openflexure-microscope-server/src/openflexure_microscope_server/things/autofocus.py
2025-06-23 12:02:00 +01:00

577 lines
22 KiB
Python

"""OpenFlexure Microscope autofocus module
This module defines a Thing that is responsible for using the stage and
camera together to perform an autofocus routine.
See repository root for licensing information.
"""
from __future__ import annotations
from contextlib import contextmanager
import logging
import time
from typing import Annotated, Mapping, Optional, Sequence
import os
from fastapi import Depends
import numpy as np
from pydantic import BaseModel
from labthings_fastapi.thing import Thing
from labthings_fastapi.dependencies.blocking_portal import BlockingPortal
from labthings_fastapi.decorators import thing_action, thing_property
from labthings_fastapi.dependencies.metadata import GetThingStates
from labthings_fastapi.types.numpy import NDArray
from labthings_fastapi.dependencies.invocation import InvocationLogger
from .camera import RawCameraDependency as Camera
from .camera import CameraDependency as WrappedCamera
from .stage import StageDependency as Stage
from .capture import RawCaptureDependency as CaptureDep
SETTLING_TIME = 0.3
BACKLASH_CORRECTION = 250
class JPEGSharpnessMonitor:
__globals__ = globals() # Required for FastAPI dependency
def __init__(self, stage: Stage, camera: Camera, portal: BlockingPortal):
self.camera = camera
self.stage = stage
self.portal = portal
print(f"Created sharpness monitor with {stage}, {camera}, {portal}")
self.stage_positions: list[Mapping[str, int]] = []
self.stage_times: list[float] = []
self.jpeg_times: list[float] = []
self.jpeg_sizes: list[int] = []
running = False
async def monitor_sharpness(self):
"""Start monitoring the frame sizes"""
self.running = True
async for frame in self.camera.lores_mjpeg_stream.frame_async_generator():
self.jpeg_times.append(time.time())
self.jpeg_sizes.append(len(frame))
if not self.running:
break
@contextmanager
def run(self):
"""Context manager, during which we will monitor sharpness from the camera"""
self.portal.start_task_soon(self.monitor_sharpness)
try:
yield
finally:
self.running = False
def focus_rel(self, dz: int, **kwargs) -> tuple[int, int]:
# Store the start time and position
self.stage_times.append(time.time())
self.stage_positions.append(self.stage.position)
# Main move
self.stage.move_relative(z=dz, **kwargs)
# Store the end time and position
self.stage_times.append(time.time())
self.stage_positions.append(self.stage.position)
# Index of the data for this movement
data_index: int = len(self.stage_positions) - 2
# Final z position after move
final_z_position: int = self.stage_positions[-1]["z"]
return data_index, final_z_position
def move_data(
self, istart: int, istop: Optional[int] = None
) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""Extract sharpness as a function of (interpolated) z"""
if istop is None:
istop = istart + 2
jpeg_times: np.ndarray = np.array(self.jpeg_times)
jpeg_sizes: np.ndarray = np.array(self.jpeg_sizes)
stage_times: np.ndarray = np.array(self.stage_times)[istart:istop]
stage_zs: np.ndarray = np.array(
[p["z"] for p in self.stage_positions[istart:istop]]
)
try:
start: int = int(np.argmax(jpeg_times > stage_times[0]))
stop: int = int(np.argmax(jpeg_times > stage_times[1]))
except ValueError as e:
if np.sum(jpeg_times > stage_times[0]) == 0:
errmsg = (
"No images were captured during the move of the stage. "
"Perhaps the camera is not streaming images?"
)
raise ValueError(errmsg) from e
raise e
if stop < 1:
stop = len(jpeg_times)
logging.debug("changing stop to %s", (stop))
jpeg_times = jpeg_times[start:stop]
jpeg_zs: np.ndarray = np.interp(
jpeg_times, stage_times, stage_zs
) # np.ndarray[float]
return jpeg_times, jpeg_zs, jpeg_sizes[start:stop]
def sharpest_z_on_move(self, index: int) -> int:
"""Return the z position of the sharpest image on a given move"""
_, jz, js = self.move_data(index)
if len(js) == 0:
raise ValueError(
"No images were captured during the move of the stage. Perhaps the camera is not streaming images?"
