{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import trimesh\n",
    "import numpy as np\n",
    "import trimesh.transformations as tf\n",
    "\n",
    "# adjust bright factor to increase or decrease the brightness of the colors\n",
    "def convert_ply_to_format(ply_file, output_file, bright_factor=1.5):\n",
    "    # Load the PLY file\n",
    "    mesh = trimesh.load(ply_file)\n",
    "\n",
    "    # Define the rotation matrix to swap y and z axes\n",
    "    angle = -np.pi / 2  # 90 degrees\n",
    "    axis = [1, 0, 0]  # Rotate around x-axis\n",
    "    R = tf.rotation_matrix(angle, axis)\n",
    "\n",
    "    # Apply the rotation to the mesh\n",
    "    mesh.apply_transform(R)\n",
    "    \n",
    "    # Adjust the brightness of vertex colors if they exist\n",
    "    if mesh.visual.kind == 'vertex' and mesh.visual.vertex_colors is not None:\n",
    "        vertex_colors = np.asarray(mesh.visual.vertex_colors)[:, :3]  # Ignore alpha channel if present\n",
    "        brightened_colors = np.clip(vertex_colors * bright_factor, 0, 255).astype(np.uint8)\n",
    "        mesh.visual.vertex_colors = brightened_colors\n",
    "\n",
    "    # Export the mesh to the specified format\n",
    "    mesh.export(output_file)\n",
    "    print(f\"Converted {ply_file} to {output_file}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Converted /nfs/turbo/coe-chaijy-unreplicated/datasets/ScanNet/raw_uncompressed/scans/scene0643_00/scene0643_00_vh_clean_2_centered.ply to /home/jianingy/research/LLaVA-original/3d_grand_demo/data/scene0643_00/scene0643_00.obj\n"
     ]
    }
   ],
   "source": [
    "ply_file_path = '/nfs/turbo/coe-chaijy-unreplicated/datasets/ScanNet/raw_uncompressed/scans/scene0643_00/scene0643_00_vh_clean_2_centered.ply'\n",
    "obj_file_path = '/home/jianingy/research/LLaVA-original/3d_grand_demo/data/scene0643_00/scene0643_00.obj'\n",
    "\n",
    "convert_ply_to_format(ply_file_path, obj_file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Converted /nfs/turbo/coe-chaijy-unreplicated/datasets/ScanNet/raw_uncompressed/scans/scene0025_00/scene0025_00_vh_clean_2_centered.ply to /home/jianingy/research/LLaVA-original/3d_grand_demo/data/scene0025_00/scene0025_00.obj\n"
     ]
    }
   ],
   "source": [
    "scene_id = 'scene0025_00'\n",
    "ply_file_path = f'/nfs/turbo/coe-chaijy-unreplicated/datasets/ScanNet/raw_uncompressed/scans/{scene_id}/{scene_id}_vh_clean_2_centered.ply'\n",
    "obj_file_path = f'/home/jianingy/research/LLaVA-original/3d_grand_demo/data/{scene_id}/{scene_id}.obj'\n",
    "\n",
    "convert_ply_to_format(ply_file_path, obj_file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Converted /nfs/turbo/coe-chaijy-unreplicated/datasets/ScanNet/raw_uncompressed/scans/scene0426_00/scene0426_00_vh_clean_2_centered.ply to /home/jianingy/research/LLaVA-original/3d_grand_demo/data/scene0426_00/scene0426_00.obj\n"
     ]
    }
   ],
   "source": [
    "scene_id = 'scene0426_00'\n",
    "ply_file_path = f'/nfs/turbo/coe-chaijy-unreplicated/datasets/ScanNet/raw_uncompressed/scans/{scene_id}/{scene_id}_vh_clean_2_centered.ply'\n",
    "obj_file_path = f'/home/jianingy/research/LLaVA-original/3d_grand_demo/data/{scene_id}/{scene_id}.obj'\n",
    "\n",
    "convert_ply_to_format(ply_file_path, obj_file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "llava",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
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