upd

configs/local/inference_config.yaml

@@ -15,7 +15,7 @@ runner:
       - OmniObject3d_test
 
   blender_script_path: "/media/hofee/data/project/python/nbv_reconstruction/blender/data_renderer.py"
-  output_dir: "/media/hofee/data/results/nbv_rec_inference/global_only_ycb_241204"
+  output_dir: " /media/hofee/data/data/temp"
   pipeline: nbv_reconstruction_pipeline
   voxel_size: 0.003
   min_new_area: 1.0
@@ -34,8 +34,8 @@ dataset:
   #   load_from_preprocess: True
 
   OmniObject3d_test:
-    root_dir: "/media/hofee/data/results/ycb_preprocessed_dataset"
+    root_dir: "/media/hofee/data/data/new_testset_output"
-    model_dir: "/media/hofee/data/data/ycb_obj"
+    model_dir: "/media/hofee/data/data/scaled_object_meshes"
     source: seq_reconstruction_dataset_preprocessed
     # split_file: "C:\\Document\\Datasets\\data_list\\OmniObject3d_test.txt"
     type: test

configs/local/strategy_generate_config.yaml

@@ -22,6 +22,6 @@ runner:
   
 datasets:
     OmniObject3d:
-      root_dir: /media/hofee/data/results/ycb_view_data
+      root_dir: /media/hofee/data/data/test_bottle/view 
       from: 0
       to: -1 # ..-1 means end

configs/local/view_generate_config.yaml

@@ -8,11 +8,11 @@ runner:
     root_dir: experiments
   generate:
     port: 5002
-    from: 1
+    from: 0
     to: 50 # -1 means all
-    object_dir: /media/hofee/data/data/ycb_obj
+    object_dir: /media/hofee/data/data/test_bottle/bottle_mesh
     table_model_path: /media/hofee/data/data/others/table.obj
-    output_dir: /media/hofee/data/results/ycb_view_data
+    output_dir: /media/hofee/data/data/test_bottle/view
     binocular_vision: true
     plane_size: 10
     max_views: 512
@@ -34,7 +34,7 @@ runner:
         max_y: 0.05
         min_z: 0.01
         max_z: 0.01
-        random_rotation_ratio: 0.3
+        random_rotation_ratio: 0.0
       random_objects:
         num: 4
         cluster: 0.9

core/seq_dataset.py

@@ -63,11 +63,15 @@ class SeqReconstructionDataset(BaseDataset):
             scene_max_cr_idx = 0
             frame_len = DataLoadUtil.get_scene_seq_length(self.root_dir, scene_name)
 
-            for i in range(frame_len):
+            for i in range(10,frame_len):
                 path = DataLoadUtil.get_path(self.root_dir, scene_name, i)
                 pts = DataLoadUtil.load_from_preprocessed_pts(path, "npy")
+                print(pts.shape)
                 if pts.shape[0] == 0:
                     continue
+                else:
+                    break
+            print(i)
             datalist.append({
                 "scene_name": scene_name,
                 "first_frame": i,
@@ -179,9 +183,9 @@ if __name__ == "__main__":
     np.random.seed(seed)
     
     config = {
-        "root_dir": "/media/hofee/data/results/ycb_view_data",
+        "root_dir": "/media/hofee/data/data/test_bottle/view",
         "source": "seq_reconstruction_dataset",
-        "split_file": "/media/hofee/data/results/ycb_test.txt",
+        "split_file": "/media/hofee/data/data/test_bottle/test_bottle.txt",
         "load_from_preprocess": True,
         "filter_degree": 75,
         "num_workers": 0,
@@ -189,7 +193,7 @@ if __name__ == "__main__":
         "type": namespace.Mode.TEST,
     }
     
-    output_dir = "/media/hofee/data/results/ycb_preprocessed_dataset"
+    output_dir = "/media/hofee/data/data/test_bottle/preprocessed_dataset"
     os.makedirs(output_dir, exist_ok=True)
 
     ds = SeqReconstructionDataset(config)

core/seq_dataset_preprocessed.py

@@ -21,7 +21,7 @@ class SeqReconstructionDatasetPreprocessed(BaseDataset):
         super(SeqReconstructionDatasetPreprocessed, self).__init__(config)
         self.config = config
         self.root_dir = config["root_dir"]
-        self.real_root_dir = r"/media/hofee/data/results/ycb_view_data"
+        self.real_root_dir = r"/media/hofee/data/data/new_testset"
         self.item_list = os.listdir(self.root_dir)
 
     def __getitem__(self, index):
@@ -66,7 +66,7 @@ if __name__ == "__main__":
     load_from_preprocess: True
     '''
     config = {
-        "root_dir": "H:\\AI\\Datasets\\packed_test_data",
+        "root_dir": "/media/hofee/data/data/test_bottle/preprocessed_dataset",
         "source": "seq_reconstruction_dataset",
         "split_file": "H:\\AI\\Datasets\\data_list\\OmniObject3d_test.txt",
         "load_from_preprocess": True,

