requirements update for HF

.gitignore

@@ -166,3 +166,5 @@ cython_debug/
 /__pycache__
 /temp_models
 /.vscode/settings.json
+**/*.pyc
+**/__pycache__/

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 import os
-
+import spaces
 import numpy as np
 os.environ['SPCONV_ALGO'] = 'native'
 from typing import *
@@ -100,7 +100,7 @@ from utils.version_info import (
     #release_torch_resources,
     #get_torch_info
 )
-import spaces
+
 
 input_image_palette = []
 current_prerendered_image = gr.State("./images/images/Beeuty-1.png")
@@ -718,6 +718,28 @@ def generate_3d_asset(depth_image_source, randomize_seed, seed, input_image, out
             "cfg_strength": 3.0,
         },
     )
+
+    # Validate the mesh
+    mesh = outputs['mesh'][0]
+    # Depending on the mesh format (it might be a dict or an object)
+    if isinstance(mesh, dict):
+        vertices = mesh['vertices']
+        faces = mesh['faces']
+    else:
+        vertices = mesh.vertices
+        faces = mesh.faces
+
+    # Check mesh properties
+    print(f"Mesh vertices: {vertices.shape}, faces: {faces.shape}")
+    if faces.max() >= vertices.shape[0]:
+        raise ValueError(f"Invalid mesh: face index {faces.max()} exceeds vertex count {vertices.shape[0]}")
+
+    # Ensure data is on GPU and has correct type
+    if not vertices.is_cuda or not faces.is_cuda:
+        raise ValueError("Mesh data must be on GPU")
+    if vertices.dtype != torch.float32 or faces.dtype != torch.int32:
+        raise ValueError("Mesh vertices must be float32, faces must be int32")
+
     # Save the video to a temporary file
     user_dir = os.path.join(constants.TMPDIR, str(req.session_hash))
     os.makedirs(user_dir, exist_ok=True)
@@ -725,7 +747,7 @@ def generate_3d_asset(depth_image_source, randomize_seed, seed, input_image, out
     video = render_utils.render_video(outputs['gaussian'][0], resolution=576, num_frames=60, r=1)['color']
     snapshot_results = render_utils.render_snapshot(outputs['gaussian'][0], resolution=576)
     depth_snapshot = snapshot_results['depth'][0]
-    video_geo = render_utils.render_video(outputs['mesh'][0], resolution=576, num_frames=30, r=1)['normal']
+    video_geo = render_utils.render_video(outputs['mesh'][0], resolution=576, num_frames=60, r=1)['normal']
     video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
     video_path = os.path.join(user_dir, f'{output_name}.mp4')
     imageio.mimsave(video_path, video, fps=15)

requirements.txt

@@ -17,9 +17,9 @@ sentencepiece
 
 #generic Torch versions
 --extra-index-url https://download.pytorch.org/whl/cu124
-torch==2.6.0
+torch
 torchvision
-#xformers #==0.0.29.post3
+xformers #==0.0.29.post3
 
 # Other dependencies
 Haishoku
@@ -68,9 +68,9 @@ git+https://github.com/EasternJournalist/utils3d.git@9a4eb15e4021b67b12c460c7057
 spconv-cu124==2.3.8
 gradio_litmodel3d==0.0.1
 #linux only
-#https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.0.post2/flash_attn-2.7.0.post2+cu12torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
-#https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
-#https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/nvdiffrast-0.3.3-cp310-cp310-linux_x86_64.whl?download=true
+https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.3/flash_attn-2.7.3+cu12torch2.6cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
+https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
+https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/nvdiffrast-0.3.3-cp310-cp310-linux_x86_64.whl?download=true
 #Windows only
 #https://huggingface.co/spaces/Surn/HexaGrid/main/wheels/flash_attn-2.7.4.post1-cp312-cp312-win_amd64.whl?download=true
 #https://huggingface.co/spaces/Surn/HexaGrid/main/wheels/diff_gaussian_rasterization-0.0.0-cp312-cp312-win_amd64.whl?download=true