Merge branch 'Project-Babble:main' into main

Author: RamesTheGeneric

BabbleApp/babble_model_loader.py

@@ -15,7 +15,7 @@
 
 
 def run_model(self):
-    if self.runtime == "ONNX" or self.runtime == "Default (ONNX)":
+    if self.runtime in ("ONNX", "Default (ONNX)"):
         frame = cv2.resize(self.current_image_gray, (256, 256))
         frame = transforms.to_tensor(frame)
         frame = transforms.unsqueeze(frame, 0)

BabbleApp/babble_processor.py

@@ -89,10 +89,14 @@ def __init__(
         self.calibrate_config = np.empty((1, 45))
         self.min_max_array = np.empty((2, 45))
 
+        ort.disable_telemetry_events()
         self.opts = ort.SessionOptions()
+        self.opts.inter_op_num_threads = 1
         self.opts.intra_op_num_threads = settings.gui_inference_threads
         self.opts.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
-        if self.runtime == "ONNX" or self.runtime == "Default (ONNX)":  # ONNX
+        self.opts.add_session_config_entry("session.intra_op.allow_spinning", "0")  # ~3% savings worth ~6ms avg latency. Not noticeable at 60fps?
+        self.opts.enable_mem_pattern = False
+        if self.runtime in ("ONNX", "Default (ONNX)"):  # ONNX
             if self.use_gpu:
                 provider = "DmlExecutionProvider"
             else:

BabbleApp/babbleapp.py

@@ -215,10 +215,10 @@ def main():
     # GUI Render loop
     while True:
         # First off, check for any events from the GUI
-        event, values = window.read(timeout=2)
+        event, values = window.read(timeout=30)
 
         # If we're in either mode and someone hits q, quit immediately
-        if event == "Exit" or event == sg.WIN_CLOSED:
+        if event in ("Exit", sg.WIN_CLOSED):
             for (
                 cam
             ) in (

BabbleApp/camera_widget.py

@@ -63,7 +63,7 @@ def __init__(self, widget_id: Tab, main_config: BabbleConfig, osc_queue: Queue):
         self.capture_event = Event()
         self.capture_queue = Queue(maxsize=2)
         self.roi_queue = Queue(maxsize=2)
-        self.image_queue = Queue(maxsize=500)
+        self.image_queue = Queue(maxsize=4)
 
         self.babble_cnn = BabbleProcessor(
             self.config,

BabbleApp/config.py

@@ -91,6 +91,8 @@ def save(self):
                     BabbleConfig(**json.load(settings_file))
                 shutil.copy(CONFIG_FILE_NAME, BACKUP_CONFIG_FILE_NAME)
                 # print("Backed up settings files.") # Comment out because it's too loud.
+            except shutil.SameFileError:
+                pass
             except json.JSONDecodeError:
                 # No backup because the saved settings file is broken.
                 pass

BabbleApp/general_settings_widget.py

@@ -336,4 +336,4 @@ def render(self, window, event, values):
         if changed:
             self.main_config.save()
 
-        self.osc_queue.put((Tab.SETTINGS))
+        self.osc_queue.put(Tab.SETTINGS)

BabbleApp/landmark_model_loader.py

@@ -15,7 +15,7 @@
 
 
 def run_model(self):  # Replace transforms n shit for the pfld model
-    if self.runtime == "ONNX" or self.runtime == "Default (ONNX)":
+    if self.runtime in ("ONNX", "Default (ONNX)"):
         frame = cv2.resize(self.current_image_gray, (256, 256))
         frame = transforms.to_tensor(frame)
         frame = transforms.unsqueeze(frame, 0)

BabbleApp/landmark_processor.py

@@ -88,12 +88,15 @@ def __init__(
         #self.calibrate_config = np.empty((1, 45))
         #self.min_max_array = np.empty((2, 45))
 
-
+        ort.disable_telemetry_events()
         self.opts = ort.SessionOptions()
+        self.opts.inter_op_num_threads = 1
         self.opts.intra_op_num_threads = settings.gui_inference_threads
         self.opts.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
-        if self.runtime == "ONNX" or self.runtime == "Default (ONNX)":    # ONNX 
-            if self.use_gpu: provider = 'DmlExecutionProvider' 
+        self.opts.add_session_config_entry("session.intra_op.allow_spinning", "0")  # ~3% savings worth ~6ms avg latency. Not noticeable at 60fps?
+        self.opts.enable_mem_pattern = False
+        if self.runtime in ("ONNX", "Default (ONNX)"):    # ONNX
+            if self.use_gpu: provider = 'DmlExecutionProvider'
             else: provider = "CPUExecutionProvider"  # Build onnxruntime to get both DML and OpenVINO
             self.sess = ort.InferenceSession(f'{self.model}onnx/model.onnx', self.opts, providers=[provider, ], provider_options=[{'device_id': self.gpu_index}]) # Load Babble CNN until PFLD has been converted
             self.input_name = self.sess.get_inputs()[0].name
@@ -219,7 +222,7 @@ def run(self):
                     self.current_image,
                     self.current_frame_number,
                     self.current_fps,
-                ) = self.capture_queue_incoming.get(block=True, timeout=0.2)
+                ) = self.capture_queue_incoming.get(block=True, timeout=0.1)
             except queue.Empty:
                 # print("No image available")
                 continue

BabbleApp/one_euro_filter.py

@@ -31,9 +31,7 @@ def __call__(self, x):
 
         t = time()
         t_e = t - self.t_prev
-        if (
-            t_e != 0.0
-        ):  # occasionally when switching to algos this becomes zero causing divide by zero errors crashing the filter.
+        if t_e != 0.0:  # occasionally when switching to algos this becomes zero causing divide by zero errors crashing the filter.
             t_e = np.full(x.shape, t_e)
 
             # The filtered derivative of the signal.

BabbleApp/osc.py

@@ -100,9 +100,10 @@ def run(self):
                 return
             try:
                 (self.cam_id, cam_info) = self.msg_queue.get(block=True, timeout=0.1)
-            except:
+            except TypeError:
+                continue
+            except queue.Empty:
                 continue
-
             output_osc(cam_info.output, self)
 
 
@@ -135,7 +136,7 @@ def shutdown(self):
             pass
 
     def recalibrate_mouth(self, address, osc_value):
-        if type(osc_value) != bool:
+        if not isinstance(osc_value, bool):
             return  # just incase we get anything other than bool
         if osc_value:
             for cam in self.cams: