inference Server runs in Docker. Before we begin, make sure you have installed Docker on your system. To learn how to install Docker, refer to the official Docker installation guide.
Next, we need to install Inference:
pip install inference
We then need to start an Inference server. This server will manage inferences and is designed to scale. It can run on your local machine, a remote server, or even a Raspberry Pi.
inference server start
Create a new Python file called
app.py and add the following code:
import cv2 import inference import supervision as sv annotator = sv.BoxAnnotator() def on_prediction(predictions, image): labels = [p["class"] for p in predictions["predictions"]] detections = sv.Detections.from_roboflow(predictions) cv2.imshow( "Prediction", annotator.annotate( scene=image, detections=detections, labels=labels ) ), cv2.waitKey(1) inference.Stream( source="webcam", # or rtsp stream or camera id model="rock-paper-scissors-sxsw/11", # from Universe output_channel_order="BGR", use_main_thread=True, # for opencv display on_prediction=on_prediction, )
Next, sign up for a free Roboflow account. Retrieve your API key from the Roboflow dashboard, then run the following command:
export API_KEY=<your api key>
Then, run the Python script:
Your webcam will open and you can play rock paper scissors: