Autofocus module!

Currently only has fast_autofocus, and there
may be some work to do on timing, but it works :)

Getting timestamps from the camera rather than
time.time() would be ideal, but it would take some thought to tie that up with
the encoder.

I'm using a low-res stream, as it seems impossible to
turn the bitrate control of the MJPEG stream off,
at least within the picamera2 API.
This commit is contained in:
Richard Bowman 2023-08-30 21:34:06 +01:00
parent 081654533f
commit 6e04618051
2 changed files with 167 additions and 4 deletions

View file

@ -4,12 +4,13 @@ from labthings_fastapi.thing_server import ThingServer
from labthings_sangaboard import SangaboardThing
from labthings_picamera2.thing import StreamingPiCamera2
from .things.autofocus import AutofocusThing
logging.basicConfig(level=logging.INFO)
thing_server = ThingServer()
camera = StreamingPiCamera2()
thing_server.add_thing(camera, "/camera")
stage = SangaboardThing()
thing_server.add_thing(stage, "/stage")
thing_server.add_thing(StreamingPiCamera2(), "/camera")
thing_server.add_thing(SangaboardThing(), "/stage")
thing_server.add_thing(AutofocusThing(), "/autofocus")
app = thing_server.app

View file

@ -0,0 +1,162 @@
from __future__ import annotations
from contextlib import contextmanager
import logging
import time
from typing import Annotated, Mapping, Optional
from anyio import from_thread
from fastapi import Depends
from labthings_fastapi.thing import Thing
from labthings_fastapi.dependencies.raw_thing import raw_thing_dependency
from labthings_fastapi.dependencies.thing import direct_thing_client_dependency
from labthings_fastapi.dependencies.blocking_portal import BlockingPortal
from labthings_fastapi.decorators import thing_action
from labthings_fastapi.types.numpy import NDArray
from labthings_picamera2.thing import StreamingPiCamera2
from labthings_sangaboard import SangaboardThing
import numpy as np
from pydantic import BaseModel
Stage = direct_thing_client_dependency(SangaboardThing, "/stage/")
Camera = raw_thing_dependency(StreamingPiCamera2)
### Autofocus utilities
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.spawn_task(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:
raise ValueError(
"No images were captured during the move of the stage. Perhaps the camera is not streaming images?"
) from e
else:
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: NDArray
class AutofocusThing(Thing):
@thing_action
def fast_autofocus(
self,
m: SharpnessMonitorDep,
dz: int=2000
) -> 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 m.run():
# Move to (-dz / 2)
m.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 = m.focus_rel(dz)
# Get the z position with highest sharpness from the previous move (index i)
fz: int = m.sharpest_z_on_move(i)
# Move all the way to the start so it's consistent
i, z = m.focus_rel(-dz)
# Move to the target position fz (relative move of (fz - z))
m.focus_rel(fz - z)
# Return all focus data
return m.data_dict()