Merge branch 'master' of github.com:changhaonan/LGMCTS-D

changhaonan · Sep 13, 2023 · f9374bd · f9374bd
2 parents 29b6d4d + 12e5be3
commit f9374bd
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Showing 4 changed files with 274 additions and 98 deletions.
diff --git a/.vscode/launch.json b/.vscode/launch.json
@@ -63,6 +63,20 @@
             "console": "integratedTerminal",
             "justMyCode": false
         },
+        {
+            "name": "Eval online SFormer",
+            "type": "python",
+            "request": "launch",
+            "program": "${workspaceFolder}/lgmcts/scripts/eval/eval_lgmcts_struct.py",
+            "args": [
+                "--method=mcts",
+                "--n_epoches=1",
+                "--mask_mode=raw_mask",
+                "--debug",
+            ],
+            "console": "integratedTerminal",
+            "justMyCode": false
+        },
         {
             "name": "Eval online (Debug)",
             "type": "python",

diff --git a/lgmcts/algorithm/region_sampler.py b/lgmcts/algorithm/region_sampler.py
@@ -511,7 +511,7 @@ def visualize(self, **kwargs):
         cv2.waitKey(0)
         cv2.destroyAllWindows()
 
-    def visualize_3d(self, show_origin: bool = False):
+    def visualize_3d(self, show_origin: bool = False, obj_center = None):
         """Visualize the region and obj bbox in 3D"""
         vis_list = []
         if self.scene_pcd is not None:
@@ -537,6 +537,8 @@ def visualize_3d(self, show_origin: bool = False):
             region2world = np.linalg.inv(self.world2region)
             region_origin = o3d.geometry.TriangleMesh.create_coordinate_frame(size=1.0)
             region_origin.transform(region2world)
+            # vis_list.append(region_origin)
+            # region_origin.translate(obj_center.tolist())
             vis_list.append(region_origin)
         o3d.visualization.draw_geometries(vis_list)
 

diff --git a/lgmcts/scripts/eval/eval_lgmcts_real.py b/lgmcts/scripts/eval/eval_lgmcts_real.py
@@ -25,7 +25,7 @@ def eval_real(data_path: str, prompt_path: str, method: str, mask_mode: str, n_s
                                   [0.,  634.80944824, 368.45831299],
                                   [0.,    0.,   1.]])
     label = json.load(open(os.path.join(data_path, "label.json"), "r"))
-    # load images
+    # load images000
     depth_scale = 100000.0
     mask = cv2.imread(os.path.join(data_path, "mask_image.png"))
     depth = cv2.imread(os.path.join(data_path, "depth_image.png"),