497 lines
18 KiB
Python
497 lines
18 KiB
Python
import datetime
|
|
import logging
|
|
import time
|
|
import uuid
|
|
from typing import Dict, List, Optional, Tuple
|
|
|
|
import marshmallow
|
|
import numpy as np
|
|
from labthings import (
|
|
current_action,
|
|
fields,
|
|
find_component,
|
|
find_extension,
|
|
update_action_progress,
|
|
)
|
|
from labthings.extensions import BaseExtension
|
|
from labthings.views import ActionView
|
|
from typing_extensions import Literal
|
|
|
|
from openflexure_microscope.api.v2.views.actions.camera import FullCaptureArgs
|
|
from openflexure_microscope.captures.capture_manager import generate_basename
|
|
from openflexure_microscope.devel import abort
|
|
from openflexure_microscope.microscope import Microscope
|
|
|
|
# Type alias for convenience
|
|
XyCoordinate = Tuple[int, int]
|
|
XyzCoordinate = Tuple[int, int, int]
|
|
|
|
|
|
### Grid construction
|
|
|
|
|
|
def construct_grid(
|
|
initial: XyCoordinate,
|
|
step_sizes: XyCoordinate,
|
|
n_steps: XyCoordinate,
|
|
style: Literal["raster", "snake", "spiral"] = "raster",
|
|
) -> List[List[XyCoordinate]]:
|
|
"""
|
|
Given an initial position, step sizes, and number of steps,
|
|
construct a 2-dimensional list of scan x-y positions.
|
|
"""
|
|
arr: List[List[XyCoordinate]] = [] # 2D array of coordinates
|
|
|
|
if style == "spiral":
|
|
# deal with the centre image immediately
|
|
coord = initial
|
|
arr.append([initial])
|
|
# for spiral, n_steps is the number of shells, and so only requires n_steps[0]
|
|
for i in range(2, n_steps[0] + 1):
|
|
arr.append([]) # Append new shell holder
|
|
side_length = (2 * i) - 1
|
|
|
|
# Iteratively generate the next location to append
|
|
|
|
# Start coordinate of the shell
|
|
# We create a copy of coord so that the new value of coord doesn't depend on itself
|
|
# Otherwise we create a generator, not a tuple, which makes type checking angry
|
|
last_coordinate: XyCoordinate = coord
|
|
coord = (
|
|
last_coordinate[0] + [-1, 1][0] * step_sizes[0],
|
|
last_coordinate[1] + [-1, 1][1] * step_sizes[1],
|
|
)
|
|
for direction in ([1, 0], [0, -1], [-1, 0], [0, 1]):
|
|
for _ in range(side_length - 1):
|
|
last_coordinate = coord
|
|
coord = (
|
|
last_coordinate[0] + direction[0] * step_sizes[0],
|
|
last_coordinate[1] + direction[1] * step_sizes[1],
|
|
)
|
|
arr[i - 1].append(coord)
|
|
|
|
# If raster or snake
|
|
else:
|
|
for i in range(n_steps[0]): # x axis
|
|
arr.append([])
|
|
for j in range(n_steps[1]): # y axis
|
|
# Create a coordinate tuple
|
|
coord = (
|
|
initial[0] + [i, j][0] * step_sizes[0],
|
|
initial[1] + [i, j][1] * step_sizes[1],
|
|
)
|
|
# Append coordinate array to position grid
|
|
arr[i].append(coord)
|
|
|
|
# Style modifiers
|
|
if style == "snake":
|
|
# For each line (row) in the coordinate array
|
|
for i, line in enumerate(arr):
|
|
# If it's an odd row
|
|
if i % 2 != 0:
|
|
# Reverse the list of coordinates
|
|
line.reverse()
|
|
|
|
return arr
|
|
|
|
|
|
def closest_point_in_xy(
|
|
current_position: XyCoordinate, points: List[XyzCoordinate]
|
|
) -> Optional[XyzCoordinate]:
|
|
"""Find the closest point in a list
|
|
|
|
Given a 2D position, find the 3D position that's closest in XY and return it.
