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{
"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": []
}
],
"metadata": {
"kernelspec": {
"display_name": "llava",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.14"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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