Update app.py

app.py

@@ -2,7 +2,8 @@ import gradio as gr
 import torch
 import random
 import numpy as np
-from transformers import MaskFormerFeatureExtractor, MaskFormerForInstanceSegmentation
+from scipy.spatial import Delaunay
+from transformers import MaskFormerFeatureExtractor, MaskFormerForInstanceSegmentation\
 
 device = torch.device("cpu")
 model = MaskFormerForInstanceSegmentation.from_pretrained("facebook/maskformer-swin-tiny-ade").to(device)
@@ -36,12 +37,15 @@ def visualize_instance_seg_mask(mask):
             image[i, j, :] = label2color[mask[i, j]]
 
     window_vertices = np.array([[x, 0, -y] for x, y in window])
+        # Perform Delaunay triangulation
+    tri = Delaunay(vertices[:, :2])  # Triangulate only based on x and y coordinates
+    
+    # Extract indices
+    indices = tri.simplices
 
-    # Define indices for triangles (assuming triangle faces)
-    window_indices = np.array([0, 1, 2], dtype=np.uint32)  # Example indices for window triangle
+    print(window_vertices)
+    print(indices)
     
-    # Concatenate vertices and indices
-    vertices = np.concatenate((window_vertices, floor_vertices))
     print(vertices)
     image = image / 255
     return image