|
|
In the event of a tie, the most recent (i.e. latest in the list) is returned.
|
|
|
|
If the list is empty, we return None
|
|
"""
|
|
if len(points) < 1:
|
|
return None
|
|
points_2d = np.asarray(points)[:, :2]
|
|
|
|
squared_distances = np.sum((points_2d - current_position) ** 2, axis=1)
|
|
# We reverse the distances before searching, as argmin will return the first
|
|
# point in the event of there being multiple points with the same minimum,
|
|
# and we want to pick the last one.
|
|
reverse_min_index = np.argmin(squared_distances[::-1])
|
|
# of course, now we must convert the index to be the right way round
|
|
min_index = len(points) - 1 - reverse_min_index
|
|
return points[int(min_index)] # The explicit cast is necessary for MyPy
|
|
|
|
|
|
### Capturing
|
|
|
|
|
|
class ScanExtension(BaseExtension):
|
|
def __init__(self):
|
|
BaseExtension.__init__(self, "org.openflexure.scan", version="2.0.0")
|
|
|
|
self._images_to_be_captured: int = 1
|
|
self._images_captured_so_far: int = 0
|
|
|
|
self.add_view(TileScanAPI, "/tile", endpoint="tile")
|
|
|
|
def capture(
|
|
self,
|
|
microscope: Microscope,
|
|
basename: Optional[str],
|
|
namemode: str = "coordinates",
|
|
temporary: bool = False,
|
|
use_video_port: bool = False,
|
|
resize: Optional[Tuple[int, int]] = None,
|
|
bayer: bool = False,
|
|
metadata: Optional[dict] = None,
|
|
annotations: Optional[Dict[str, str]] = None,
|
|
tags: Optional[List[str]] = None,
|
|
dataset: Optional[Dict[str, str]] = None,
|
|
):
|
|
metadata = metadata or {}
|
|
annotations = annotations or {}
|
|
tags = tags or []
|
|
|
|
# Construct a tile filename
|
|
if namemode == "coordinates":
|
|
filename = "{}_{}_{}_{}".format(basename, *microscope.stage.position)
|
|
else:
|
|
filename = "{}_{}".format(
|
|
basename,
|
|
str(self._images_captured_so_far).zfill(
|
|
len(str(self._images_to_be_captured))
|
|
),
|
|
)
|
|
folder = "SCAN_{}".format(basename)
|
|
|
|
# Do capture
|
|
return microscope.capture(
|
|
filename=filename,
|
|
folder=folder,
|
|
temporary=temporary,
|
|
use_video_port=use_video_port,
|
|
resize=resize,
|
|
bayer=bayer,
|
|
annotations=annotations,
|
|
tags=tags,
|
|
dataset=dataset,
|
|
metadata=metadata,
|
|
cache_key=folder,
|
|
)
|
|
|
|
def progress(self):
|
|
progress = (self._images_captured_so_far / self._images_to_be_captured) * 100
|
|
logging.info(progress)
|
|
return progress
|
|
|
|
### Scanning
|
|
def tile(
|
|
self,
|
|
microscope: Microscope,
|
|
basename: Optional[str] = None,
|
|
namemode: str = "coordinates",
|
|
temporary: bool = False,
|
|
stride_size: XyzCoordinate = (2000, 1500, 100),
|
|
grid: XyzCoordinate = (3, 3, 5),
|
|
style="raster",
|
|
autofocus_dz: int = 50,
|
|
use_video_port: bool = False,
|
|
resize: Optional[Tuple[int, int]] = None,
|
|
bayer: bool = False,
|
|
fast_autofocus: bool = False,
|
|
metadata: Optional[dict] = None,
|
|
annotations: Optional[Dict[str, str]] = None,
|
|
tags: Optional[List[str]] = None,
|
|
detect_empty_fields_and_skip_autofocus: bool = False,
|
|
):
|
|
metadata = metadata or {}
|
|
annotations = annotations or {}
|
|
tags = tags or []
|
|
|
|
start = time.time()
|
|
|
|
# Store initial position
|
|
initial_position = microscope.stage.position
|
|
# Construct an x-y grid (worry about z later)
|
|
x_y_grid = construct_grid(
|
|
initial_position[:2], stride_size[:2], grid[:2], style=style
|
|
) # This is a list of lists.
