v0.6.0

ulc_mm_package/QtGUI/acquisition.py

@@ -1,4 +1,4 @@
-""" Image manager
+"""Image manager
 
 Receives images from the camera and sends them to Liveview and ScopeOp.
 

ulc_mm_package/QtGUI/dev_run.py

@@ -49,9 +49,6 @@
 
 from ulc_mm_package.image_processing.processing_constants import FLOWRATE
 
-from ulc_mm_package.utilities.ngrok_utils import make_tcp_tunnel, NgrokError
-from ulc_mm_package.utilities.email_utils import send_ngrok_email
-
 from ulc_mm_package.neural_nets.AutofocusInference import AutoFocus
 import ulc_mm_package.neural_nets.neural_network_constants as nn_constants
 
@@ -636,13 +633,6 @@ def __init__(self, *args, **kwargs):
         # Misc
         self.fan.turn_on_all()
         self.btnExit.clicked.connect(self.exit)
-        try:
-            ngrok_address = make_tcp_tunnel()
-            send_ngrok_email()
-        except NgrokError as e:
-            print(f"Ngrok error : {e}")
-            ngrok_address = "-ngrok error-"
-        self.lblngrok.setText(f"{ngrok_address}")
 
         # Set slider min/max
         self.min_exposure_us = 100

ulc_mm_package/QtGUI/form_gui.py

@@ -1,4 +1,4 @@
-""" Experiment form GUI window
+"""Experiment form GUI window
 
 Takes user input and exports experiment metadata.
 

ulc_mm_package/QtGUI/liveview_gui.py

@@ -1,4 +1,4 @@
-""" Liveview GUI window
+"""Liveview GUI window
 
 Displays camera preview and conveys info to user during runs."""
 

ulc_mm_package/QtGUI/oracle.py

@@ -1,4 +1,4 @@
-""" High-level state machine manager.
+"""High-level state machine manager.
 
 The Oracle sees all and knows all.
 It owns all GUI windows, threads, and worker objects (ScopeOp and Acquisition).
@@ -70,8 +70,6 @@
     AUTOFOCUS_MODEL_DIR,
     YOGO_MODEL_DIR,
 )
-from ulc_mm_package.utilities.email_utils import send_ngrok_email, EmailError
-from ulc_mm_package.utilities.ngrok_utils import make_tcp_tunnel, NgrokError
 
 from ulc_mm_package.QtGUI.scope_op import ScopeOp
 from ulc_mm_package.QtGUI.form_gui import FormGUI
@@ -159,24 +157,7 @@ def __init__(self):
         self.next_state()
 
     def _init_tcp(self):
-        try:
-            tcp_addr = make_tcp_tunnel()
-            self.logger.info(f"SSH address is {tcp_addr}.")
-            self.liveview_window.update_tcp(tcp_addr)
-            send_ngrok_email()
-        except NgrokError as e:
-            self.logger.warning(
-                f"SSH address could not be found - {e}. This can be safely ignored."
-            )
-            self.liveview_window.update_tcp("unavailable")
-        except EmailError as e:
-            self.logger.warning(
-                f"SSH address could not be emailed - {e}. This can be safely ignored."
-            )
-        except Exception as e:
-            self.logger.warning(
-                f"Unexpected error while setting up TCP: {e}. This can be safely ignored."
-            )
+        self.liveview_window.update_tcp("unavailable")
 
     def _check_lock(self):
         if path.isfile(LOCKFILE):

ulc_mm_package/QtGUI/scope_op.py

@@ -1,4 +1,4 @@
-""" Mid-level/hardware state machine manager
+"""Mid-level/hardware state machine manager
 
 Controls hardware (ie. the Scope) operations.
 Manages hardware routines and interactions with Oracle and Acquisition.
@@ -875,6 +875,9 @@ def run_experiment(self, img, timestamp) -> None:
             self.mscope.cell_diagnosis_model.work_queue_size(),
         )
 
+        # ------------------------------------
+        # Get and process YOGO results
+        # ------------------------------------
         t0 = perf_counter()
         for result in prev_yogo_results:
             self.mscope.predictions_handler.add_yogo_pred(result)
@@ -903,6 +906,9 @@ def run_experiment(self, img, timestamp) -> None:
         t1 = perf_counter()
         self._update_metadata_if_verbose("yogo_result_mgmt", t1 - t0)
 
+        # ------------------------------------
+        # Run periodic singleshot autofocus routine
+        # ------------------------------------
         t0 = perf_counter()
         resized_img = cv2.resize(img, IMG_RESIZED_DIMS, interpolation=cv2.INTER_CUBIC)
         try:
@@ -937,8 +943,10 @@ def run_experiment(self, img, timestamp) -> None:
         if filtered_focus_err is not None:
             self.filtered_focus_err = filtered_focus_err
 