preprocess/preprocessor.py

@@ -164,7 +164,7 @@ def save_scene_data(root, scene, scene_idx=0, scene_total=1,file_type="txt"):
 
 if __name__ == "__main__":
     #root = "/media/hofee/repository/new_data_with_normal"
-    root = r"/media/hofee/data/results/ycb_view_data"
+    root = r"/media/hofee/data/data/test_bottle/view"
     scene_list = os.listdir(root)
     from_idx = 0 # 1000
     to_idx = len(scene_list) # 1500

runners/inferencer.py

@@ -146,7 +146,21 @@ class Inferencer(Runner):
 
             pred_pose[:3,:3] = PoseUtil.rotation_6d_to_matrix_tensor_batch(pred_pose_9d[:,:6])[0]
             pred_pose[:3,3] = pred_pose_9d[0,6:]
+            # ----- Debug -----
             
+            from utils.vis import visualizeUtil
+            import ipdb; ipdb.set_trace()
+            all_directions = []
+            np.savetxt("input_pts.txt", input_data["combined_scanned_pts"].cpu().numpy()[0])
+            for i in range(50):
+                output = self.pipeline(input_data)
+                pred_pose_9d = output["pred_pose_9d"]
+                cam_pos, sample_points = visualizeUtil.get_cam_pose_and_cam_axis(pred_pose_9d.cpu().numpy()[0], is_6d_pose=True)
+                all_directions.append(sample_points)
+            all_directions = np.array(all_directions)
+            reshape_all_directions = all_directions.reshape(-1, 3)
+            np.savetxt("all_directions.txt", reshape_all_directions)
+            # ----- ----- -----
             try:
                 new_target_pts, new_target_normals, new_scan_points_indices = RenderUtil.render_pts(pred_pose, scene_path, self.script_path, scan_points, voxel_threshold=voxel_threshold, filter_degree=filter_degree, nO_to_nL_pose=O_to_L_pose)
                 #import ipdb; ipdb.set_trace()
@@ -157,11 +171,11 @@ class Inferencer(Runner):
 
                 downsampled_new_target_pts = PtsUtil.voxel_downsample_point_cloud(new_target_pts, voxel_threshold)
                 overlap, _ = ReconstructionUtil.check_overlap(downsampled_new_target_pts, voxel_downsampled_combined_scanned_pts_np, overlap_area_threshold = curr_overlap_area_threshold, voxel_size=voxel_threshold, require_new_added_pts_num = True)
-                if not overlap:
+                # if not overlap:
-                    Log.yellow("no overlap!")
+                #     Log.yellow("no overlap!")
-                    retry += 1
+                #     retry += 1
-                    retry_overlap_pose.append(pred_pose.cpu().numpy().tolist())
+                #     retry_overlap_pose.append(pred_pose.cpu().numpy().tolist())
-                    continue
+                #     continue
                 
                 history_indices.append(new_scan_points_indices)
             except Exception as e:

utils/render.py

@@ -84,10 +84,12 @@ class RenderUtil:
             params_data_path = os.path.join(temp_dir, "params.json")
             with open(params_data_path, 'w') as f:
                 json.dump(params, f)
+            #import ipdb; ipdb.set_trace()
             result = subprocess.run([
                 '/home/hofee/blender-4.0.2-linux-x64/blender', '-b', '-P', script_path, '--', temp_dir
             ], capture_output=True, text=True)
             #print(result)
+            #import ipdb; ipdb.set_trace()
             path = os.path.join(temp_dir, "tmp")
             cam_info = DataLoadUtil.load_cam_info(path, binocular=True)
             depth_L, depth_R = DataLoadUtil.load_depth(

utils/vis.py

@@ -7,6 +7,7 @@ import trimesh
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 from utils.data_load import DataLoadUtil
 from utils.pts import PtsUtil
+from utils.pose import PoseUtil
 
 class visualizeUtil:
     
@@ -34,6 +35,21 @@ class visualizeUtil:
         np.savetxt(os.path.join(output_dir, "all_cam_pos.txt"), all_cam_pos)
         np.savetxt(os.path.join(output_dir, "all_cam_axis.txt"), all_cam_axis)
     
+    @staticmethod
+    def get_cam_pose_and_cam_axis(cam_pose, is_6d_pose):
+        if is_6d_pose:
+            matrix_cam_pose = np.eye(4)
+            matrix_cam_pose[:3,:3] = PoseUtil.rotation_6d_to_matrix_numpy(cam_pose[:6])
+            matrix_cam_pose[:3, 3] = cam_pose[6:]
+        else:
+            matrix_cam_pose = cam_pose
+        cam_pos = matrix_cam_pose[:3, 3]
+        cam_axis = matrix_cam_pose[:3, 2]
+        num_samples = 10
+        sample_points = [cam_pos + 0.02*t * cam_axis for t in range(num_samples)]
+        sample_points = np.array(sample_points)
+        return cam_pos, sample_points
+    
     @staticmethod
     def save_all_combined_pts(root, scene, output_dir):
         length = DataLoadUtil.get_scene_seq_length(root, scene)