)
return jz[np.argmax(js)]
def data_dict(self) -> SharpnessDataArrays:
"""Return the gathered data as a single convenient dictionary"""
data = {}
for k in ["jpeg_times", "jpeg_sizes", "stage_times", "stage_positions"]:
data[k] = getattr(self, k)
return SharpnessDataArrays(**data)
SharpnessMonitorDep = Annotated[JPEGSharpnessMonitor, Depends()]
class SharpnessDataArrays(BaseModel):
jpeg_times: NDArray
jpeg_sizes: NDArray
stage_times: NDArray
stage_positions: list[dict[str, int]]
class AutofocusThing(Thing):
"""The Thing concerned with combinations of z axis movements and the camera.
Actions here involve moving a stage in z, and using the camera to either
capture images (generally, z-stacking) and measuring the sharpness of the
field of view to assess focus (autofocus and testing the success of a z-stack)"""
@thing_action
def fast_autofocus(
self,
sharpness_monitor: SharpnessMonitorDep,
dz: int = 2000,
start: str = "centre",
) -> SharpnessDataArrays:
"""Sweep the stage up and down, then move to the sharpest point
This method will will move down by dz/2, sweep up by dz, and then evaluate
the position where the image was sharpest. We'll then move back down, and
finally up to the sharpest point.
"""
with sharpness_monitor.run():
# Move to (-dz / 2)
if start == "centre":
sharpness_monitor.focus_rel(-dz / 2)
# Move to dz while monitoring sharpness
# i: Sharpness monitor index for this move
# z: Final z position after move
i, z = sharpness_monitor.focus_rel(dz, block_cancellation=True)
# Get the z position with highest sharpness from the previous move (index i)
fz: int = sharpness_monitor.sharpest_z_on_move(i)
# Move all the way to the start so it's consistent
i, z = sharpness_monitor.focus_rel(-dz)
# Move to the target position fz (relative move of (fz - z))
sharpness_monitor.focus_rel(fz - z)
# Return all focus data
return sharpness_monitor.data_dict()
@thing_action
def z_move_and_measure_sharpness(
self,
sharpness_monitor: SharpnessMonitorDep,
dz: Sequence[int],
wait: float = 0,
) -> SharpnessDataArrays:
"""Make a move (or a series of moves) and monitor sharpness
This method will will make a series of relative moves in z, and
return the sharpness (JPEG size) vs time, along with timestamps
for the moves. This can be used to calibrate autofocus.
Each move is relative to the last one, i.e. we will finish at
`sum(dz)` relative to the starting position.
If `wait` is specified, we will wait for that many seconds
between moves.
"""
with sharpness_monitor.run():
for i, current_dz in enumerate(dz):
if i > 0 and wait > 0:
time.sleep(wait)
sharpness_monitor.focus_rel(current_dz)
return sharpness_monitor.data_dict()
@thing_action
def looping_autofocus(
self,
stage: Stage,
sharpness_monitor: SharpnessMonitorDep,
dz=2000,
start="centre",
):
"""Repeatedly autofocus the stage until it looks focused.
This action will run the `fast_autofocus` action until it settles on a point
in the middle 3/5 of its range. Such logic can be helpful if the microscope
is close to focus, but not quite within `dz/2`. It will attempt to autofocus
up to 10 times.
"""
repeat = True
attempts = 0
backlash = 200
with sharpness_monitor.run():
while repeat and attempts < 10:
if start == "centre":
stage.move_relative(x=0, y=0, z=-(backlash + dz / 2))
stage.move_relative(x=0, y=0, z=backlash)
i, z = sharpness_monitor.focus_rel(dz, block_cancellation=True)
_, heights, sizes = sharpness_monitor.move_data(i)
peak_height = heights[np.argmax(sizes)]
height_min = np.min(heights)
height_max = np.max(heights)
if (
peak_height - height_min < dz / 5
or height_max - peak_height < dz / 5
):
attempts += 1
start = "centre"
stage.move_absolute(z=peak_height - backlash)
stage.move_absolute(z=peak_height)
else:
repeat = False
stage.move_relative(x=0, y=0, z=-(dz + backlash))
stage.move_absolute(z=peak_height)
return heights.tolist(), sizes.tolist()
@thing_property
def stack_images_to_capture(self) -> int:
"""The number of images to capture and save in a stack
Defaults to 1 unless you need to see either side of focus"""
return self.thing_settings.get("stack_images_to_capture", 1)
@stack_images_to_capture.setter
def stack_images_to_capture(self, value: int) -> None:
self.thing_settings["stack_images_to_capture"] = value
@thing_property
def stack_images_to_test(self) -> int:
"""The number of images to test for successful focusing in a stack
Defaults to 9, which balances reliability and speed"""
return self.thing_settings.get("stack_images_to_test", 9)
@stack_images_to_test.setter
def stack_images_to_test(self, value: int) -> None:
self.thing_settings["stack_images_to_test"] = value
@thing_property
def stack_dz(self) -> int:
"""Space in steps between images in a z-stack
Suggested is 50 for 60-100x
100 for 40x
200 for 20x"""
return self.thing_settings.get("stack_dz", 50)
@stack_dz.setter
def stack_dz(self, value: int) -> None:
self.thing_settings["stack_dz"] = value
@thing_action
def run_smart_stack(
self,
cam: WrappedCamera,
stage: Stage,
logger: InvocationLogger,
metadata_getter: GetThingStates,
capture: CaptureDep,
sharpness_monitor: SharpnessMonitorDep,
images_dir: str,
autofocus_dz: int,
) -> None:
"""Run a smart stack, which captures images offset in z, testing
whether the sharpest image is towards the centre of the stack.
