Parallelise capture of images and the next move
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Richard Bowman
parent
6e4e79f2d2
commit
4a18ef729a
1 changed files with 59 additions and 31 deletions
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@ -14,6 +14,7 @@ from scipy.stats import norm
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from copy import deepcopy
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from datetime import datetime
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from subprocess import CompletedProcess, Popen, PIPE, SubprocessError, run
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from threading import Event, Thread
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import glob
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import zipfile
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import json
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@ -514,11 +515,21 @@ class SmartScanThing(Thing):
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with open(os.path.join(images_folder, 'scan_inputs.json'), 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=4)
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# Make the initial move (which probably does nothing)
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# NB we will move to the next scan point at the **end** of the loop, so that it can
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# happen concurrently with saving the images.
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loc = self.move_to_next_point(stage, logger, path=path, focused_path=focused_path)
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# At the start of the loop, we simultaneously capture an image and move to the next scan point.
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# We skip capturing on the first run, because we've not focused yet - and also we skip capturing if
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# it looks like background.
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capture_thread = None
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while len(path) > 0:
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loc = self.move_to_next_point(stage, logger, path=path, focused_path=focused_path)
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if capture_thread: # wait for the previous capture to be saved
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capture_thread.join()
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if not self.preview_stitch_running():
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self.preview_stitch_start(images_folder)
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if self.stitch_automatically:
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if not self.correlate_running():
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self.correlate_start(images_folder, overlap=overlap)
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ensure_free_disk_space(scan_folder)
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# Check if the image is background
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@ -530,7 +541,9 @@ class SmartScanThing(Thing):
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# if more than 92% of the image is background, treat it as background and continue
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if not image_is_sample:
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logger.info(f"Skipping {stage.position} as it is {round(background_detect.background_fraction(),0)}% background.")
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capture_image = False
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else:
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capture_image = True
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# if not, it's sample. run an autofocus and use the updated height
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new_pos = [
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[stage.position["x"] - dx, stage.position["y"]],
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@ -581,40 +594,55 @@ class SmartScanThing(Thing):
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)
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stage.move_absolute(z=int(loc[2]))
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attempts += 1
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# Acquire the image in a thread, and continue once it's acquired (i.e. leave saving in the background)
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acquired = Event()
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name = f"image_{loc[0]}_{loc[1]}.jpg"
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# img = Image.open(cam.capture_jpeg(resolution="full").open())
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jpegblob = cam.capture_jpeg(resolution="full")
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jpegblob.save(os.path.join(raw_images_folder, name))
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img = Image.open(jpegblob.open())
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exif = img.info['exif']
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width, height = img.size
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img = img.resize((int(width*0.5), int(height*0.5)))
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img_width, _ = img.size
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logger.info(f"Saving {name}")
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img.save(
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os.path.join(images_folder, name),
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exif=exif,
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quality=95,
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subsampling=0
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def capture_and_save(): #cam: CamDep, logger: InvocationLogger, acquired: Event, name: str, images_folder: str, raw_images_folder: str) -> None:
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"""Capture an image and save it to disk
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This will set the event `acquired` once the image has been acquired, so
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that the stage may be moved while it's saved.
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"""
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capture_start = time.time()
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jpegblob = cam.capture_jpeg(resolution="full")
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acquired.set()
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acquisition_time = time.time() - capture_start
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jpegblob.save(os.path.join(raw_images_folder, name))
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img = Image.open(jpegblob.open())
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exif = img.info['exif']
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width, height = img.size
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img = img.resize((int(width*0.5), int(height*0.5)))
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logger.info(f"Saving {name}")
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img.save(
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os.path.join(images_folder, name),
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exif=exif,
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quality=95,
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subsampling=0
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)
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save_time = time.time() - acquisition_time - capture_start
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logger.info(f"Acquired {name} in {acquisition_time}s then {save_time}s saving to disk")
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capture_thread = Thread(
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target=capture_and_save,
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#kwargs={
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# "cam": cam,
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# "logger": logger,
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# "acquired": acquired,
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# "name": name,
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# "images_folder": images_folder,
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# "raw_images_folder": raw_images_folder,
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#}
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)
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capture_thread.start()
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acquired.wait() # wait until the image is acquired
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positions.append(loc[:2])
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names.append(name)
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if not self.preview_stitch_running():
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self.preview_stitch_start(images_folder)
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if self.stitch_automatically:
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if not self.correlate_running():
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self.correlate_start(images_folder, overlap=overlap)
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# add the current position to the list of all positions visited
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true_path.append(loc)
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if len(names) > 1:
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generate_config(images_folder, positions, names, CSM, csm_calibration_width, img_width, logger)
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#if len(names) > 1:
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# generate_config(images_folder, positions, names, CSM, csm_calibration_width, img_width, logger)
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temp_path = []
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@ -623,9 +651,7 @@ class SmartScanThing(Thing):
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temp_path.append(i)
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else:
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logger.info(f'Rejected moving to {i} as it is out of range')
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path = temp_path.copy()
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path = sorted(path, key=lambda x: (steps_from_centre(x, true_path[0][:2], dx, dy), distance_to_site(loc[:2], x)))
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except InvocationCancelledError:
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@ -645,6 +671,8 @@ class SmartScanThing(Thing):
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)
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raise e
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finally:
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if capture_thread:
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capture_thread.join()
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try:
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logger.info("Returning to starting position.")
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if starting_position is not None:
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