+        # ------------------------------------
+        # Get classic image sharpness metric
+        # ------------------------------------
         t0 = perf_counter()
-
         # Downsample image for use in flowrate + classic image focus metric
         img_ds_10x = downsample_image(img, 10)
         try:
@@ -951,6 +959,10 @@ def run_experiment(self, img, timestamp) -> None:
             )
             self.oof_to_motor_sweep()
             return
+
+        # ------------------------------------
+        # Run flow control routine
+        # ------------------------------------
         try:
             self.flowrate, _ = self.flowcontrol_routine.send((img_ds_10x, timestamp))
         except Exception as e:
@@ -963,11 +975,15 @@ def run_experiment(self, img, timestamp) -> None:
         t1 = perf_counter()
         self._update_metadata_if_verbose("flowrate_dt", t1 - t0)
 
+        # ------------------------------------
         # Run periodic autobrightness routine
+        # ------------------------------------
         curr_mean_pixel_val = self.periodic_autobrightness_routine.send(resized_img)
 
+        # ------------------------------------
+        # Update remaining metadata in per-image csv
+        # ------------------------------------
         t0 = perf_counter()
-        # Update remaining metadata
         self.img_metadata["motor_pos"] = self.mscope.motor.getCurrentPosition()
         try:
             pressure, status = self.mscope.pneumatic_module.getPressure()

ulc_mm_package/hardware/real/pneumatic_module.py

@@ -75,8 +75,9 @@ def __init__(
         (
             self.min_duty_cycle,
             self.max_duty_cycle,
-            self.min_step_size,
+            self.default_min_step_size,
         ) = self.get_config_params()
+        self.min_step_size = self.default_min_step_size
 
         self.duty_cycle = self.max_duty_cycle
         self.prev_duty_cycle = self.duty_cycle

ulc_mm_package/hardware/scope.py

@@ -153,7 +153,7 @@ def reset_for_end_experiment(self) -> None:
         self.cell_diagnosis_model.reset(wait_for_jobs=False)
 
         # Reset predictions handler
-        self.predictions_handler: PredictionsHandler = PredictionsHandler()
+        self.predictions_handler.reset()
 
     def shutoff(self):
         self.logger.info("Shutting off scope hardware.")

ulc_mm_package/hardware/scope_routines.py

@@ -15,7 +15,6 @@
     checkLedWorking,
 )
 from ulc_mm_package.image_processing.flow_control import (
-    FlowController,
     CantReachTargetFlowrate,
 )
 from ulc_mm_package.image_processing.cell_finder import (
@@ -244,10 +243,12 @@ def flow_control_routine(
         mscope.flow_controller.reset()
         flow_controller = mscope.flow_controller
         flow_controller.set_target_flowrate(target_flowrate)
+        flow_controller.set_alpha(processing_constants.FLOW_CONTROL_EWMA_ALPHA)
         if fast_flow:
             flow_controller.set_alpha(
                 processing_constants.FLOW_CONTROL_EWMA_ALPHA * 2
             )  # Double the alpha, ~halve the half life
+            flow_controller.pneumatic_module.min_step_size *= 2
 
         while True:
             img, timestamp = yield flow_val, syringe_can_move
@@ -261,15 +262,25 @@ def flow_control_routine(
             flow_val, flow_error, syringe_can_move = flow_controller.control_flow(
                 img, timestamp
             )
+
+            # This check is here so that we don't flood the logger with the same message repeatedly
             if (prev_can_move is True) and (syringe_can_move is False):
-                # This is here so that we don't flood the logger with the same message
+                # If we were in fast_flow, we need to reset the min_step_size
+                if fast_flow:
+                    flow_controller.pneumatic_module.min_step_size = (
+                        flow_controller.pneumatic_module.default_min_step_size
+                    )
+
                 self.logger.error(
                     "Can't reach target flowrate. Syringe at end of travel."
                 )
 
             if fast_flow:
                 if flow_error is not None:
                     if flow_error == 0:
+                        flow_controller.pneumatic_module.min_step_size = (
+                            flow_controller.pneumatic_module.default_min_step_size
+                        )
                         return flow_val
 
     @init_generator
@@ -386,6 +397,7 @@ def periodic_autobrightness_routine(
             if counter >= processing_constants.PERIODIC_AB_PERIOD_NUM_FRAMES:
                 autobrightness.autobrightness_pid_control(img)
                 curr_img_brightness = autobrightness.prev_mean_img_brightness
+                counter = 0
 
     def checkPressureDifference(
         self, mscope: MalariaScope, ambient_pressure: float
@@ -485,7 +497,9 @@ def find_cells_routine(
         # Maximum number of times to run check for cells routine before aborting
         max_attempts = 3
         cell_finder = CellFinder()
-        flow_controller = FlowController(mscope.pneumatic_module)
+        mscope.flow_controller.reset()
+        flow_controller = mscope.flow_controller
+
         img = yield
 
