update

example3_plot_data.py

@@ -4,7 +4,7 @@ import cv2
 import orisys
 import numpy as np
 import time
-
+import argparse
 import pyqtgraph as pg
 
 def create_plot():
@@ -90,22 +90,40 @@ for i in range(3):
 
 def main():
     global start_time
-    
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--video","-v", type=str, default="0", help="Camera ID / Video file path")
+    parser.add_argument("--config","-c", type=str, default="./config/ddjx01.json", help="Configuration file path")
+    parser.add_argument("--cal","-cal", type=str, default="./config/ddjx01.npy", help="Calibration file path")
+    parser.add_argument("--verbose","-verbose", type=bool, default=True, help="Print detailed information")
+    args = parser.parse_args()
+
+    # 步骤1：创建传感器对象 (必要步骤)，
+    # config_name为配置文件名（内置配置文件名）或路径（自定义配置文件路径）
+    # cal_path为校准文件路径, 每一个设备需要创建/使用一个校准文件
+
+    # 方式1: 从视频文件读取
+    try:
+        input = int(args.video)
+        is_camera = True
+        sensor = orisys.Sensor(input, config_name=args.config, cal_path= args.cal, verbose=args.verbose)
+    except:
+        is_camera = False
+        sensor = orisys.Sensor(args.video, config_name=args.config, cal_path= args.cal, verbose=args.verbose)
     # 打开视频
     # sensor1 = Sensor("./s1.mp4",isstitch=True,cuda = True,verbose = True)
    # 方式1: 从视频文件读取
-    sensor1 = orisys.Sensor(8, config_name="./config/ddjx01.json", cal_path= "./config/ddjx01.npy", cuda=False, verbose=True)
+    # sensor1 = orisys.Sensor("./s1.mp4", config_name="./config/ddjx01.json", cal_path= "./config/ddjx01.npy", cuda=False, verbose=True)
 
     start_time = time.time()
     is_save = False
     frame_count = 0
     writer = None
     while True:
-        sensor1.get_img() # 提取并拼接复眼图像
+        sensor.get_img() # 提取并拼接复眼图像
         
-        if is_save and writer is not None and sensor1.frame is not None:
+        if is_save and writer is not None and sensor.frame is not None:
             frame_count += 1
-            save_img = sensor1.frame
+            save_img = sensor.frame
             
             # Convert grayscale (1 channel) to BGR (3 channels) if needed
             if len(save_img.shape) == 2 or (len(save_img.shape) == 3 and save_img.shape[2] == 1):
@@ -115,15 +133,15 @@ def main():
             
             writer.write(save_img)
 
-        sensor1.compute_deformation(check_motion=False) # 计算形变和分解
+        sensor.compute_deformation(check_motion=False) # 计算形变和分解
         # 提取信息：
         # 向量场: VRAW, VNORMAL, VSHEAR: 原始，法向，切向 
         # 帧率，时间戳: FPS, TIMESTAMP
         # 变形量总和: FNORMAL , FSHEARX, FSHEARY : 法向，切向（X)，切向（Y)
-        fps, fn, fx, fy, flow = sensor1.read_info(sensor1.info.FPS, sensor1.info.FNORMAL, sensor1.info.FSHEARX, sensor1.info.FSHEARY, sensor1.info.VRAW)
+        fps, fn, fx, fy, flow, vnormal, vshear = sensor.read_info(sensor.info.FPS, sensor.info.FNORMAL, sensor.info.FSHEARX, sensor.info.FSHEARY, sensor.info.VRAW, sensor.info.VNORMAL,sensor.info.VSHEAR)
         print(fps,fn,fx,fy)
         # 显示向量场
-        arrows  = orisys.util.draw_arrows(sensor1.img, flow, threshold=5, grid_spacing=10, arrow_scale=1.0) 
+        arrows  = orisys.util.draw_arrows(sensor.img, flow, threshold=5, grid_spacing=10, arrow_scale=1.0) 
         cv2.imshow("Deformation", arrows)
         # 显示深度图
         mag = draw_magnitude_map(flow)
@@ -149,7 +167,7 @@ def main():
             # Ensure directory exists
             os.makedirs(os.path.dirname(save_path), exist_ok=True)
             # Get frame dimensions from the actual frame
-            save_img = sensor1.frame
+            save_img = sensor.frame
 
             if save_img is not None:
                 # Convert grayscale (1 channel) to BGR (3 channels) if needed for dimension check
@@ -180,7 +198,7 @@ def main():
                 print(f"Stop writing, total frames: {frame_count}")
             frame_count = 0
     
-    sensor1.disconnect() # 断开传感器连接
+    sensor.disconnect() # 断开传感器连接
     
 
 

src/orisys/sensor.py

@@ -150,9 +150,12 @@ class Sensor:
         self.__tracker = Tracker(adaptive=True, cuda=cuda, verbose=self.verbose, config_tracker=self.__config_tracker)
         self.__contact3d = Contact3D(config_contact=self.__config_contact, verbose=self.verbose)
         self.__hhd = None
-        # cfg_ds = self.__config_tracker.get("hhd_downsample", None)
-        # self._hhd_downsample = max(1, int(cfg_ds if cfg_ds is not None else hhd_downsample))
-        self._hhd_downsample = self.__config_tracker.get("hhd_downsample", None)
+        # Integer >= 1: run HHD on flow downsampled by this factor for speed (1 = full res).
+        _raw_ds = self.__config_tracker.get("hhd_downsample", 1)
+        try:
+            self._hhd_downsample = max(1, int(_raw_ds)) if _raw_ds is not None else 1
+        except (TypeError, ValueError):
+            self._hhd_downsample = 1
         self._hhd_grid_shape = None
         cfg_backend = self.__config_tracker.get("backend", None)
         self.poisson_backend = cfg_backend if cfg_backend is not None else backend
@@ -297,7 +300,10 @@ class Sensor:
             raise Exception("Warning: Compute flow first")
 
         orig_h, orig_w = flow.shape[:2]
-        k = self._hhd_downsample
+        try:
+            k = max(1, int(self._hhd_downsample))
+        except (TypeError, ValueError):
+            k = 1
 
         if k > 1:
             ds_w = max(1, orig_w // k)