Deploy YOLOv5
using Serve YOLOv5 app to serve models and can be used to deploy custom and pretrained models that you can use via Apply NN
layer. Custom models will appear in the custom tab of the table only if you have any trained YOLOv5 models in your Team Files. You can train your own model using Train YOLOv5 app. If you want to use pretrained models, simply select "Pretrained public models" tab in model selector.
- Add
Deploy YOLOv5
layer - Open agent settings and select agent and device
- Open models selector and select one of the available models
- Press
SERVE
- Wait until model is deployed, you will see "Model deployed" message in the bottom of the layer card
- Connect this layer to
Apply NN Inference
layer'sDeployed model (optional)
socket - If you want to deploy another model, press
STOP
and repeat steps 3, 4, 5 and 6
- Select agent - select agent and device that will be used for deployment:
Agent
- select agentDevice
- select CPU or GPU (faster) device if available
- Select model - select custom or pretrained model
Model type
- custom or pretrainedCheckpoint
- select checkpoint
- Auto stop model session - automatically stop model session when pipeline is finished
JSON view
{ "action": "deploy_yolov5", "src": [], "dst": "$deploy_yolov5_1", "settings": { "agent_id": 348, "device": "cuda:0", "model_type": "Pretrained models", "model_name": "YOLOv5nu", "task_type": "object detection", "model_path": null, "stop_model_session": true, "session_id": 60050 } }