Source code for raytraverse.sampler.imagesampler

# -*- coding: utf-8 -*-
# Copyright (c) 2020 Stephen Wasilewski, HSLU and EPFL
# =======================================================================
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
# =======================================================================
import os

import numpy as np

from raytools import io
from raytraverse.lightpoint import LightPointKD
from raytraverse.mapper import ViewMapper
from raytraverse.sampler.samplerpt import SamplerPt
from raytraverse.renderer import ImageRenderer




class ImageSampler(SamplerPt):
    """sample image (for testing algorithms).

    Parameters
    ----------
    scene: raytraverse.scene.ImageScene
        scene class containing image file information
    scalefac: float, optional
        by default set to the average of non-zero pixels in the image used to
        establish sampling thresholds similar to contribution based samplers
    """

    def __init__(self, scene, vm=None, scalefac=None, method='linear',
                 color=False, uv=False, **kwargs):
        engine = ImageRenderer(scene.scene, vm, method, color=color, uv=uv)
        super().__init__(scene, engine, features=engine.features,
                         stype="image", **kwargs)
        if scalefac is None:
            img = io.hdr2array(scene.scene)
            scalefac = np.average(img[img > 0])
        self.accuracy *= scalefac
        self.vecs = None
        self.lum = []

    def _run_callback(self, point, posidx, vm, write=False, **kwargs):
        return LightPointKD(self.scene, self.vecs, self.lum, vm=vm, pt=point,
                            posidx=posidx, src=self.stype, write=write,
                            features=self.features, **kwargs)





class DeterministicImageSampler(ImageSampler):

    ub = 1



    def run(self, point, posidx, mapper=None, lpargs=None, **kwargs):
        if mapper is None:
            mapper = ViewMapper(jitterrate=0)
        mapper.jitterrate = 0
        return super().run(point, posidx, mapper=mapper, lpargs=lpargs,
                           **kwargs)