Update activation function in RgbMlp class to use tanh for improved output range

inference.py

@@ -101,6 +101,6 @@ def generate3d(model, rgb, ccm, device):
     elapsed_time = end_time - start_time
     print(f"uv takes {elapsed_time}s")
 
-    print("Raw color min/max/mean:", colors.min(), colors.max(), colors.mean())
-    print("Scaled color min/max/mean:", colors.min(), colors.max(), colors.mean())
+    # print("Raw color min/max/mean:", colors.min(), colors.max(), colors.mean())
+    # print("Scaled color min/max/mean:", colors.min(), colors.max(), colors.mean())
     return mesh_path_glb+".obj"

model/archs/mlp_head.py

@@ -1,5 +1,6 @@
 import torch.nn as nn
 import torch.nn.functional as F
+import torch
 
 
 class SdfMlp(nn.Module):
@@ -34,7 +35,7 @@ class RgbMlp(nn.Module):
         x = F.relu(self.fc1(input))
         x = F.relu(self.fc2(x))
         out = self.fc3(x)
-
+        out = torch.tanh(out)
         return out