update

.gitignore

@@ -1,5 +1,6 @@
 # ---> Python
 # Byte-compiled / optimized / DLL files
+test/
 __pycache__/
 *.py[cod]
 *$py.class

load_normal.py

@@ -0,0 +1,49 @@
+import cv2
+import os
+import numpy as np
+
+def load_normal(path, binocular=False, left_only=False):
+    if binocular and not left_only:
+        normal_path_L = os.path.join(
+            os.path.dirname(path), "normal", os.path.basename(path) + "_L.png"
+        )
+        normal_image_L = cv2.imread(normal_path_L, cv2.IMREAD_UNCHANGED)
+        normal_path_R = os.path.join(
+            os.path.dirname(path), "normal", os.path.basename(path) + "_R.png"
+        )
+        normal_image_R = cv2.imread(normal_path_R, cv2.IMREAD_UNCHANGED)
+        normalized_normal_image_L = normal_image_L / 255.0 * 2.0 - 1.0
+        normalized_normal_image_R = normal_image_R / 255.0 * 2.0 - 1.0
+        return normalized_normal_image_L, normalized_normal_image_R
+    else:
+        if binocular and left_only:
+            normal_path = os.path.join(
+                os.path.dirname(path), "normal", os.path.basename(path) + "_L.png"
+            )
+        else:
+            normal_path = os.path.join(
+                os.path.dirname(path), "normal", os.path.basename(path) + ".png"
+            )
+        normal_image = cv2.imread(normal_path, cv2.IMREAD_UNCHANGED)
+        normalized_normal_image = normal_image / 255.0 * 2.0 - 1.0
+        return normalized_normal_image
+
+def show_rgb(event, x, y, flags, param):
+    if event == cv2.EVENT_MOUSEMOVE:
+        pixel_value = param[y, x]
+        print(f"RGB at ({x},{y}): {pixel_value}")
+
+if __name__ == "__main__":
+    path = "/Users/hofee/temp/1"
+    normal_image = load_normal(path, binocular=True, left_only=True)
+    display_image = ((normal_image + 1.0) / 2.0 * 255).astype(np.uint8)
+
+    cv2.namedWindow("Normal Image")
+    cv2.setMouseCallback("Normal Image", show_rgb, param=display_image)
+
+    while True:
+        cv2.imshow("Normal Image", display_image)
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    cv2.destroyAllWindows()

runners/cad_close_loop_strategy.py

@@ -88,10 +88,10 @@ class CADCloseLoopStrategyRunner(Runner):
         )
         np.savetxt(f"first_real_pts_{model_name}.txt", first_splitted_real_world_pts)
         """ register """
-        Log.info("[Part 1/5] do registeration")
+        Log.info("[Part 1/4] do registeration")
         real_world_to_cad = PtsUtil.register(first_splitted_real_world_pts, cad_model)
         cad_to_real_world = np.linalg.inv(real_world_to_cad)
-        Log.success("[Part 1/5] finish init and register")
+        Log.success("[Part 1/4] finish init and register")
         real_world_to_blender_world = np.eye(4)
         real_world_to_blender_world[:3, 3] = np.asarray([0, 0, 0.9215])
         cad_model_real_world: trimesh.Trimesh = cad_model.apply_transform(
@@ -108,7 +108,7 @@ class CADCloseLoopStrategyRunner(Runner):
             temp_dir = "/home/yan20/nbv_rec/project/franka_control/temp_output"
             cad_model_blender_world.export(os.path.join(temp_dir, f"{temp_name}.obj"))
             """ sample view """
-            Log.info("[Part 2/5] start running renderer")
+            Log.info("[Part 2/4] start running renderer")
             subprocess.run(
                 [
                     self.blender_bin_path,
@@ -121,12 +121,12 @@ class CADCloseLoopStrategyRunner(Runner):
                 capture_output=True,
                 text=True,
             )
-            Log.success("[Part 2/5] finish running renderer")
+            Log.success("[Part 2/4] finish running renderer")
             
             """ preprocess """
-            Log.info("[Part 3/5] start preprocessing data")
+            Log.info("[Part 3/4] start preprocessing data")
             save_scene_data(temp_dir, temp_name)
-            Log.success("[Part 3/5] finish preprocessing data")
+            Log.success("[Part 3/4] finish preprocessing data")
 
             pts_dir = os.path.join(temp_dir, temp_name, "pts")
             sample_view_pts_list = []

vis_pts_and_nrm.py

@@ -0,0 +1,54 @@
+# import numpy as np
+# import matplotlib.pyplot as plt
+# from mpl_toolkits.mplot3d import Axes3D
+
+# # 假设 points_and_normals 是你的 Nx6 矩阵
+# # 前三列是点坐标，后三列是法线
+# points_and_normals = np.loadtxt("/Users/hofee/Downloads/temp_output/cad_model_world/points_and_normals.txt")  # 这里用随机点代替你的数据
+# points = points_and_normals[:100, :3]
+# normals = points_and_normals[:100, 3:]
+
+# # 创建3D图形
+# fig = plt.figure()
+# ax = fig.add_subplot(111, projection='3d')
+
+# # 绘制点云
+# ax.scatter(points[:, 0], points[:, 1], points[:, 2], color='b', marker='o')
+
+# # 绘制法线 (从每个点出发的一小段箭头)
+# ax.quiver(points[:, 0], points[:, 1], points[:, 2],
+#           normals[:, 0], normals[:, 1], normals[:, 2], length=0.1, color='r')
+
+# plt.show()
+
+import numpy as np
+
+# 假设 points_and_normals 是你的 Nx6 矩阵
+# points_and_normals[:,:3] 是点的坐标
+# points_and_normals[:,3:] 是法线
+points_and_normals = np.loadtxt("/Users/hofee/Downloads/temp_output/cad_model_world/points_and_normals.txt")  # 这里用随机点代替你的数据
+print(points_and_normals.shape)
+points = points_and_normals[300:400, :3]
+normals = points_and_normals[300:400, 3:]
+
+# 设置你想在法线方向上采样的距离范围和点数
+num_samples_per_point = 20  # 每个法线方向采样的点数
+sampling_distances = np.linspace(0, 0.5, num_samples_per_point)  # 采样距离范围
+
+# 创建一个空列表来保存采样点
+sampled_points = []
+
+# 对每个点进行法线方向的采样
+for point, normal in zip(points, normals):
+    for dist in sampling_distances:
+        # 在法线方向上偏移点
+        sampled_point = point + dist * normal
+        sampled_points.append(sampled_point)
+
+# 转换为 numpy 数组
+sampled_points = np.array(sampled_points)
+
+# 保存为点云文件 (例如 .txt 或 .xyz 格式)
+np.savetxt('sampled_points.txt', sampled_points)
+
+print("采样点云已保存为 'sampled_points.xyz'")