refactor: Prune unused dependencies

notebook/demo_multi_object.ipynb

@@ -25,7 +25,6 @@
                 "import os\n",
                 "import uuid\n",
                 "import imageio\n",
-                "import numpy as np\n",
                 "from IPython.display import Image as ImageDisplay\n",
                 "\n",
                 "from inference import Inference, ready_gaussian_for_video_rendering, load_image, load_masks, display_image, make_scene, render_video, interactive_visualizer"

notebook/inference.py

@@ -5,7 +5,6 @@
 os.environ["CUDA_HOME"] = os.environ["CONDA_PREFIX"]
 os.environ["LIDRA_SKIP_INIT"] = "true"
 
-import sys
 from typing import Union, Optional, List, Callable
 import numpy as np
 from PIL import Image
@@ -17,13 +16,10 @@
 import shutil
 import subprocess
 import seaborn as sns
-from PIL import Image
 import numpy as np
 import gradio as gr
 import matplotlib.pyplot as plt
 from copy import deepcopy
-from kaolin.visualize import IpyTurntableVisualizer
-from kaolin.render.camera import Camera, CameraExtrinsics, PinholeIntrinsics
 import builtins
 from pytorch3d.transforms import quaternion_multiply, quaternion_invert
 

notebook/mesh_alignment.py

@@ -11,7 +11,6 @@
 import torch
 import trimesh
 from PIL import Image
-import torch.nn.functional as F
 from pytorch3d.structures import Meshes
 from pytorch3d.renderer import PerspectiveCameras, RasterizationSettings, MeshRasterizer, TexturesVertex
 from moge.model.v1 import MoGeModel

requirements.dev.txt

@@ -1,4 +1 @@
 pytest
-findpydeps
-pipdeptree
-lovely_tensors

requirements.inference.txt

@@ -1,4 +1,3 @@
-kaolin==0.17.0
 gsplat @ git+https://github.com/nerfstudio-project/gsplat.git@2323de5905d5e90e035f792fe65bad0fedd413e7
 seaborn==0.13.2
 gradio==5.49.0

requirements.txt

@@ -1,88 +1,19 @@
-astor==0.8.1
-async-timeout==4.0.3
-auto_gptq==0.7.1
-autoflake==2.3.1
-av==12.0.0
-bitsandbytes==0.43.0
-black==24.3.0
-bpy==4.3.0
-colorama==0.4.6
-conda-pack==0.7.1
-crcmod==1.7
-cuda-python==12.1.0
-dataclasses==0.6
-decord==0.6.0
-deprecation==2.1.0
 easydict==1.13
 einops-exts==0.0.4
-exceptiongroup==1.2.0
-fastavro==1.9.4
-fasteners==0.19
-flake8==7.0.0
-Flask==3.0.3
-fqdn==1.5.1
-ftfy==6.2.0
-fvcore==0.1.5.post20221221
-gdown==5.2.0
-h5py==3.12.1
-hdfs==2.7.3
-httplib2==0.22.0
 hydra-core==1.3.2
 hydra-submitit-launcher==1.2.0
 igraph==0.11.8
-imath==0.0.2
-isoduration==20.11.0
-jsonlines==4.0.0
-jsonpickle==3.0.4
-jsonpointer==2.4
-jupyter==1.1.1
-librosa==0.10.1
 lightning==2.3.3
 loguru==0.7.2
-mosaicml-streaming==0.7.5
 nvidia-cuda-nvcc-cu12==12.1.105
-nvidia-pyindex==1.0.9
-objsize==0.7.0
 open3d==0.18.0
 opencv-python==4.9.0.80
-OpenEXR==3.3.3
-optimum==1.18.1
 optree==0.14.1
-orjson==3.10.0
-panda3d-gltf==1.2.1
-pdoc3==0.10.0
-peft==0.10.0
-pip-system-certs==4.0
-point-cloud-utils==0.29.5
-polyscope==2.3.0
-pycocotools==2.0.7
-pydot==1.4.2
 pymeshfix==0.17.0
-pymongo==4.6.3
-pyrender==0.1.45
-PySocks==1.7.1
-pytest==8.1.1
-python-pycg==0.9.2
-randomname==0.2.1
-roma==1.5.1
-rootutils==1.0.7
-Rtree==1.3.0
-sagemaker==2.242.0
 scikit-image==0.23.1
-sentence-transformers==2.6.1
-simplejson==3.19.2
-smplx==0.1.28
 spconv-cu121==2.3.8
 tensorboard==2.16.2
 timm==0.9.16
-tomli==2.0.1
-torchaudio==2.5.1+cu121
-uri-template==1.3.0
-usort==1.0.8.post1
-wandb==0.20.0
-webcolors==1.13
-webdataset==0.2.86
-Werkzeug==3.0.6
 xatlas==0.0.9
 xformers==0.0.28.post3
 MoGe @ git+https://github.com/microsoft/MoGe.git@a8c37341bc0325ca99b9d57981cc3bb2bd3e255b

