test datasets thing class

backend.py

@@ -1,5 +1,5 @@
 """
-tree-segmentation
+aerial-segmentation
 Proof of concept showing effectiveness of a fine tuned instance segmentation model for detecting trees.
 """
 import os
@@ -12,6 +12,7 @@ import numpy as np
 import torch
 import torchvision
 import detectron2
+import json
 
 # import some common detectron2 utilities
 import itertools
@@ -96,6 +97,12 @@ def visualize_image(im, mode, tree_threshold:float, building_threshold:float, co
     metadata = MetadataCatalog.get("urban-small_train")
     category_names = metadata.get("thing_classes")
     print(category_names)
+    with open("building_model_weight/_annotations.coco.json", "r") as f:
+        coco = json.load(f)
+        categories = coco["categories"]
+    print("categories", categories)
+    metadata.thing_classes = [c["name"] for c in categories]
+    print("metadata.thing_classes", metadata.thing_classes )
     # visualizer = Visualizer(im[:, :, ::-1],
     #                         metadata=metadata,
     #                         scale=0.5,