|
|
|
|
# Keep task progress
|
|
# NB the number of points is found from the number of elements in
|
|
# x_y_grid; this is not guaranteed to be the same in every row.
|
|
self._images_to_be_captured = sum([len(line) for line in x_y_grid])
|
|
self._images_captured_so_far = 0
|
|
|
|
# Generate a basename if none given
|
|
if not basename:
|
|
basename = generate_basename()
|
|
|
|
# Add dataset metadata
|
|
dataset_d = {
|
|
"id": uuid.uuid4(),
|
|
"type": "xyzScan",
|
|
"name": basename,
|
|
"acquisitionDate": datetime.datetime.now().isoformat(),
|
|
"strideSize": stride_size,
|
|
"grid": grid,
|
|
"style": style,
|
|
"autofocusDz": autofocus_dz,
|
|
}
|
|
|
|
# Check if autofocus is enabled
|
|
autofocus_extension = find_extension("org.openflexure.autofocus")
|
|
if (
|
|
autofocus_dz
|
|
and autofocus_extension
|
|
and microscope.has_real_stage()
|
|
and microscope.has_real_camera()
|
|
):
|
|
autofocus_enabled = True
|
|
else:
|
|
autofocus_enabled = False
|
|
|
|
if detect_empty_fields_and_skip_autofocus:
|
|
# Check for the background detect extension if we need it, raise an error now if it's missing.
|
|
background_detect_extension = find_extension(
|
|
"org.openflexure.background-detect"
|
|
)
|
|
if not background_detect_extension:
|
|
raise RuntimeError(
|
|
"Detecting background fields requires the background detect extension and it was not found."
|
|
)
|
|
|
|
focused_positions: List[
|
|
XyzCoordinate
|
|
] = [] # Positions where we found sharp images
|
|
|
|
# Now step through each point in the x-y coordinate array
|
|
for line in x_y_grid:
|
|
for x_y in line:
|
|
# Set the next z position based on the closest point that was in focus.
|
|
# For a snake/spiral scan, this should always be the last point, unless
|
|
# it's skipped for some reason. In a raster scan, this should be the last
|
|
# point, except when we're at the start of a row when it will be the first
|
|
# point of the preceding row.
|
|
closest_focused_point = closest_point_in_xy(x_y, focused_positions)
|
|
next_z = (
|
|
closest_focused_point[2]
|
|
if closest_focused_point
|
|
else initial_position[2]
|
|
)
|
|
# Move to new grid position
|
|
logging.debug("Moving to step %s", ([x_y[0], x_y[1], next_z]))
|
|
microscope.stage.move_abs((x_y[0], x_y[1], next_z))
|
|
|
|
# Check if the current field looks empty, and skip autofocus if it does
|
|
skip_autofocus = False
|
|
if detect_empty_fields_and_skip_autofocus:
|
|
verdict = background_detect_extension.grab_and_classify_image()
|
|
logging.debug(f"Background detection verdict: {verdict}")
|
|
if verdict["classification"] == "background":
|
|
skip_autofocus = True
|
|
logging.info(
|
|
f"Detected an empty field at {x_y}, skipping autofocus."
