Nanonets

Nanonets Image Classification API

Classify images by file upload or by publicly accessible URL against a Nanonets image classification model. Supports batch URL submission for efficient prediction. Base path `/api/v2/ImageCategorization/LabelFile/` and `/api/v2/ImageCategorization/LabelUrls/`.

Nanonets Image Classification API is one of 4 APIs that Nanonets publishes on the APIs.io network, described by a machine-readable OpenAPI specification.

This API exposes 1 machine-runnable capability that can be deployed as REST, MCP, or Agent Skill surfaces via Naftiko.

Tagged areas include Image Classification, Computer Vision, and Deep Learning. The published artifact set on APIs.io includes API documentation, an OpenAPI specification, and 1 Naftiko capability spec.

GitHub OpenAPI

Documentation

📖
Documentation
https://docs.nanonets.com/reference/imagecategorizationlabelfilepost
📖
Documentation
https://docs.nanonets.com/reference/imagecategorizationlabelurlspost2

Specifications

⚙
OpenAPI
https://raw.githubusercontent.com/api-evangelist/nanonets/refs/heads/main/openapi/nanonets-image-classification-api-openapi.yml

Other Resources

🔗
NaftikoCapability
https://raw.githubusercontent.com/api-evangelist/nanonets/refs/heads/main/capabilities/image-classification.yaml

OpenAPI Specification

nanonets-image-classification-api-openapi.yml Raw ↑ 
openapi: 3.0.3
info:
  title: Nanonets Image Classification API
  description: |
    Predict against a Nanonets image classification model. Submit images either
    as multipart file uploads or as a batch of publicly accessible URLs.
  version: 2.0.0
  contact:
    name: Nanonets
    url: https://nanonets.com
    email: [email protected]
servers:
  - url: https://app.nanonets.com/api/v2
security:
  - BasicAuth: []
tags:
  - name: Image Classification Predict
    description: Predict on uploaded images or image URLs against a classification model.
paths:
  /ImageCategorization/LabelFile/:
    post:
      tags: [Image Classification Predict]
      summary: Prediction For Image File
      description: Upload a file from the local filesystem to an image classification model.
      operationId: imageCategorizationLabelFilePost
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              type: object
              required: [file, modelId]
              properties:
                file:
                  type: string
                  format: binary
                modelId:
                  type: string
                  description: Unique identifier of the classification model.
      responses:
        '200':
          description: Classification result.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ClassificationResponse'
  /ImageCategorization/LabelUrls/:
    post:
      tags: [Image Classification Predict]
      summary: Prediction For Image URLs
      description: Submit one or more publicly accessible image URLs for classification.
      operationId: imageCategorizationLabelUrlsPost
      requestBody:
        required: true
        content:
          application/x-www-form-urlencoded:
            schema:
              type: object
              required: [urls, modelId]
              properties:
                urls:
                  type: array
                  items: { type: string, format: uri }
                modelId:
                  type: string
      responses:
        '200':
          description: Classification result.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ClassificationResponse'
components:
  securitySchemes:
    BasicAuth:
      type: http
      scheme: basic
  schemas:
    ClassificationResponse:
      type: object
      properties:
        message: { type: string }
        result:
          type: array
          items:
            type: object
            properties:
              message: { type: string }
              prediction:
                type: array
                items:
                  type: object
                  properties:
                    label: { type: string }
                    probability: { type: number, minimum: 0, maximum: 1 }
              input: { type: string }