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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multi-view reconstruction and Meshing\n",
    "\n",
    "## 0. Import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import cv2\n",
    "\n",
    "import openalea.phenomenal.data as phm_data\n",
    "import openalea.phenomenal.display as phm_display\n",
    "import openalea.phenomenal.object as phm_obj\n",
    "import openalea.phenomenal.multi_view_reconstruction as phm_mvr\n",
    "import openalea.phenomenal.mesh as phm_mesh\n",
    "import openalea.phenomenal.display.notebook as phm_display_notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Prerequisites\n",
    "\n",
    "### 1.1 Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plant_number = 2  # Available : 1, 2, 3, 4 or 5\n",
    "bin_images = phm_data.bin_images(f\"data/plant_{plant_number}\")\n",
    "calibrations = phm_data.calibrations(f\"data/plant_{plant_number}\")\n",
    "\n",
    "phm_display.show_images(\n",
    "    list(bin_images[\"side\"].values()) + list(bin_images[\"top\"].values())\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Multi-view reconstruction\n",
    "\n",
    "### 2.1 Associate images and projection function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def routine_select_ref_angle(bin_side_images):\n",
    "    max_len = 0\n",
    "    max_angle = None\n",
    "\n",
    "    for angle in bin_side_images:\n",
    "        x_pos, y_pos, x_len, y_len = cv2.boundingRect(\n",
    "            cv2.findNonZero(bin_side_images[angle])\n",
    "        )\n",
    "\n",
    "        if x_len > max_len:\n",
    "            max_len = x_len\n",
    "            max_angle = angle\n",
    "\n",
    "    return max_angle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "refs_angle_list = [routine_select_ref_angle(bin_images[\"side\"])]\n",
    "print(refs_angle_list)\n",
    "\n",
    "image_views = list()\n",
    "for id_camera in bin_images:\n",
    "    for angle in bin_images[id_camera]:\n",
    "        projection = calibrations[id_camera].get_projection(angle)\n",
    "\n",
    "        image_ref = None\n",
    "        if id_camera == \"side\" and angle in refs_angle_list:\n",
    "            image_ref = bin_images[id_camera][angle]\n",
    "\n",
    "        inclusive = False\n",
    "        if id_camera == \"top\":\n",
    "            inclusive = True\n",
    "\n",
    "        image_views.append(\n",
    "            phm_obj.ImageView(\n",
    "                bin_images[id_camera][angle],\n",
    "                projection,\n",
    "                inclusive=inclusive,\n",
    "                image_ref=image_ref,\n",
    "            )\n",
    "        )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Do multi-view reconstruction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "voxels_size = 16  # mm\n",
    "error_tolerance = 0\n",
    "voxel_grid = phm_mvr.reconstruction_3d(\n",
    "    image_views, voxels_size=voxels_size, error_tolerance=error_tolerance\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.4 Save / Load voxel grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "voxel_grid.write(f\"plant_{plant_number}_size_{voxels_size}.npz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "voxel_grid = phm_obj.VoxelGrid.read(f\"plant_{plant_number}_size_{voxels_size}.npz\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.5 Viewing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "phm_display_notebook.show_voxel_grid(voxel_grid, size=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.Meshing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vertices, faces = phm_mesh.meshing(\n",
    "    voxel_grid.to_image_3d(), reduction=0.90, smoothing_iteration=5, verbose=True\n",
    ")\n",
    "\n",
    "print(\"Number of vertices : {nb_vertices}\".format(nb_vertices=len(vertices)))\n",
    "print(\"Number of faces : {nb_faces}\".format(nb_faces=len(faces)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Viewing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "phm_display_notebook.show_mesh(vertices, faces)"
   ]
  }
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