Labels and categorizes images to indicate whether they contain violent, parodic, adult, medical or racy elements. ???+ info “API integration” To use this step your team needs to have the Google Vision integration configured in Graphext. The corresponding credentials are required to connect to a third-party API. You can configure API integrations following theDocumentation Index
Fetch the complete documentation index at: https://docs.graphext.com/llms.txt
Use this file to discover all available pages before exploring further.
INTEGRATIONS or ADD INTEGRATION
link in the top-left corner of your Team’s page, selecting API keys, and then the name of the desired third-party service.
To enable the Google Vision integration in particular you will need access to Google’s Vision service. Follow the instructions
shere to create the required API key.
Usage
The following example shows how the step can be used in a recipe.Examples
Examples
- Example 1
- Signature
The step has no configuration parameters, so it’s simply
Inputs & Outputs
The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced
by name e.g. "churn-clf").
Inputs
Inputs
Direct URLs to the images to analyze, e.g. https://upload.wikimedia.org/wikipedia/commons/c/c7/Madrid_-_El_Oso_y_el_Madro%C3%B1o.jpg.
Outputs
Outputs
Lists of entities identified in the picture.
Indicates whether the image contains violence.
Indicates whether the image is a spoof (parody).
Indicates whether the image features adult content.
Indicates whether the image features medical content.
Indicates whether the image features racy content.
Configuration
The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e.step(..., {"param": "value", ...}) -> (output).
Parameters
Parameters
ID of the integration you’d like to use.