Monitor Model Predictions
Pre-requisite
In order to monitor your models in production, you need to create a deployment.
import requests
deployment_id = os.environ["PICSELLIA_DEPLOYMENT_ID"]
url = f"https://example.com/api/v1/deployment/{deployment_id}/add"
encoded_image = base64.b64encode(image).decode('utf-8')
payload = {
"platform_host": "localhost",
"raw_predictions": {
"labels": [0, 2],
"boxes": [[0, 5, 100, 150], [0, 2, 20, 60]],
"detection_scores": [0.5, 0.7]
},
"tags": {"condition": "sunny"},
"latency": 0.1,
"picture_id": "uuid4",
"filename": "picture1.png",
"height": 800,
"width": 900,
"source": "aws_ec2_eu_west_3",
"model_type": "detection",
"model": "detection-efficientnet-1",
"image": encoded_image
}
headers = {
"Accept": "application/json",
"Content-Type": "application/json"
}
response = requests.request("POST", url, json=payload, headers=headers)
print(response.text)
Updated 4 months ago