parameters: ()
return_statement: return {
          'IOU_CONSTRAINT': 0.5,
          'AREA_PRECISION_CONSTRAINT': 0.5,
          'GT_SAMPLE_NAME_2_ID': 'gt_img_([0-9]+).txt',
          'DET_SAMPLE_NAME_2_ID': 'res_img_([0-9]+).txt',
          'LTRB': False,  # LTRB:2points(left,top,right,bottom) or 4 points(x1,y1,x2,y2,x3,y3,x4,y4)
          'CRLF': False,  # Lines are delimited by Windows CRLF format
          'CONFIDENCES': False,  # Detections must include confidence value. AP will be calculated
          'PER_SAMPLE_RESULTS': True  # Generate per sample results and produce data for visualization
      }
docstring: default_evaluation_params: Default parameters to use for the validation and evaluation.
docstring_summary: default_evaluation_params: Default parameters to use for the validation and evaluation.
docstring_tokens: default_evaluation_params : Default parameters to use for the validation and evaluation .
function: def default_evaluation_params():
      """
      default_evaluation_params: Default parameters to use for the validation and evaluation.
      """
      return {
          'IOU_CONSTRAINT': 0.5,
          'AREA_PRECISION_CONSTRAINT': 0.5,
          'GT_SAMPLE_NAME_2_ID': 'gt_img_([0-9]+).txt',
          'DET_SAMPLE_NAME_2_ID': 'res_img_([0-9]+).txt',
          'LTRB': False,  # LTRB:2points(left,top,right,bottom) or 4 points(x1,y1,x2,y2,x3,y3,x4,y4)
          'CRLF': False,  # Lines are delimited by Windows CRLF format
          'CONFIDENCES': False,  # Detections must include confidence value. AP will be calculated
          'PER_SAMPLE_RESULTS': True  # Generate per sample results and produce data for visualization
      }
function_tokens: def default_evaluation_params ( ) : return { 'IOU_CONSTRAINT' : 0.5 , 'AREA_PRECISION_CONSTRAINT' : 0.5 , 'GT_SAMPLE_NAME_2_ID' : 'gt_img_([0-9]+).txt' , 'DET_SAMPLE_NAME_2_ID' : 'res_img_([0-9]+).txt' , 'LTRB' : False , # LTRB:2points(left,top,right,bottom) or 4 points(x1,y1,x2,y2,x3,y3,x4,y4) 'CRLF' : False , # Lines are delimited by Windows CRLF format 'CONFIDENCES' : False , # Detections must include confidence value. AP will be calculated 'PER_SAMPLE_RESULTS' : True # Generate per sample results and produce data for visualization }