Remove pytorch3d

app.py

@@ -5,8 +5,7 @@ import clip
 import gradio as gr
 from gradio_rerun import Rerun
 import numpy as np
-from pytorch3d.renderer import TexturesVertex
-from pytorch3d.structures import Meshes
+import trimesh
 import rerun as rr
 import torch
 
@@ -79,13 +78,13 @@ def get_normals(vertices: torch.Tensor, faces: torch.Tensor) -> torch.Tensor:
     num_frames, num_faces = vertices.shape[0], faces.shape[-2]
     faces = faces.expand(num_frames, num_faces, 3)
 
-    verts_rgb = torch.ones_like(vertices)
-    verts_rgb[:, :, 1] = 0
-    textures = TexturesVertex(verts_features=verts_rgb)
-    meshes = Meshes(verts=vertices, faces=faces, textures=textures)
-    normals = meshes.verts_normals_padded()
+    normals = [
+        trimesh.Trimesh(vertices=v, faces=f, process=False).vertex_normals
+        for v, f in zip(vertices, faces)
+    ]
+    normals = torch.from_numpy(np.stack(normals))
 
-    return normals, meshes
+    return normals
 
 
 def generate(
@@ -118,7 +117,7 @@ def generate(
     padded_vertices = out["char_raw"]["char_vertices"][0]
     vertices = padded_vertices[padding_mask]
     faces = out["char_raw"]["char_faces"][0]
-    normals, meshes = get_normals(vertices, faces)
+    normals = get_normals(vertices, faces)
     fx, fy, cx, cy = out["intrinsics"][0].cpu().numpy()
     K = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]])
     caption = out["caption_raw"][0]

requirements.txt

@@ -9,8 +9,8 @@ scikit-learn
 fvcore
 iopath
 ema_pytorch
-ftfy 
-regex 
+ftfy
+regex
 tqdm
-git+https://github.com/openai/CLIP.git
-git+https://github.com/facebookresearch/pytorch3d.git
+trimesh
+git+https://github.com/openai/CLIP.git