The sharpest image, and optionally images around the sharpest,
will be saved using their coordinates to images_dir
Arguments:
images_dir: the folder to save all images
autofocus_dz: should the stack fail, the range to refocus over before retrying
variables cam to sharpness_monitor are Thing dependencies injected automatically by LabThings FastAPI
"""
# Set the variables to prevent changes from the GUI or other windows
stack_dz = self.stack_dz
images_to_capture = self.stack_images_to_capture
images_to_test = self.stack_images_to_test
stack_z_range = stack_dz * (images_to_test - 1)
# Starting too low by "overshoot" makes smart stacking faster.
# Starting a stack too high requires it to move to the start,
# autofocus and then re-stack. Starting slightly too low only
# requires extra +z movements and captures.
overshoot = stack_dz * 5
# Ensure the stack settings are appropriate
self.validate_stack_inputs(images_to_test, images_to_capture)
success = False
# Loop until a stack is successful
while not success:
result, heights, captures, sharpest_index = self.z_stack(
stack_dz,
images_to_test,
images_dir,
stack_z_range,
overshoot,
stage,
cam,
capture,
metadata_getter,
)
if result == "success":
success = True
break
# If a stack is not successful, move to the start and autofocus
self.reset_stack(
heights,
autofocus_dz,
stage,
sharpness_monitor,
)
# Save the sharpest image, and images either side of focus
self.save_stack(
sharpest_index,
captures,
images_to_test,
images_to_capture,
logger,
capture,
)
# Return the z position of the sharpest image, for path planning and tracking
return heights[-images_to_test:][sharpest_index]
def reset_stack(
self,
heights: list[int],
autofocus_dz: int,
stage: Stage,
sharpness_monitor: SharpnessMonitorDep,
) -> None:
"""Return to the initial height of the current stack, and run
a looping autofocus. Clears all previous captures, heights and sharpnesses.
Arguments:
heights: a list of the z positions of previous captures
autofocus_dz: the range in steps to autofocus
variables stage and sharpness_monitor are Thing dependencies passed through from the calling action
"""
stage.move_absolute(z=heights[0])
self.looping_autofocus(
stage=stage,
sharpness_monitor=sharpness_monitor,
dz=autofocus_dz,
)
def save_stack(
self,
sharpest_index: int,
captures: list[list],
images_to_test: int,
images_to_capture: int,
logger: InvocationLogger,
capture: CaptureDep,
) -> int:
"""Save the required captures to disk. Will save the sharpest image,
and any images either side of focus.
Arguments:
sharpest_index: the index of the sharpest image, within the "images_to_test" slice
captures: a list of captures, including file name, image data and metadata
images_to_test: the number of images in the stack tested for success
images_to_capture: the number of images to save to disk
variables logger and capture are Thing dependencies passed through from the calling action
"""
# Find the range of images from the stack to capture
stack_extent = int((images_to_capture - 1) / 2)
stack_range = range(
sharpest_index - stack_extent, sharpest_index + stack_extent + 1
)
# Loop through the range, saving each capture to disk
for capture_index in stack_range:
capture._save_capture(
jpeg_path=captures[-images_to_test:][capture_index][0],
image=captures[-images_to_test:][capture_index][1],
metadata=captures[-images_to_test:][capture_index][2],
logger=logger,
)
return sharpest_index
def z_stack(
self,
stack_dz: int,
images_to_test: int,
images_dir: str,
stack_z_range: int,
overshoot: int,
stage: Stage,
cam: WrappedCamera,
capture: CaptureDep,
metadata_getter: GetThingStates,
) -> list:
"""Capture a series of images offset by stack_dz, and test whether
the sharpest image is towards the centre of the stack.
