A partial refactor of background detect
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6 changed files with 162 additions and 4 deletions
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@ -19,6 +19,7 @@ import piexif
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import labthings_fastapi as lt
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from labthings_fastapi.types.numpy import NDArray
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from openflexure_microscope_server.background_detect import ChannelDistributions, BackgroundDetectLUV
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class JPEGBlob(lt.blob.Blob):
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"""A class representing a JPEG image as a LabThings FastAPI Blob."""
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@ -155,6 +156,10 @@ class BaseCamera(lt.Thing):
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lores_mjpeg_stream = lt.outputs.MJPEGStreamDescriptor()
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_memory_buffer = CameraMemoryBuffer()
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def __init__(self):
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super().__init__()
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self.background_detector = BackgroundDetectLUV()
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def __enter__(self) -> None:
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"""Open hardware connection when the Thing context manager is opened."""
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raise NotImplementedError("CameraThings must define their own __enter__ method")
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@ -455,6 +460,67 @@ class BaseCamera(lt.Thing):
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time.sleep(self.settling_time)
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self.discard_frames()
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background_tolerance = lt.ThingSetting(
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initial_value=7.0,
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model=float,
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)
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"""How many standard deviations to allow for the background."""
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min_sample_coverage = lt.ThingSetting(
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initial_value=25.0,
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model=float,
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)
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"""The percentage of the image that needs to be not be background to label as sample."""
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# Requires a getter and a setter to support being a BaseModel but being
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# saved to file as a dict
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_background_distributions: Optional[ChannelDistributions] = None
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@lt.thing_setting
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def background_distributions(self) -> Optional[ChannelDistributions]:
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"""The statistics of the background image."""
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bd = self._background_distributions
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if bd is None:
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return None
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return ChannelDistributions(**bd)
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@background_distributions.setter
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def background_distributions(
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self, value: Optional[ChannelDistributions | dict]
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) -> None:
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if value is None:
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self._background_distributions = None
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elif isinstance(value, ChannelDistributions):
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self._background_distributions = value.model_dump()
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elif isinstance(value, dict):
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self._background_distributions = value
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else:
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raise TypeError(
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f"Cannot set background_distributions with an object of type {type(value)}"
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)
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@lt.thing_action
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def image_is_sample(self, portal: lt.deps.BlockingPortal) -> bool:
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"""Label the current image as either background or sample."""
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current_image = self.grab_jpeg(portal)
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current_image = np.array(Image.open(current_image.open()))
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return self.background_detector.image_is_sample(current_image)
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@lt.thing_action
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def set_background(self, portal: lt.deps.BlockingPortal):
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"""Grab an image, and use its statistics to set the background.
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This should be run when the microscope is looking at an empty region,
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and will calculate the mean and standard deviation of the pixel values
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in the LUV colourspace. These values will then be used to compare
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future images to the distribution, to determine if each pixel is
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foreground or background.
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"""
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background = self.grab_jpeg(portal)
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background = np.array(Image.open(background.open()))
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self.background_detector.set_background(current_image)
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CameraDependency = lt.deps.direct_thing_client_dependency(BaseCamera, "/camera/")
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RawCameraDependency = lt.deps.raw_thing_dependency(BaseCamera)
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@ -30,6 +30,7 @@ class OpenCVCamera(BaseCamera):
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:param camera_index: The index of the camera to use for the microscope.
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"""
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super().__init()
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self.camera_index = camera_index
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self._capture_thread: Optional[Thread] = None
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self._capture_enabled = False
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@ -118,6 +118,7 @@ class StreamingPiCamera2(BaseCamera):
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:param camera_num: The number of the camera. This should generally be left as 0
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as most Raspberry Pi boards only support 1 camera.
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"""
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super().__init()
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self._setting_save_in_progress = False
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self.camera_num = camera_num
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self.camera_configs: dict[str, dict] = {}
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@ -58,6 +58,7 @@ class SimulatedCamera(BaseCamera):
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:param frame_interval: Nominally the time between frames on the MJPEG stream,
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however the rate may be slower due to calculation time for focus.
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"""
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super().__init()
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self.shape = shape
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self.glyph_shape = glyph_shape
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self.canvas_shape = canvas_shape
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