checked 5 sensors run in parralle, cpu max out

2025-12-27 15:15:42 +08:00
parent a8b02105fc
commit 0b1b7138c0
3 changed files with 233 additions and 41 deletions
@@ -0,0 +1,73 @@
+"""
+Example 7: Five Sensors with Async Pipeline
+
+Demonstrates scaling to 5 sensors running in parallel with async mode.
+Each sensor runs in its own process with 3-stage async pipeline.
+"""
+
+import os
+os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
+
+import cv2
+import orisys
+import multiprocessing as mp
+import numpy as np
+
+
+def main():
+    # Configure 5 sensors (using same video for demo - replace with actual sources)
+    configs = [
+        {'vid_src': './s1.mp4', 'isstitch': True, 'cuda': True, 'cal_path': './config/cal.npy'},
+        {'vid_src': './s1.mp4', 'isstitch': True, 'cuda': True, 'cal_path': './config/cal.npy'},
+        {'vid_src': './s1.mp4', 'isstitch': True, 'cuda': True, 'cal_path': './config/cal.npy'},
+        {'vid_src': './s1.mp4', 'isstitch': True, 'cuda': True, 'cal_path': './config/cal.npy'},
+        {'vid_src': './s1.mp4', 'isstitch': True, 'cuda': True, 'cal_path': './config/cal.npy'},
+    ]
+    
+    with orisys.MultiSensor.async_context(configs) as multi:
+        print(f"\n{len(configs)} sensors started. Press 'q' to quit")
+        
+        for all_data in multi:
+            valid_data = [d for d in all_data if d and d['img'] is not None]
+            
+            # Print stats for all sensors
+            for data in valid_data:
+                print(f"S{data['sensor_id']}: FPS={data['fps']:4.1f} Fn={data['fnormal']:7.1f}", end=" | ")
+            if valid_data:
+                print()
+            
+            # Create grid display (2 rows: 3 + 2)
+            imgs = []
+            for data in valid_data:
+                if data['flow'] is not None:
+                    img = orisys.util.draw_arrows(data['img'].copy(), data['flow'], threshold=5)
+                else:
+                    img = data['img']
+                # Add sensor ID label
+                cv2.putText(img, f"S{data['sensor_id']}", (10, 30), 
+                           cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2)
+                imgs.append(img)
+            
+            if len(imgs) >= 5:
+                # Create 2x3 grid (pad with black if needed)
+                h, w = imgs[0].shape[:2]
+                black = np.zeros((h, w, 3), dtype=np.uint8) if len(imgs[0].shape) == 3 else np.zeros((h, w), dtype=np.uint8)
+                
+                row1 = np.hstack([imgs[0], imgs[1], imgs[2]])
+                row2 = np.hstack([imgs[3], imgs[4], black])
+                grid = np.vstack([row1, row2])
+                
+                # Resize for display
+                grid = cv2.resize(grid, (1200, 800))
+                cv2.imshow("5 Sensors Grid", grid)
+            
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+    
+    cv2.destroyAllWindows()
+
+
+if __name__ == '__main__':
+    mp.freeze_support()
+    main()
+