sam3d_objects/data/utils.py

@@ -5,7 +5,6 @@
 from collections.abc import Iterable
 import inspect
 import ast
-import astor
 from torch.utils import _pytree
 
 # None = root, Iterable[Any] = path, Any = path of one
@@ -215,7 +214,7 @@ def _get_caller_arg_name(argnum=0, parent_frame=1):
                 break  # only get the first parent call
 
         # get first argument string (do not handle '=')
-        label = astor.to_source(args[argnum]).strip()
+        label = ast.unparse(args[argnum]).strip()
     except:
         # TODO(Pierre) log exception
         label = "{label}"

sam3d_objects/model/backbone/tdfy_dit/representations/mesh/flexicubes/flexicubes.py

@@ -15,7 +15,6 @@
 # limitations under the License.
 import torch
 from .tables import *
-from kaolin.utils.testing import check_tensor
 
 __all__ = [
     'FlexiCubes'
@@ -56,29 +55,18 @@ def __init__(self, device="cuda"):
 
     def __call__(self, voxelgrid_vertices, scalar_field, cube_idx, resolution, qef_reg_scale=1e-3,
                  weight_scale=0.99, beta=None, alpha=None, gamma_f=None, voxelgrid_colors=None, training=False):
-        assert torch.is_tensor(voxelgrid_vertices) and \
-            check_tensor(voxelgrid_vertices, (None, 3), throw=False), \
-            "'voxelgrid_vertices' should be a tensor of shape (num_vertices, 3)"
-        num_vertices = voxelgrid_vertices.shape[0]
-        assert torch.is_tensor(scalar_field) and \
-            check_tensor(scalar_field, (num_vertices,), throw=False), \
-            "'scalar_field' should be a tensor of shape (num_vertices,)"
-        assert torch.is_tensor(cube_idx) and \
-            check_tensor(cube_idx, (None, 8), throw=False), \
-            "'cube_idx' should be a tensor of shape (num_cubes, 8)"
+        assert voxelgrid_vertices.ndim == 2 and voxelgrid_vertices.shape[1] == 3, "voxelgrid_vertices must be (N, 3)"
+        assert scalar_field.shape == (voxelgrid_vertices.shape[0],), "scalar_field must be (N,)"
+
+        assert cube_idx.ndim == 2 and cube_idx.shape[1] == 8, "cube_idx must be (M, 8)"
         num_cubes = cube_idx.shape[0]
-        assert beta is None or (
-            torch.is_tensor(beta) and
-            check_tensor(beta, (num_cubes, 12), throw=False)
-        ), "'beta' should be a tensor of shape (num_cubes, 12)"
-        assert alpha is None or (
-            torch.is_tensor(alpha) and
-            check_tensor(alpha, (num_cubes, 8), throw=False)
-        ), "'alpha' should be a tensor of shape (num_cubes, 8)"
-        assert gamma_f is None or (
-            torch.is_tensor(gamma_f) and
-            check_tensor(gamma_f, (num_cubes,), throw=False)
-        ), "'gamma_f' should be a tensor of shape (num_cubes,)"
+
+        if beta is not None:
+            assert beta.shape == (num_cubes, 12), "beta must be (M, 12)"
+        if alpha is not None:
+            assert alpha.shape == (num_cubes, 8), "alpha must be (M, 8)"
+        if gamma_f is not None:
+            assert gamma_f.shape == (num_cubes,), "gamma_f must be (M,)"
 
         surf_cubes, occ_fx8 = self._identify_surf_cubes(scalar_field, cube_idx)
         if surf_cubes.sum() == 0: