---
title: "Evaluate job result"
method: GET
path: "/api/{projectId}/deployment/evaluate"
tags: ["Deployment"]
---

# Evaluate job result

`GET /api/{projectId}/deployment/evaluate`

## Request

- Base URL: `https://studio.edgeimpulse.com/v1`
- URL: `https://studio.edgeimpulse.com/v1/api/{projectId}/deployment/evaluate`
- Auth: one of:
  - API key in header `x-api-key`
  - API key in cookie `jwt`
  - API key in header `x-jwt-token`
  - OAuth 2
    - Authorization code: `/v1/oauth/authorize`
    - Client credentials
    - Implicit: `/v1/oauth/authorize`
    - Password
    - Token URL: `/v1/oauth/token`
- TypeScript: <https://skmtc.dev/edgeimpulse/apis/edge-impulse-api/docs/api/:projectId/deployment/evaluate/get.ts> (a function with typed inputs; its response is checked against the schema)

Get evaluate job result, containing detailed performance statistics for every possible variant of the impulse.

## Path parameters

- `projectId` integer, required

## Query parameters

- `impulseId` integer

## Response `200`

OK

- EvaluateJobResponse
  - `success` boolean, required: Whether the operation succeeded
  - `error` string: Optional error description (set if 'success' was false)
  - `result` ModelVariantStats[], required
    - `modelType` 'int8' | 'float32' | 'akida' | 'requiresRetrain', required
    - `learnBlockId` integer, required: The learning block this model variant is from
    - `learnBlockType` 'anomaly' | 'anomaly-gmm' | 'keras' | 'keras-transfer-image' | 'keras-transfer-kws' | 'keras-object-detection' | 'keras-regression' | 'keras-akida' | 'keras-akida-transfer-image' | 'keras-akida-object-detection' | 'keras-visual-anomaly' | 'keras-freeform' | 'keras-self-contained-freeform' | 'keras-anomaly' | 'vlm', required: The type of learning block (anomaly, keras, keras-transfer-image, ...). Each behaves differently.
    - `confusionMatrix` object, required: A map from actual labels to predicted labels, where actual labels are listed in `trainingLabels` and possible predicted labels are listed in `classificationLabels`.
    - `trainingLabels` string[], required: The labels present in the model's training data. These are all present in the first dimension of the confusion matrix.
    - `classificationLabels` string[], required: The possible labels resulting from classification. These may be present in the second dimension of the confusion matrix.
    - `totalWindowCount` integer: The total number of windows that were evaluated
    - `totalCorrectWindowCount` EvaluateResultValue
      - `raw` number: The value based on the model alone
      - `withAnomaly` number: The value including the result of anomaly detection
    - `accuracy` EvaluateResultValue, required
      - `raw` number: The value based on the model alone
      - `withAnomaly` number: The value including the result of anomaly detection

---

[API](https://skmtc.dev/edgeimpulse/apis/edge-impulse-api.md) - [All operations](https://skmtc.dev/edgeimpulse/apis/edge-impulse-api/llms.txt) - [OpenAPI document](https://skmtc.dev/edgeimpulse/apis/edge-impulse-api/revisions/e2a976d38427?raw)