Returns a test result string, a list of z positions, a list of captures and the
index of the sharpest image in a successful stack.
Arguments:
stack_dz: the distance in steps between images in the stack
images_to_test: the number of images in the stack to test for focus
images_dir: a string of the path to write all images
stack_z_range: the height in steps of the stack to test
overshoot: how far below the estimated optimal starting position to begin stacking
variables stage to metadata_getter are Thing dependencies passed through from the calling action
"""
# Move down by the height of the z stack, plus an overshoot
# Better to start too low and take too many images than too high and need to refocus
stage.move_relative(z=-(overshoot + BACKLASH_CORRECTION + stack_z_range / 2))
stage.move_relative(z=BACKLASH_CORRECTION)
captures = []
sharpnesses = []
heights = []
# If the sharpest image isn't found within the 15 images above the estimated point, break
# the loop and return "restart"
while len(captures) <= images_to_test + 15:
time.sleep(SETTLING_TIME)
# Append a new image to the stack
captures, heights, sharpnesses = self.capture_stack_image(
captures,
heights,
sharpnesses,
images_dir,
cam,
stage,
capture,
metadata_getter,
)
# If the number of images is enough to test, test them
if len(captures) >= images_to_test:
stack_result = self.check_stack_result(sharpnesses[-images_to_test:])
if stack_result == "success":
sharpest_index = np.argmax(sharpnesses[-images_to_test:])
return "success", heights, captures, sharpest_index
if stack_result == "restart":
return "restart", heights, None, None
stage.move_relative(z=stack_dz)
return "restart", heights, None, None
def capture_stack_image(
self,
captures: list[list],
heights: list[int],
sharpnesses: list[int],
images_dir: str,
cam: WrappedCamera,
stage: Stage,
capture: CaptureDep,
metadata_getter: GetThingStates,
) -> list:
"""Append a new capture to the ongoing stack.
Includes appending the height, image sharpness and image
data to the relevant lists.
arguments:
captures: a list of captures, including file name, image data and metadata
heights: a list of the z positions of previous captures
sharpnesses: a list of the sharpnesses of previous captures
images_dir: a path to the folder to save images
variables stage to metadata_getter are Thing dependencies passed through from the calling action
"""
stage_location = stage.position
jpeg_path = os.path.join(
images_dir,
f"{stage_location['x']}_{stage_location['y']}_{stage_location['z']}.jpeg",
)
image, metadata = capture._capture_image(
cam=cam,
metadata_getter=metadata_getter,
)
captures.append([jpeg_path, image, metadata])
sharpnesses.append(cam.grab_jpeg_size(stream_name="lores"))
heights.append(stage_location["z"])
return captures, heights, sharpnesses
def validate_stack_inputs(
self, images_to_test: int, images_to_capture: int
) -> None:
"""Check the stack settings are appropriate, and raise an error if not
Arguments:
images_to_test: number of images in the stack to test for focus
images_to_capture: number of images to be captured around the focused image
"""
if images_to_test < images_to_capture:
raise RuntimeError(
"Can't capture more images than are tested. Please increase number to test, or decrease number to capture"
)
if images_to_test % 2 == 0:
raise RuntimeError("Images to test should be odd")
if images_to_test <= 0 or images_to_capture <= 0:
raise RuntimeError("Stack parameters need to be at least 1")
def check_stack_result(self, sharpnesses: list[int]) -> str:
"""Test a list of sharpnesses, to decide whether the sharpest image from a stack is within them
Returns a string
'success' if the sharpest image is towards the centre
'continue' if the sharpest image is in the final two images of the list
'restart' if the sharpest image is in the first two images of the list
Arguments:
sharpnesses: a list of the sharpnesses to test for focus
"""
sharpest_index = np.argmax(sharpnesses)
sharpness_length = len(sharpnesses)
# If only testing one image, then by definition the sharpest is central
if sharpness_length == 1:
return "success"
# If testing three images, test if the centre is the sharpest
if sharpness_length == 3:
if sharpest_index == 1:
return "success"
if sharpest_index == 0:
return "restart"
return "continue"
# For larger stacks, test if the best image is not within two of the edge of the stack
# ie for a stack of 7 images, best image must be between 3rd and and 5th
exclusion_range = 2
if sharpest_index < exclusion_range:
return "restart"
if sharpest_index >= sharpness_length - exclusion_range:
return "continue"
return "success"