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Motion detection is now a function and a few other minor tweaks

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Chish36 2025-07-24 14:49:28 +01:00 • committed by Julian Stirling
parent ada120db9c
commit b90ecf8c49
1 changed files with 45 additions and 36 deletions
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81
src/openflexure_microscope_server/things/stage_measure.py
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@ -57,14 +57,20 @@ def steps_generate(small_step: int, z_perc: int, big_step: int, dir: int, stream
return step_sizes_small, minimum_offset_small, z_steps, minimum_offset_z, step_sizes_big, wrong_axis_max_small, wrong_axis_max_z
def predict_z(positions: list, axis: str, relative_move: float, stage: StageDep) -> float:
def predict_z(positions: list, axis: str, relative_move: float, stage: StageDep, csm: CSMDep) -> float:
"""
Predicts the next z position for a big move using an array of previous positions.
"""
pixel_step = {
'x':1/csm.image_to_stage_displacement_matrix[0][1],
'y':1/csm.image_to_stage_displacement_matrix[1][0]
}
lateral_positions = [i[axis] for i in positions]
z_positions = [i['z'] for i in positions]
parameters, covariance = curve_fit(quadratic, lateral_positions, z_positions)
z_dest = quadratic(stage.position[axis] + relative_move, *parameters)
parameters, _ = curve_fit(quadratic, lateral_positions, z_positions)
z_dest = quadratic(stage.position[axis] + (relative_move/pixel_step[axis]), *parameters)
z_diff = z_dest - stage.position['z']
return z_diff
@ -88,6 +94,39 @@ def move_and_measure(step_size: dict, axis: str, delta: dict, image1, autofocus_
return delta, offset, focus_data, wrong_axis
def motion_detection(axis: str, direction: int, csm: CSMDep, stage: StageDep, cam: CamDep, logger: InvocationLogger) -> dict:
displacements = [1,2,4,8,16,32,64,128,256,512] # Array of increasing step sizes
motion_minimum = 20 # minimum nuber of pixels for motion to be detected
this_motion_step = {
'x': 0,
'y': 0
}
delta = {
'x': 0,
'y': 0
}
for loop in range(np.shape(displacements)[0]):
this_motion_step[axis] = displacements[loop] * direction * -1
logger.info(f"Testing with step size {this_motion_step[axis]}")
image1 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
csm.move_in_image_coordinates(x = this_motion_step['x'], y = this_motion_step['y'])
image2 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
offset = [x * 1 for x in fft_image_tracking.displacement_between_images(
image_0 = image1, image_1 = image2, sigma=10, fractional_threshold=0.1, pad=True)] # Units is pixels
delta['x'] = int(offset[1])
delta['y'] = int(offset[0])
logger.info(f"Offset measured as {np.abs(delta[axis])}")
if np.abs(delta[axis]) > motion_minimum:
logger.info("Motion detected.")
break
true_final = stage.position
return true_final
class RangeofMotionThing(Thing):
def rom_axis(
self,
@ -114,7 +153,6 @@ class RangeofMotionThing(Thing):
stage_coords = []
cor_lat_steps = []
focused_positions = []
axis_results = {}
# Generate required dictionaries for step sizes and minimum offsets
@ -136,7 +174,6 @@ class RangeofMotionThing(Thing):
parasitic_motion = False
stage_coords.append(stage.position)
focused_positions.append(stage.position)
logger.info("Moving the stage in 5 medium sized steps.")
@ -147,7 +184,6 @@ class RangeofMotionThing(Thing):
logger.info(f"Offset measured as {delta[axis]}")
stage_coords.append(stage.position)
cor_lat_steps.append(offset)
focused_positions.append(stage.position)
# Check for parasitic motion
@ -158,7 +194,7 @@ class RangeofMotionThing(Thing):
# 1 big step followed by 3 small steps
while np.abs(delta[axis]) > np.abs(minimum_offset_small[axis]) and parasitic_motion == False:
z_diff = predict_z(positions = focused_positions, axis = axis, relative_move = step_sizes_big[axis], stage = stage)
z_diff = predict_z(positions = stage_coords, axis = axis, relative_move = step_sizes_big[axis], stage = stage, csm = csm)
logger.info(f"Z calibration complete.")
@ -195,7 +231,6 @@ class RangeofMotionThing(Thing):
stage_coords.append(stage.position)
cor_lat_steps.append(offset)
focused_positions.append(stage.position)
if np.abs(delta[wrong_axis]) > np.abs(wrong_axis_max_small[wrong_axis]):
logger.info(f"Parasitic motion detected in {wrong_axis}-axis whilst measuring {axis}-axis.")
@ -207,37 +242,11 @@ class RangeofMotionThing(Thing):
break
# Motion detection
logger.info(f"Running motion detection")
displacements = np.array([1,2,4,8,16,32,64,128,256,512,1024]) # Array of increasing step sizes
motion_minimum = 20 # minimum nuber of pixels for motion to be detected
final_pos = motion_detection(axis = axis, direction = direction, csm = csm, stage = stage, cam = cam, logger = logger)
this_motion_step = {
'x':np.zeros(np.shape(displacements)[0]),
'y':np.zeros(np.shape(displacements)[0]),
'z':0
}
this_motion_step[axis] = displacements * direction * -1
for loop in range(np.shape(displacements)[0]):
logger.info(f"Testing with step size {this_motion_step[axis][loop]}")
image1 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
stage.move_relative(x = this_motion_step['x'][loop], y = this_motion_step['y'][loop], z = this_motion_step['z'])
image2 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
offset = [x * 1 for x in fft_image_tracking.displacement_between_images(
image_0 = image1, image_1 = image2, sigma=10, fractional_threshold=0.1, pad=True)] # Units is pixels
delta['x'] = int(offset[1])
delta['y'] = int(offset[0])
logger.info(f"Offset measured as {np.abs(delta[axis])}")
if np.abs(delta[axis]) > motion_minimum:
logger.info("Motion detected.")
break
stage_coords[np.shape(stage_coords)[0] - 1] = stage.position
final_pos = stage.position
stage_coords[np.shape(stage_coords)[0] - 1] = final_pos
axis_results = {
"correlation_lateral_steps": cor_lat_steps,