- YOLOv8 Instance Segmentation
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- YOLOv8 Instance Segmentation
- CSV Sink
- YOLOv8 Instance Segmentation
- CSV Sink
- YOLOv8 Instance Segmentation
- S3 Upload
YOLOv8 is a state-of-the-art object detection and image segmentation model created by Ultralytics, the developers of YOLOv5. YOLOv8, launched on January 10, 2023, features:
there are many YOLOv8 segmentation models released. These include:
• YOLOv8n-seg (Nano): Approximately 3.2 million parameters
• YOLOv8s-seg (Small): Approximately 11.2 million parameters
• YOLOv8m-seg (Medium): Approximately 25.9 million parameters
• YOLOv8l-seg (Large): Approximately 43.7 million parameters
• YOLOv8x-seg (Extra Large): Approximately 68.2 million parameters
First, install Inference:
pip install inference
To try a demo with a model trained on the Microsoft COCO dataset, use:
import inference
model = inference.load_roboflow_model("yolov8n-seg-640")
results = model.infer(image="YOUR_IMAGE.jpg")
Above, replace:
YOUR_IMAGE.jpg
with the path to your image.You can also run fine-tuned models with Inference.
Retrieve your Roboflow API key and save it in an environment variable called ROBOFLOW_API_KEY
:
export ROBOFLOW_API_KEY="your-api-key"
To use your model, run the following code:
import inference
model = inference.load_roboflow_model("model-name/version")
results = model.infer(image="YOUR_IMAGE.jpg")
Above, replace:
YOUR_IMAGE.jpg
with the path to your image.model_id/version
with the YOLOv8 model ID and version you want to use. Learn how to retrieve your model and version ID.