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Update deploy and predict page #72

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30 changes: 22 additions & 8 deletions ...al-networks/inference-and-deployment/deploy_and_predict_with_supervisely_sdk.md
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Expand Up @@ -10,7 +10,7 @@ In-platform deployment is similar to manually launching a [Serving App](./superv

{% hint style="info" %}

This method only works for your models trained in Supervisely and stored in Team Files. It also requires Supervisely SDK version `6.73.305` or higher.
This method requires Supervisely SDK version `6.73.305` or higher. # TODO: update version

{% endhint %}

Expand All @@ -19,14 +19,15 @@ This method only works for your models trained in Supervisely and stored in Team
1. Install supervisely SDK if not installed.

```bash
pip install supervisely>=6.73.305
pip install supervisely>=6.73.305 # TODO: update version
```

2. Go to Team Files and copy the path to your model artifacts (`artifacts_dir`).
2. Go to Team Files and copy the path to your model artifacts (`artifacts_dir`) for custom model or use the name of the pretrained model.

![Copy path to artifacts dir](/.gitbook/assets/neural-networks/artifacts_dir.png)
![Copy app name and model name](/.gitbook/assets/neural-networks/pretrained_model.png)

3. Run this code to deploy a model on the platform. Don't forget to fill in your `workspace_id` and `artifacts_dir`.
3. Run this code to deploy a model on the platform. Don't forget to fill in your `team_id` and `artifacts_dir`.

```python
import os
Expand All @@ -38,12 +39,22 @@ load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api()

# ⬇ Put your workspace_id and artifacts_dir.
workspace_id = 123
# Custom model
# ⬇ Put your team_id and artifacts_dir.
team_id = 123
artifacts_dir = "/experiments/27_Lemons/265_RT-DETRv2/"

# Deploy model
task_id = api.task.deploy_custom_model(workspace_id, artifacts_dir)
# Deploy
session = api.nn.deploy_custom_model(artifacts_dir=artifacts_dir, team_id=team_id)

# Pretrained model
# ⬇ Put your app_name and model_name.
app_name="Serve RT-DETRv2"
model_name="rtdetr_r18vd"

# Deploy
session = api.nn.deploy_pretrained_model(app_name=app_name, model_name=model_name)

```

### 2. Predict
Expand All @@ -63,6 +74,9 @@ from supervisely.nn.inference import Session
# task_id was returned from the previous code
session = sly.nn.inference.Session(api, task_id=task_id)

# Or you can use session from the "Deploy" step
session = api.nn.deploy_custom_model(artifacts_dir=artifacts_dir, team_id=team_id)

# Predict Image
image_id = 123 # ⬅ put your image_id from a platform
prediction = session.inference_image_id(image_id)
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