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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# SAM 3D Body (3DB) Mesh Alignment to SAM 3D Object Scale\n",
"\n",
"This notebook processes a single 3DB mesh and aligns it to the SAM 3D Objects scale.\n",
"\n",
"**Input Data:**\n",
"- `images/human_object/image.jpg` - Input image for MoGe\n",
"- `meshes/human_object/3DB_results/mask_human.png` - Human mask\n",
"- `meshes/human_object/3DB_results/human.ply` - Single 3DB mesh in OpenGL coordinates\n",
"- `meshes/human_object/3DB_results/focal_length.json` - 3DB focal length\n",
"\n",
"**Output:**\n",
"- `meshes/human_object/aligned_meshes/human_aligned.ply` - Aligned 3DB mesh in OpenGL coordinates"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import torch\n",
"import matplotlib.pyplot as plt\n",
"from PIL import Image\n",
"from mesh_alignment import process_and_save_alignment\n",
"\n",
"device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
"print(f\"Using device: {device}\")\n",
"PATH = os.getcwd()\n",
"print(f\"Current working directory: {PATH}\")\n",
"\n",
"# Please inference the SAM 3D Body (3DB) Repo (https://github.com/facebookresearch/sam-3d-body) to get the 3DB Results\n",
"image_path = f\"{PATH}/images/human_object/image.png\"\n",
"mask_path = f\"{PATH}/meshes/human_object/3DB_results/mask_human.png\"\n",
"mesh_path = f\"{PATH}/meshes/human_object/3DB_results/human.ply\"\n",
"focal_length_json_path = f\"{PATH}/meshes/human_object/3DB_results/focal_length.json\"\n",
"output_dir = f\"{PATH}/meshes/human_object/aligned_meshes\"\n",
"os.makedirs(output_dir, exist_ok=True)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Load and Display Input Data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"input_image = Image.open(image_path)\n",
"mask = Image.open(mask_path).convert('L')\n",
"fig, axes = plt.subplots(1, 2, figsize=(10, 5))\n",
"axes[0].imshow(input_image)\n",
"axes[0].set_title('Input Image')\n",
"axes[0].axis('off')\n",
"axes[1].imshow(mask, cmap='gray')\n",
"axes[1].set_title('Mask')\n",
"axes[1].axis('off')\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Process and Save Aligned Mesh"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"success, output_mesh_path, result = process_and_save_alignment(\n",
" mesh_path=mesh_path,\n",
" mask_path=mask_path,\n",
" image_path=image_path,\n",
" output_dir=output_dir,\n",
" device=device,\n",
" focal_length_json_path=focal_length_json_path\n",
")\n",
"\n",
"if success:\n",
" print(f\"Alignment completed successfully! Output: {output_mesh_path}\")\n",
"else:\n",
" print(\"Alignment failed!\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Interactive 3D Visualization\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from mesh_alignment import visualize_meshes_interactive\n",
"\n",
"aligned_mesh_path = f\"{PATH}/meshes/human_object/aligned_meshes/human_aligned.ply\"\n",
"dfy_mesh_path = f\"{PATH}/meshes/human_object/3Dfy_results/0.glb\"\n",
"\n",
"demo, combined_glb_path = visualize_meshes_interactive(\n",
" aligned_mesh_path=aligned_mesh_path,\n",
" dfy_mesh_path=dfy_mesh_path,\n",
" share=True\n",
")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "sam3d_objects-3dfy",
"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": "3.11.0"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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