Skip to content

Latest commit

 

History

History
113 lines (80 loc) · 3.68 KB

MultiLabelClassificationModelApi.md

File metadata and controls

113 lines (80 loc) · 3.68 KB
Raw

nanonets.MultiLabelClassificationModelApi

All URIs are relative to https://app.nanonet.com/api/v2

Method HTTP request Description
multi_label_classification_by_model_id_get GET /MultiLabelClassification/Model/{model_id} Get Model by Id
multi_label_image_classification_post POST /MultiLabelClassification/Model/ Create New Model

multi_label_classification_by_model_id_get

multi_label_classification_by_model_id_get(model_id)

Get Model by Id

This endpoint retrieves a specific model's details given it's id.

Example

from __future__ import print_function
import time
import nanonets
from nanonets.rest import ApiException
from pprint import pprint
# Configure HTTP basic authorization: ApiKey
configuration = nanonets.Configuration()
configuration.username = 'YOUR_USERNAME'
configuration.password = 'YOUR_PASSWORD'

# create an instance of the API class
api_instance = nanonets.MultiLabelClassificationModelApi(nanonets.ApiClient(configuration))
model_id = 'model_id_example' # str | 

try:
    # Get Model by Id
    api_instance.multi_label_classification_by_model_id_get(model_id)
except ApiException as e:
    print("Exception when calling MultiLabelClassificationModelApi->multi_label_classification_by_model_id_get: %s\n" % e)

Parameters

Name Type Description Notes
model_id str

Return type

void (empty response body)

Authorization

ApiKey

HTTP request headers

  • Content-Type: Not defined
  • Accept: application/json

[Back to top] [Back to API list] [Back to Model list] [Back to README]

multi_label_image_classification_post

multi_label_image_classification_post(body, content_type)

Create New Model

You can create a new model using this endpoint. A successful API call will return the json structure of the newly created model. You can then use the model's id to upload images for each category and then retrain the model.

Example

from __future__ import print_function
import time
import nanonets
from nanonets.rest import ApiException
from pprint import pprint
# Configure HTTP basic authorization: ApiKey
configuration = nanonets.Configuration()
configuration.username = 'YOUR_USERNAME'
configuration.password = 'YOUR_PASSWORD'

# create an instance of the API class
api_instance = nanonets.MultiLabelClassificationModelApi(nanonets.ApiClient(configuration))
body = nanonets.CreateNewModelrequest() # CreateNewModelrequest | 
content_type = 'content_type_example' # str | 

try:
    # Create New Model
    api_instance.multi_label_image_classification_post(body, content_type)
except ApiException as e:
    print("Exception when calling MultiLabelClassificationModelApi->multi_label_image_classification_post: %s\n" % e)

Parameters

Name Type Description Notes
body CreateNewModelrequest
content_type str

Return type

void (empty response body)

Authorization

ApiKey

HTTP request headers

  • Content-Type: application/json
  • Accept: application/json

[Back to top] [Back to API list] [Back to Model list] [Back to README]