|
|
)
|
|
|
|
if autofocus_enabled and not skip_autofocus:
|
|
if fast_autofocus:
|
|
# Run fast autofocus. Client should provide dz ~ 2000
|
|
autofocus_extension.fast_autofocus(microscope, dz=autofocus_dz)
|
|
else:
|
|
# Run slow autofocus. Client should provide dz ~ 50
|
|
autofocus_extension.autofocus(
|
|
microscope,
|
|
range(-3 * autofocus_dz, 4 * autofocus_dz, autofocus_dz),
|
|
)
|
|
logging.debug("Finished autofocus")
|
|
time.sleep(1)
|
|
autofocus_accepted = True
|
|
here = microscope.stage.position
|
|
# Check if we've moved worryingly far in Z
|
|
if closest_focused_point:
|
|
lateral_move = np.sqrt(
|
|
np.sum(
|
|
(
|
|
np.array(here)[:2]
|
|
- np.array(closest_focused_point)[:2]
|
|
)
|
|
** 2
|
|
)
|
|
)
|
|
axial_move = np.abs(here[2] - closest_focused_point[2])
|
|
if axial_move > lateral_move * 0.4:
|
|
autofocus_accepted = False
|
|
logging.warning(
|
|
f"During a scan, there was a large axial jump from {closest_focused_point}"
|
|
f" to {here}. This may mean autofocus has failed."
|
|
)
|
|
# Append the (current, i.e. focused) position to the list
|
|
if autofocus_accepted:
|
|
focused_positions.append(here)
|
|
|
|
# If we're not doing a z-stack, just capture
|
|
if grid[2] <= 1:
|
|
self.capture(
|
|
microscope,
|
|
basename,
|
|
namemode=namemode,
|
|
temporary=temporary,
|
|
use_video_port=use_video_port,
|
|
resize=resize,
|
|
bayer=bayer,
|
|
dataset=dataset_d,
|
|
annotations=annotations,
|
|
tags=tags,
|
|
)
|
|
# Update task progress
|
|
self._images_captured_so_far += 1
|
|
update_action_progress(self.progress())
|
|
else:
|
|
logging.debug("Entering z-stack")
|
|
self.stack(
|
|
microscope=microscope,
|
|
basename=basename,
|
|
namemode=namemode,
|
|
temporary=temporary,
|
|
step_size=stride_size[2],
|
|
steps=grid[2],
|
|
use_video_port=use_video_port,
|
|
resize=resize,
|
|
bayer=bayer,
|
|
dataset=dataset_d,
|
|
annotations=annotations,
|
|
tags=tags,
|
|
)
|
|
if current_action() and current_action().stopped:
|
|
return
|
|
# Make sure we use our current best estimate of focus (i.e. the current position) next point
|
|
next_z = microscope.stage.position[2]
|
|
|
|
logging.debug("Returning to %s", (initial_position))
|
|
microscope.stage.move_abs(initial_position)
|
|
|
|
end = time.time()
|
|
logging.info("Scan took %s seconds", end - start)
|
|
|
|
def stack(
|
|
self,
|
|
microscope: Microscope,
|
|
basename: Optional[str] = None,
|
|
namemode: str = "coordinates",
|
|
temporary: bool = False,
|
|
step_size: int = 100,
|
|
steps: int = 5,
|
|
return_to_start: bool = True,
|
|
use_video_port: bool = False,
|
|
resize: Optional[Tuple[int, int]] = None,
|
|
bayer: bool = False,
|
|
metadata: Optional[dict] = None,
|
|
annotations: Optional[Dict[str, str]] = None,
|
|
dataset: Optional[Dict[str, str]] = None,
|
|
tags: Optional[List[str]] = None,
|
|
):
|
|
metadata = metadata or {}
|
|
annotations = annotations or {}
|
|
tags = tags or []
|
|
|
|
# Store initial position
|
|
initial_position = microscope.stage.position
|
|
logging.debug("Starting z-stack from position %s", microscope.stage.position)