         # Initial check for cells, return current motor position if cells found
@@ -495,6 +509,11 @@ def find_cells_routine(
         except NoCellsFound:
             cell_finder.reset()
 
+        # Defensive check, ensure the motor isn't moving (say for example,
+        # if CellFinder was triggered by an OOF exception and SSAF just triggered a motor move)
+        while mscope.motor.is_locked():
+            pass
+
         while True:
             """
             1. Pull syringe for pull_time seconds (unless deliberately skipped)

ulc_mm_package/image_processing/data_storage.py

@@ -298,16 +298,16 @@ def close(
                 summary_report_dir / f"{self.time_str}_per_image_metadata_plot.jpg"
             )
 
-            per_img_metadata_file = open(self.per_img_metadata_filename, "r")
             counts_plot_loc = str(summary_report_dir / "counts.jpg")
             conf_plot_loc = str(summary_report_dir / "confs.jpg")
             objectness_plot_loc = str(summary_report_dir / "objectness.jpg")
 
             # Only generate additional plots if DEBUG_REPORT environment variable is set to True
             if DEBUG_REPORT:
-                make_per_image_metadata_plots(
-                    per_img_metadata_file, per_image_metadata_plot_save_loc
-                )
+                with open(self.per_img_metadata_filename, "r") as per_img_metadata_file:
+                    make_per_image_metadata_plots(
+                        per_img_metadata_file, per_image_metadata_plot_save_loc
+                    )
 
                 try:
                     make_cell_count_plot(pred_tensors, counts_plot_loc)

ulc_mm_package/neural_nets/NCSModel.py

@@ -116,6 +116,9 @@ def _compile_model(
                 compiled_model = self.core.compile_model(
                     model,
                     self.device_name,
+                    config={
+                        "PERFORMANCE_HINT": "THROUGHPUT",
+                    },
                 )
                 self.connected = True
                 return compiled_model

ulc_mm_package/neural_nets/neural_network_constants.py

@@ -7,14 +7,14 @@
 
 
 # ================ Autofocus constants ================ #
-AF_PERIOD_S = 0.5
+AF_PERIOD_S = 0.1  # (10 imgs/sec)
 AF_PERIOD_NUM = int(
     AF_PERIOD_S * ACQUISITION_FPS
 )  # Used for periodic (ie. EWMA) autofocus
-AF_BATCH_SIZE = 10  # Used for single shot autofocus
+AF_BATCH_SIZE = 20  # Used for single shot autofocus
 
 AF_THRESHOLD = 2
-AF_QSIZE = 10  # For AF_PERIOD_S = 0.5, we have a max delay of 5 sec
+AF_QSIZE = 25
 
 AUTOFOCUS_MODEL_NAME = "fast-cosmos-557"
 AUTOFOCUS_MODEL_DIR = str(

ulc_mm_package/neural_nets/predictions_handler.py

@@ -71,6 +71,19 @@ def __init__(self):
         # Setup heatmap masking
         self.heatmaps = np.zeros((len(YOGO_CLASS_LIST), sy * sx))
 
+    def reset(self):
+        self.pred_tensors.fill(0)
+        self.new_pred_pointer = 0
+        self.max_confs = {x: [] for x in self.class_ids}
+        self.curr_min_of_max_confs_by_class = {
+            x: HIGH_CONF_THRESH - 1e-6 for x in self.class_ids
+        }
+        self.min_confs = {x: [] for x in self.class_ids}
+        self.curr_max_of_min_confs_by_class = {
+            x: HIGH_CONF_THRESH for x in self.class_ids
+        }
+        self.heatmaps.fill(0)
+
     def add_raw_pred_to_heatmap(self, yogo_res: AsyncInferenceResult) -> None:
         """Add the raw YOGO prediction to the heatmap.
 

ulc_mm_package/scope_constants.py

@@ -200,10 +200,6 @@ def IMG_HEIGHT(self) -> int:
 if VERBOSE:
     PER_IMAGE_METADATA_KEYS.extend(PER_IMAGE_TIMING_KEYS)
 
-# ================ Environment variables ================ #
-NGROK_AUTH_TOKEN_ENV_VAR = "NGROK_AUTH_TOKEN"
-EMAIL_PW_TOKEN = "GMAIL_TOKEN"
-
 # ================ SSD directory constants ================ #
 SSD_NAME = "SamsungSSD"
 if SIMULATION:

ulc_mm_package/summary_report/parasitemia_visualization.py

@@ -169,6 +169,7 @@ def make_parasitemia_plot(parasitemia, err, savefile):
     fig.subplots_adjust(left=0.1, right=0.9, top=0.8, bottom=0.1)
     fig.tight_layout()
     plt.savefig(savefile)
+    plt.close()
 
 
 if __name__ == "__main__":