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add View3dImageProcessor, add interactive methods to View3d
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opencsp/common/lib/cv/spot_analysis/image_processor/View3dImageProcessor.py
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,167 @@ | ||
| from typing import Callable | ||
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| import cv2 as cv | ||
| import matplotlib.backend_bases | ||
| import numpy as np | ||
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| from opencsp.common.lib.cv.spot_analysis.SpotAnalysisOperable import SpotAnalysisOperable | ||
| from opencsp.common.lib.cv.spot_analysis.image_processor.AbstractSpotAnalysisImageProcessor import ( | ||
| AbstractSpotAnalysisImagesProcessor, | ||
| ) | ||
| import opencsp.common.lib.render.figure_management as fm | ||
| import opencsp.common.lib.render_control.RenderControlAxis as rca | ||
| import opencsp.common.lib.render_control.RenderControlFigure as rcf | ||
| import opencsp.common.lib.render_control.RenderControlSurface as rcs | ||
| import opencsp.common.lib.tool.file_tools as ft | ||
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| class View3dImageProcessor(AbstractSpotAnalysisImagesProcessor): | ||
| def __init__( | ||
| self, | ||
| label: str | rca.RenderControlAxis = 'Light Intensity', | ||
| interactive: bool | Callable[[SpotAnalysisOperable], bool] = False, | ||
| max_resolution: tuple[int, int] | None = None, | ||
| crop_to_threshold: int | None = None, | ||
| ): | ||
| """ | ||
| Interprets the current image as a 3D surface plot and either displays it, or if interactive it displays the | ||
| surface and waits on the next press of the "enter" key. | ||
| Parameters | ||
| ---------- | ||
| label : str | rca.RenderControlAxis, optional | ||
| The label to use for the window title, by default 'Light Intensity' | ||
| interactive : bool | Callable[[SpotAnalysisOperable], bool], optional | ||
| If True then the spot analysis pipeline is paused until the user presses the "enter" key, by default False | ||
| max_resolution : tuple[int, int] | None, optional | ||
| Limits the resolution along the x and y axes to the given values. No limit if None. By default None. | ||
| crop_to_threshold : int | None, optional | ||
| Crops the image on the x and y axis to the first/last value >= the given threshold. None to not crop the | ||
| image. Useful when trying to inspect hot spots on images with very concentrated values. By default None. | ||
| """ | ||
| super().__init__(self.__class__.__name__) | ||
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| self.interactive = interactive | ||
| self.enter_pressed = False | ||
| self.closed = False | ||
| self.max_resolution = max_resolution | ||
| self.crop_to_threshold = crop_to_threshold | ||
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| self.rcf = rcf.RenderControlFigure(tile=False) | ||
| if isinstance(label, str): | ||
| self.rca = rca.RenderControlAxis(z_label=label) | ||
| else: | ||
| self.rca = label | ||
| self.rcs = rcs.RenderControlSurface(alpha=1.0, color=None, contour='xyz') | ||
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| self._init_figure_record() | ||
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| def _init_figure_record(self): | ||
| self.fig_record = fm.setup_figure_for_3d_data( | ||
| self.rcf, | ||
| self.rca, | ||
| equal=False, | ||
| number_in_name=False, | ||
| name=self.rca.z_label, | ||
| code_tag=f"{__file__}.__init__()", | ||
| ) | ||
| self.view = self.fig_record.view | ||
| self.axes = self.fig_record.figure.gca() | ||
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| self.enter_pressed = False | ||
| self.closed = False | ||
| self.fig_record.figure.canvas.mpl_connect('close_event', self.on_close) | ||
| self.fig_record.figure.canvas.mpl_connect('key_release_event', self.on_key_release) | ||
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| def on_key_release(self, event: matplotlib.backend_bases.KeyEvent): | ||
| if event.key == "enter" or event.key == "return": | ||
| self.enter_pressed = True | ||
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| def on_close(self, event: matplotlib.backend_bases.CloseEvent): | ||
| self.closed = True | ||
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| def _get_range_for_threshold(self, image: np.ndarray, threshold: int, axis: int) -> tuple[int, int]: | ||
| """ | ||
| Get the start (inclusive) and end (exclusive) range for which the given image is >= the given threshold. | ||
| Parameters | ||
| ---------- | ||
| image : np.ndarray | ||
| The 2d numpy array to be searched. | ||
| threshold : int | ||
| The cutoff value that the returned region should have pixels greater than. | ||
| axis : int | ||
| 0 for rows (y), 1 for columns (x) | ||
| Returns | ||
| ------- | ||
| start, end: tuple[int, int] | ||
| The start (inclusive) and end (exclusive) matching range. Returns the full image size if there are no | ||
| matching pixels. | ||
| """ | ||
| # If we want the maximum value for all rows, then we need to accumulate across columns. | ||
| # If we want the maximum value for all columns, then we need to accumulate across rows. | ||
| perpendicular_axis = 0 if axis == 1 else 1 | ||
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| # find matches | ||
| img_matching = np.max(image, perpendicular_axis) >= self.crop_to_threshold | ||
| match_idxs = np.argwhere(img_matching) | ||
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| # find the range | ||
| if match_idxs.size > 0: | ||
| start, end = match_idxs[0][0], match_idxs[-1][0] + 1 | ||
| else: | ||
| start, end = 0, image.shape[axis] | ||
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| return start, end | ||
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| def _execute(self, operable: SpotAnalysisOperable, is_last: bool) -> list[SpotAnalysisOperable]: | ||
| image = operable.primary_image.nparray | ||
| image_path = ( | ||
| operable.primary_image_source_path | ||
| or operable.primary_image.source_path | ||
| or operable.primary_image.cache_path | ||
| ) | ||
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| # check if the view has been closed | ||
| if self.closed: | ||
| # UI design decision: it feels more natural to me (Ben) for the plot to not be shown again when it has | ||
| # been closed instead of being reinitialized and popping back up. | ||
| return [operable] | ||
| # self._init_figure_record() | ||
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| # reduce data based on threshold | ||
| if self.crop_to_threshold is not None: | ||
| x_start, x_end = self._get_range_for_threshold(image, self.crop_to_threshold, 1) | ||
| y_start, y_end = self._get_range_for_threshold(image, self.crop_to_threshold, 0) | ||
| image = image[y_start:y_end, x_start:x_end] | ||
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| # reduce data based on max_resolution | ||
| if self.max_resolution is not None: | ||
| width = np.min([image.shape[1], self.max_resolution[0]]) | ||
| height = np.min([image.shape[0], self.max_resolution[1]]) | ||
| image = cv.resize(image, (height, width), interpolation=cv.INTER_AREA) | ||
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| # Clear the previous data | ||
| self.fig_record.view.clear() | ||
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| # Update the title | ||
| _, image_name, _ = ft.path_components(image_path) | ||
| self.fig_record.title = image_name | ||
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| # Draw the new data | ||
| self.view.draw_xyz_surface(image, self.rcs) | ||
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| # draw | ||
| self.view.show(block=False) | ||
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| # wait for the user to press enter | ||
| wait_for_enter_key = self.interactive if isinstance(self.interactive, bool) else self.interactive(operable) | ||
| if wait_for_enter_key: | ||
| self.enter_pressed = False | ||
| while True: | ||
| if self.enter_pressed or self.closed: | ||
| break | ||
| self.fig_record.figure.waitforbuttonpress(0.1) | ||
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| return [operable] |
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