json update

src/orisys/sensor.py

@@ -3,7 +3,6 @@
 """
 import os
 import numpy as np
-from scipy import ndimage
 import cv2
 from .Stitcher import Stitcher
 from .tracker import Tracker
@@ -25,7 +24,7 @@ class Sensor:
         Initialize Sensor with video source and configuration.
         
         Args:
-            vid_src: Video source (int for camera ID, str for file path, None for default camera)
+            vid_src: Video source (int for camera ID, str for file path)
             isstitch: Whether to use stitching mode for multi-tile sensor (default: False)
             verbose: Whether to print initialization logs (default: True)
             cuda: Whether to use CUDA acceleration for optical flow & decomposition (default: True)
@@ -38,12 +37,10 @@ class Sensor:
             self.CUPY_AVAILABLE = False
 
         # Initialize settings
-        if vid_src is not None:
-            vid_src = vid_src
-        else:
-            print("User must specify a video source.")
-        self.vid_src, self.isstitch, self.cuda, self.verbose = vid_src, isstitch, cuda, verbose
-        self.config_name = config_name
+        if vid_src is None:
+            raise ValueError("User must specify a video source.")
+
+        self.vid_src, self.isstitch, self.cuda, self.verbose, self.config_name = vid_src, isstitch, cuda, verbose, config_name
         
         # Initialize Sensor Configuration
         self.get_config()
@@ -71,8 +68,6 @@ class Sensor:
             ret, frame = self.cap.read()
             if not ret:
                 time.sleep(1)
-        if self.verbose:
-            print("Video source connected.")
         
         # Initialize and calibrate
         self.__find_stitch_boxes(frame, show=False)
@@ -82,23 +77,20 @@ class Sensor:
             print("Sensor initialized and calibrated.")
         
         # Initialize state variables
-        self.stitch_valid = False
-        self.n_boxes = None
+        self.stitch_valid = self.imgupdate = self.vupdate = False
         self.stitch_calibration = []
-        self.img = self.flow = self.normal = self.shear = self.force = self.depth = None
-        self.img_filtered = None  # For temporal noise reduction
+        self.img = self.flow = self.normal = self.shear = self.force = self.depth = self.n_boxes = self.img_filtered = None
         self.fnormal=self.fshearx=self.fsheary=self.ftor=0.0
-        self.imgupdate = self.vupdate = False
 
         # Logging state
         self.last_log_time = time.time()
         self.fps = 0
 
         if self.verbose:
-            print("Settings:")
+            print("Settings:" {self.config_name})
             print(f"  Video source: {vid_src}")
             print(f"  Stitch mode: {isstitch}")
-            print(f"  CUDA acceleration: {cuda}")
+            print(f"  CUDA acceleration: {self.cuda}")
             print(f"  Cupy available: {self.CUPY_AVAILABLE}")
             print(f"  OpenCV CUDA devices: {cv2.cuda.getCudaEnabledDeviceCount()}")
     
@@ -128,6 +120,15 @@ class Sensor:
         self.config_index = self.config["camera"]["index"]
         self.config_pos_default = self.config["camera"]["pos_default"]
 
+        if self.verbose:
+            print("Config loaded: ", str(self.config_name))
+            print("  Resolution raw: ", str(self.config_resolution_raw))
+            print("  FPS: ", str(self.config_fps))
+            print("  Units: ", str(self.config_units))
+            print("  Resolution stitch: ", str(self.config_resolution_stitch))
+            print("  Index: ", str(self.config_index))
+            print("  Pos default: ", str(self.config_pos_default))
+
     def get_img(self):
         """
         Capture frame from video source, convert to grayscale, and perform stitching.