class_docstr: The schema for predictions or labels when doing classification, object detection, keypoint detection or instance segmentation 
class_docstr_tok: ["The","schema","for","predictions","or","labels","when","doing","classification",",","object","detection",",","keypoint","detection","or","instance","segmentation"]
docstr: Create an instance of PredictionTaskSchemaBase from a JSON string
docstr_tok: ["Create","an","instance","of","PredictionTaskSchemaBase","from","a","JSON","string"]
code: def from_json(
      cls, json_str: str
  ) -> Union(PredictionTaskSchemaKeypoint, PredictionTaskSchemaSimple):
      """Create an instance of PredictionTaskSchemaBase from a JSON string"""
      return cls.from_dict(json.loads(json_str))
  
file_path: lightly/lightly/openapi_generated/swagger_client/models/prediction_task_schema_base.py
imports: from __future__ import annotations
  import pprint
  import re
  import json
  import lightly.openapi_generated.swagger_client.models
  from pydantic import Extra, BaseModel, Field, StrictStr, constr, validator
label_desc: Use image node_id 5 for calling the PredictionTaskSchemaBase obj's underlying member method code with example usage: obj.from_json(cls, json_str) and returns: cls