Source code for rastervision.core.rv_pipeline.object_detection_config

from enum import Enum
from typing import Optional

from rastervision.pipeline.config import register_config, Config, Field
from rastervision.core.rv_pipeline import RVPipelineConfig, PredictOptions
from import ObjectDetectionGeoJSONStoreConfig
from rastervision.core.evaluation import ObjectDetectionEvaluatorConfig

[docs]class ObjectDetectionWindowMethod(Enum): """Enum for window methods Attributes: chip: the default method """ chip = 'chip' label = 'label' image = 'image' sliding = 'sliding'
[docs]@register_config('object_detection_chip_options') class ObjectDetectionChipOptions(Config): neg_ratio: float = Field( 1.0, description= ('The ratio of negative chips (those containing no bounding ' 'boxes) to positive chips. This can be useful if the statistics ' 'of the background is different in positive chips. For example, ' 'in car detection, the positive chips will always contain roads, ' 'but no examples of rooftops since cars tend to not be near rooftops.' )) ioa_thresh: float = Field( 0.8, description= ('When a box is partially outside of a training chip, it is not clear if (a ' 'clipped version) of the box should be included in the chip. If the IOA ' '(intersection over area) of the box with the chip is greater than ioa_thresh, ' 'it is included in the chip.')) window_method: ObjectDetectionWindowMethod = ObjectDetectionWindowMethod.chip label_buffer: Optional[int] = None
[docs]@register_config('object_detection_predict_options') class ObjectDetectionPredictOptions(PredictOptions): merge_thresh: float = Field( 0.5, description= ('If predicted boxes have an IOA (intersection over area) greater than ' 'merge_thresh, then they are merged into a single box during postprocessing. ' 'This is needed since the sliding window approach results in some false ' 'duplicates.')) score_thresh: float = Field( 0.5, description= ('Predicted boxes are only output if their score is above score_thresh.' ))
[docs]@register_config('object_detection') class ObjectDetectionConfig(RVPipelineConfig): """Configure an :class:`.ObjectDetection` pipeline.""" chip_options: ObjectDetectionChipOptions = ObjectDetectionChipOptions() predict_options: ObjectDetectionPredictOptions = ObjectDetectionPredictOptions( )
[docs] def build(self, tmp_dir): from rastervision.core.rv_pipeline.object_detection import ObjectDetection return ObjectDetection(self, tmp_dir)
[docs] def get_default_label_store(self, scene): return ObjectDetectionGeoJSONStoreConfig()
[docs] def get_default_evaluator(self): return ObjectDetectionEvaluatorConfig()