|
|
|
|
with microscope.lock:
|
|
# Move to center scan
|
|
logging.debug("Moving to z-stack starting position")
|
|
microscope.stage.move_rel((0, 0, int((-step_size * steps) / 2)))
|
|
logging.debug("Starting scan from position %s", microscope.stage.position)
|
|
|
|
for i in range(steps):
|
|
time.sleep(0.1)
|
|
logging.debug("Capturing from position %s", microscope.stage.position)
|
|
self.capture(
|
|
microscope,
|
|
basename,
|
|
namemode=namemode,
|
|
temporary=temporary,
|
|
use_video_port=use_video_port,
|
|
resize=resize,
|
|
bayer=bayer,
|
|
metadata=metadata,
|
|
annotations=annotations,
|
|
dataset=dataset,
|
|
tags=tags,
|
|
)
|
|
# Update task progress
|
|
self._images_captured_so_far += 1
|
|
update_action_progress(self.progress())
|
|
if current_action() and current_action().stopped:
|
|
return
|
|
|
|
if i != steps - 1:
|
|
logging.debug("Moving z by %s", (step_size))
|
|
microscope.stage.move_rel((0, 0, step_size))
|
|
if return_to_start:
|
|
logging.debug("Returning to %s", (initial_position))
|
|
microscope.stage.move_abs(initial_position)
|
|
|
|
|
|
class TileScanArgs(FullCaptureArgs):
|
|
namemode = fields.String(missing="coordinates", example="coordinates")
|
|
grid = fields.List(
|
|
fields.Integer(validate=marshmallow.validate.Range(min=1)),
|
|
missing=[3, 3, 3],
|
|
example=[3, 3, 3],
|
|
)
|
|
style = fields.String(missing="raster")
|
|
autofocus_dz = fields.Integer(missing=50)
|
|
fast_autofocus = fields.Boolean(missing=False)
|
|
stride_size = fields.List(
|
|
fields.Integer, missing=[2000, 1500, 100], example=[2000, 1500, 100]
|
|
)
|
|
detect_empty_fields_and_skip_autofocus = fields.Boolean(missing=False)
|
|
|
|
|
|
class TileScanAPI(ActionView):
|
|
args = TileScanArgs()
|
|
|
|
# Allow 10 seconds to stop upon DELETE request
|
|
# Gives fast-autofocus time to finish if it's running
|
|
default_stop_timeout = 10
|
|
|
|
def post(self, args):
|
|
microscope = find_component("org.openflexure.microscope")
|
|
|
|
if not microscope:
|
|
abort(503, "No microscope connected. Unable to autofocus.")
|
|
|
|
resize = args.get("resize", None)
|
|
if resize:
|
|
if ("width" in resize) and ("height" in resize):
|
|
resize = (
|
|
int(resize["width"]),
|
|
int(resize["height"]),
|
|
) # Convert dict to tuple
|
|
else:
|
|
abort(404)
|
|
|
|
logging.info("Running tile scan...")
|
|
|
|
# Acquire microscope lock with 1s timeout
|
|
with microscope.lock(timeout=1):
|
|
# Run scan_extension_v2
|
|
return self.extension.tile(
|
|
microscope,
|
|
basename=args.get("filename"),
|
|
namemode=args.get("namemode"),
|
|
temporary=args.get("temporary"),
|
|
stride_size=args.get("stride_size"),
|
|
grid=args.get("grid"),
|
|
style=args.get("style"),
|
|
autofocus_dz=args.get("autofocus_dz"),
|
|
use_video_port=args.get("use_video_port"),
|
|
resize=resize,
|
|
bayer=args.get("bayer"),
|
|
fast_autofocus=args.get("fast_autofocus"),
|
|
annotations=args.get("annotations"),
|
|
tags=args.get("tags"),
|
|
detect_empty_fields_and_skip_autofocus=args.get(
|
|
"detect_empty_fields_and_skip_autofocus"
|
|
),
|
|
)
|