65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Step4 处理器：预测采样点生成
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将原 WaterQualityInversionPipeline.step4_sampling() 方法
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剥离为独立的 Step4SamplingHandler。
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"""
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import time
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from typing import Any, Dict
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from src.core.handlers.base import BaseStepHandler, PipelineContext
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from src.core.steps.prediction_step import PredictionStep
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class Step4SamplingHandler(BaseStepHandler):
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"""步骤4：生成预测采样点并提取光谱。
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对应 config key: 'step4_sampling'
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委托类: PredictionStep.generate_sampling_points()
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"""
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step_key = 'step4_sampling'
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def execute(self, context: PipelineContext, config: dict) -> Dict[str, Any]:
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step_start_time = time.time()
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deglint_img_path = self._resolve_path(
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config.get('deglint_img_path'), context.deglint_img_path, 'deglint_img'
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)
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water_mask_path = self._resolve_path(
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config.get('water_mask_path'), context.water_mask_path, 'water_mask'
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)
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glint_mask_path = self._resolve_path(
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config.get('glint_mask_path'), context.glint_mask_path, 'glint_mask'
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)
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try:
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result = PredictionStep.generate_sampling_points(
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deglint_img_path=deglint_img_path,
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interval=config.get('interval', 50),
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sample_radius=config.get('sample_radius', 5),
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chunk_size=config.get('chunk_size', 1000),
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water_mask_path=water_mask_path,
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glint_mask_path=glint_mask_path,
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output_dir=str(context.sampling_dir),
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use_adaptive_sampling=config.get('use_adaptive_sampling', True),
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)
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step_end_time = time.time()
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context.record_step_time(
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"步骤4: 生成预测采样点", step_start_time, step_end_time
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)
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return {'sampling_csv_path': result}
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except Exception as e:
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step_end_time = time.time()
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context.record_step_time(
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"步骤4: 生成预测采样点", step_start_time, step_end_time,
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status="failed", error=str(e)
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)
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raise
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