Visualize a 3d cloud of points from a file and then click on a 2D image projection of those points with visualizing the clicks using text in Matplotlib and Jupyter

create_6_points_file.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Installation requirements:\n",
    "\n",
    "# !conda create -n myptv -y\n",
    "# !conda activate myptv\n",
    "# !pip install git+https://github.com/alexlib/myptv\n",
    "# !pip install ipympl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import * # recommended only for short interactive sessions\n",
    "%matplotlib tk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot the target file in 3D\n",
    "# zoom in with the Right button rolling\n",
    "# rotate with the left button\n",
    "# pan with the middle button\n",
    "\n",
    "fig = figure(figsize=(10,10))\n",
    "# ax = axes(projection='3d')\n",
    "ax = fig.add_subplot(1, 1, 1, projection='3d')\n",
    "targets = loadtxt('./Calibration/target_file.csv')\n",
    "ax.plot(targets[:,0], targets[:,2], targets[:,1], 'ro')\n",
    "for counter, row in enumerate(targets):\n",
    "    ax.text(row[0], row[2], row[1], str(counter) );\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# looking at the both plots, decide which points you want to pick\n",
    "# type here the order of the points you want to click \n",
    "\n",
    "points = [436, 22, 0, 414, 207, 229]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.text as mpl_text\n",
    "\n",
    "im = imread('Calibration/cal1.tif')\n",
    "fig,ax = subplots(figsize = (im.shape[1]/300, im.shape[0]/300))\n",
    "ax.imshow(im, cmap='gray')\n",
    "ax.axis('off')\n",
    "clicks = []\n",
    "\n",
    "\n",
    "def onclick(event):\n",
    "\n",
    "    # tx = 'button=%d, x=%d, y=%d, xdata=%f, ydata=%f' % (event.button, event.x, event.y, event.xdata, event.ydata)\n",
    "    # text.set_text(tx)\n",
    "    counter = len(clicks)\n",
    "    print('%s click: button=%d, x=%d, y=%d, xdata=%f, ydata=%f' %\n",
    "          ('double' if event.dblclick else 'single', event.button,\n",
    "           event.x, event.y, event.xdata, event.ydata))\n",
    "    ax.text(event.xdata, event.ydata, str(points[counter]),fontsize=20,color='w')\n",
    "    plt.draw_if_interactive()    \n",
    "    clicks.append([event.xdata, event.ydata, *targets[points[counter]-1,1:]])\n",
    "    print(f'counter = {counter}')\n",
    "\n",
    "    \n",
    "\n",
    "cid = fig.canvas.mpl_connect('button_press_event', onclick)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace tmp.txt with the file name from the YAML\n",
    "\n",
    "savetxt('tmp.txt',array(clicks))\n"
   ]
  }
 ],
 "metadata": {
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  "kernelspec": {
   "display_name": "Python 3.9.12 ('myptv')",
   "language": "python",
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  "language_info": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "pygments_lexer": "ipython3",
   "version": "3.9.12"
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 "nbformat_minor": 2
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