Get codespell passing and add it as a CI job.
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25 changed files with 113 additions and 85 deletions
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@ -1,7 +1,7 @@
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"""OpenFlexure Microscope Camera.
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This module defines the interface for cameras. Any compatible lt.Thing
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should enabe the server to work.
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should enable the server to work.
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See repository root for licensing information.
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"""
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@ -86,7 +86,7 @@ class OpenCVCamera(BaseCamera):
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It's likely to be highly inefficient - raw and/or uncompressed captures using
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binary image formats will be added in due course.
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"""
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logging.warning(f"OpenCV camera doen't respect {resolution} setting")
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logging.warning(f"OpenCV camera doesn't respect {resolution} setting")
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ret, frame = self.cap.read()
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if not ret:
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raise RuntimeError(
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@ -104,7 +104,7 @@ class OpenCVCamera(BaseCamera):
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This function will produce a JPEG image.
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"""
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logging.warning(f"OpenCV camera doen't respect {resolution} setting")
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logging.warning(f"OpenCV camera doesn't respect {resolution} setting")
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frame = self.capture_array()
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jpeg = cv2.imencode(".jpg", frame)[1].tobytes()
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exif_dict = {
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@ -79,7 +79,7 @@ class SensorMode(BaseModel):
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class SensorModeSelector(BaseModel):
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"""A Pydantic model holding the two values needed to select a PiCamera Sensor mode.
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Theses values are the output size and the bit depth.
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These values are the output size and the bit depth.
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This is a Pydantic model so that it can be saved to disk.
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"""
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@ -95,7 +95,7 @@ class LensShading(BaseModel):
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(12, 16) in size. The arrays are luminance, red-difference chroma (Cr), and
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blue-difference chroma (Cb).
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This is a Pydantic modell so that it can be saved to the disk.
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This is a Pydantic model so that it can be saved to the disk.
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"""
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luminance: list[list[float]]
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@ -162,7 +162,7 @@ class StreamingPiCamera2(BaseCamera):
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This method is run by any Thing when a ThingSetting is saved. However, the
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method reads the thing_setting. As reading the thing setting talks to the
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camera and calls save_settings if the value is not as expected, this could
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cause recursion. Aslo this means that saving one setting causes all others
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cause recursion. Also this means that saving one setting causes all others
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to be read each time.
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"""
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try:
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@ -197,7 +197,7 @@ class StreamingPiCamera2(BaseCamera):
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@lt.thing_setting
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def colour_gains(self) -> tuple[float, float]:
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"""The red and blue colour gains, must be betwen 0.0 and 32.0."""
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"""The red and blue colour gains, must be between 0.0 and 32.0."""
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if not self._setting_save_in_progress and self.streaming:
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with self._streaming_picamera() as cam:
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cam_value = cam.capture_metadata()["ColourGains"]
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@ -759,7 +759,7 @@ class StreamingPiCamera2(BaseCamera):
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same as the default behaviour, which is to use an adaptive lens shading
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table.
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This flat table is used to take an image wth no lens shading so that the
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This flat table is used to take an image with no lens shading so that the
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correct lens shading table can be calibrated.
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"""
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with self._streaming_picamera(pause_stream=True):
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@ -84,7 +84,7 @@ def set_minimum_exposure(camera: Picamera2) -> None:
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Note ISO is left at auto, because this is needed for the gains
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to be set correctly.
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"""
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# Disable Automatic exposure and gain algoritm (AeEnable), and set analogue
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# Disable Automatic exposure and gain algorithm (AeEnable), and set analogue
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# gain and exposure time.
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# Setting the shutter speed to 1us will result in it being set
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# to the minimum possible, which is ~8us for PiCamera v2
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@ -427,7 +427,7 @@ def set_static_lst(
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cr: np.ndarray,
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cb: np.ndarray,
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) -> None:
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"""Update the ``rpi.alsc`` section of a camera tuning dict to use a static correcton.
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"""Update the ``rpi.alsc`` section of a camera tuning dict to use a static correction.
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``tuning`` will be updated in-place to set its shading to static, and disable any
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adaptive tweaking by the algorithm.
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@ -452,7 +452,7 @@ def set_static_ccm(
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float, float, float, float, float, float, float, float, float
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],
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) -> None:
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"""Update the ``rpi.alsc`` section of a camera tuning dict to use a static correcton.
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"""Update the ``rpi.alsc`` section of a camera tuning dict to use a static correction.
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``tuning`` will be updated in-place to set its shading to static, and disable any
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adaptive tweaking by the algorithm.
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@ -480,7 +480,7 @@ def set_static_geq(
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"""Update the ``rpi.geq`` section of a camera tuning dict.
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:param tuning: the raspberry pi tuning file. This will be updated in-place to
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set the geq offest to the given value.
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set the geq offset to the given value.
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:param offset: The desired green equalisation offset. Default 65535. The default is
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the maximum allowed value. This means the brightness will always be below the
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threshold where averaging is used. This is default as we always need the green
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@ -42,7 +42,7 @@ class SimulatedCamera(BaseCamera):
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canvas_shape: tuple[int, int, int] = (3000, 4000, 3),
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frame_interval: float = 0.1,
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):
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"""Initalise the simulated with settings for how images are generated.
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"""Initialise the simulated with settings for how images are generated.
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:param shape: The shape (size) of the generated image.
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:param glyph_shape: The size randomly positioned glyphs.
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@ -128,7 +128,7 @@ class SimulatedCamera(BaseCamera):
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"""Wrap the attach_to_server method so the server instance can be stored.
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Direct access to the server instance is needed to get the stage position while
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maintianing the same public API as a real camera that doesn't need this access.
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maintaining the same public API as a real camera that doesn't need this access.
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"""
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self._server = server
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return super().attach_to_server(server, path, setting_storage_path)
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@ -198,7 +198,7 @@ class SimulatedCamera(BaseCamera):
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It's likely to be highly inefficient - raw and/or uncompressed captures using
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binary image formats will be added in due course.
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"""
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logging.warning(f"Simulation camera doen't respect {resolution} setting")
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logging.warning(f"Simulation camera doesn't respect {resolution} setting")
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return self.generate_frame()
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@lt.thing_action
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@ -211,7 +211,7 @@ class SimulatedCamera(BaseCamera):
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This function will produce a JPEG image.
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"""
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logging.warning(f"Simulation camera doen't respect {resolution} setting")
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logging.warning(f"Simulation camera doesn't respect {resolution} setting")
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frame = self.capture_array()
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jpeg = cv2.imencode(".jpg", frame)[1].tobytes()
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exif_dict = {
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