update foe to contact for easy understanding

2025-12-28 20:19:43 +08:00
parent 79c55b7529
commit e8e4fd8625
6 changed files with 493 additions and 49 deletions
@@ -0,0 +1,88 @@
+import os
+os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"  # Windows 下禁用硬件加速，避免兼容性问题
+import cv2
+import orisys
+import numpy as np
+
+def main():
+    
+    # 方式1: 从视频文件读取
+    sensor = orisys.Sensor("./s1.mp4", isstitch=True, cuda=True, verbose=True)
+    
+    # 方式2: 从摄像头读取（取消注释使用）
+    # sensor = orisys.Sensor(0, isstitch=True, cuda=True, verbose=True)
+
+    print("\n按 'q' 退出程序，按 'r' 重置光流追踪器")
+
+    while True:
+        # 步骤 2.1: 获取并拼接图像
+        sensor.get_img()
+        
+        # 步骤 2.2: 计算形变场
+        sensor.compute_deformation()
+        
+        fps, flow, vnormal = sensor.read_info(
+            sensor.info.FPS,
+            sensor.info.VRAW,
+            sensor.info.VNORMAL
+        )
+     
+        arrows = orisys.util.draw_arrows(
+            sensor.img.copy(),  # 使用 copy() 避免修改原图
+            vnormal,
+            threshold=5,
+            grid_spacing=10,
+            arrow_scale=1.0
+        )
+        cv2.imshow("形变场 Deformation", arrows)
+
+        mag_img = orisys.util.draw_magnitude_map(
+            sensor.img.copy(),
+            vnormal,
+            threshold=5,
+            colormap=cv2.COLORMAP_HOT,
+            downsample_factor = 1
+        )
+        cv2.imshow("magnitude map", mag_img)
+
+        # 计算触碰点
+        contact_result = sensor.get_contact(multiple_foe=False, min_magnitude=1, expansion_threshold=0.01,denoise_sigma=15)
+        # 在图像上触碰点和区域
+        image_with_foe = orisys.util.draw_foe(sensor.img.copy(), contact_result)
+        cv2.imshow("Contact Centroid", image_with_foe)
+
+        # 计算触碰区域
+        divergence = contact_result['divergence_map']
+        
+        # 归一化散度值到0-255范围（使用绝对值，然后归一化）
+        div_abs = divergence
+        if div_abs.max() > div_abs.min():
+            div_normalized = ((div_abs - div_abs.min()) / (div_abs.max() - div_abs.min()) * 255).astype(np.uint8)
+        else:
+            div_normalized = np.zeros_like(div_abs, dtype=np.uint8)
+        
+        # 应用颜色映射（使用JET：蓝色=低散度，红色=高散度）
+        cv2.imshow("Divergence Map", cv2.applyColorMap(div_normalized, cv2.COLORMAP_JET))
+        
+
+        # =====================================================================
+        # 4. 键盘控制
+        # =====================================================================
+        key = cv2.waitKey(1) & 0xFF
+        if key == ord("q"):
+            print("\n退出程序...")
+            break
+        if key == ord("r"):
+            # 重置光流追踪器（当追踪漂移时使用）
+            sensor.reset()
+            print("光流追踪器已重置")
+    
+    # =========================================================================
+    # 5. 清理资源
+    # =========================================================================
+    sensor.disconnect()  # 释放视频源和相关资源
+    cv2.destroyAllWindows()
+
+
+if __name__ == '__main__':
+    main()