From 04bfaa8efa6d908db7f03f60dd7fe9450c5ba432 Mon Sep 17 00:00:00 2001 From: Alex Liberzon Date: Thu, 29 Feb 2024 22:51:31 +0200 Subject: [PATCH 1/3] Create test_calibration_optimize.ipynb --- tests/test_calibration_optimize.ipynb | 159 ++++++++++++++++++++++++++ 1 file changed, 159 insertions(+) create mode 100644 tests/test_calibration_optimize.ipynb diff --git a/tests/test_calibration_optimize.ipynb b/tests/test_calibration_optimize.ipynb new file mode 100644 index 0000000..8d6bfb4 --- /dev/null +++ b/tests/test_calibration_optimize.ipynb @@ -0,0 +1,159 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# test calibration using scipy.optimize\n", + "\n", + "import numpy as np\n", + "import scipy.optimize as opt" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import unittest\n", + "\n", + "import numpy as np\n", + "\n", + "from openptv_python.calibration import (\n", + " Calibration,\n", + ")\n", + "from openptv_python.imgcoord import image_coordinates\n", + "from openptv_python.orientation import (\n", + " external_calibration,\n", + ")\n", + "from openptv_python.parameters import ControlPar, OrientPar, VolumePar, read_control_par\n", + "from openptv_python.tracking_frame_buf import TargetArray\n", + "from openptv_python.trafo import arr_metric_to_pixel" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "class TestGradientDescent(unittest.TestCase):\n", + " # Based on the C tests in liboptv/check_orientation.c\n", + "\n", + " def setUp(self):\n", + " control_file_name = \"testing_folder/corresp/control.par\"\n", + " # self.control = ControlPar(4)\n", + " self.control = read_control_par(control_file_name)\n", + "\n", + " self.orient_par_file_name = \"testing_folder/corresp/orient.par\"\n", + " self.orient_par = OrientPar().from_file(self.orient_par_file_name)\n", + "\n", + " self.cal = Calibration().from_file(\n", + " \"testing_folder/calibration/cam1.tif.ori\",\n", + " \"testing_folder/calibration/cam1.tif.addpar\",\n", + " )\n", + " self.orig_cal = Calibration().from_file(\n", + " \"testing_folder/calibration/cam1.tif.ori\",\n", + " \"testing_folder/calibration/cam1.tif.addpar\",\n", + " )\n", + "\n", + " \n", + " def test_external_calibration(self):\n", + " \"\"\"External calibration using clicked points.\"\"\"\n", + " ref_pts = np.array(\n", + " [\n", + " [-40.0, -25.0, 8.0],\n", + " [40.0, -15.0, 0.0],\n", + " [40.0, 15.0, 0.0],\n", + " [40.0, 0.0, 8.0],\n", + " ]\n", + " )\n", + "\n", + " # Fake the image points by back-projection\n", + " targets = arr_metric_to_pixel(\n", + " image_coordinates(ref_pts, self.cal, self.control.mm),\n", + " self.control,\n", + " )\n", + "\n", + " # Jigg the fake detections to give raw_orient some challenge.\n", + " targets[:, 1] -= 0.1\n", + "\n", + " self.assertTrue(external_calibration(self.cal, ref_pts, targets, self.control))\n", + " np.testing.assert_array_almost_equal(\n", + " self.cal.get_angles(), self.orig_cal.get_angles(), decimal=3\n", + " )\n", + " np.testing.assert_array_almost_equal(\n", + " self.cal.get_pos(), self.orig_cal.get_pos(), decimal=3\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "test_external_calibration (__main__.TestGradientDescent)\n", + "External calibration using clicked points. ... ok\n", + "\n", + "----------------------------------------------------------------------\n", + "Ran 1 test in 0.120s\n", + "\n", + "OK\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Coefficients (beta): [ 1.80534911e-04 -6.77499328e-05 -6.52416361e-04 -1.77426081e-05\n", + " -1.31470856e-07 4.02517087e-06]\n", + "Residuals: []\n", + "rank: 6\n", + "singular_values: None\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "unittest.main(argv=[''], verbosity=2, exit=False)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "openptvpy", + "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": "3.10.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From a3284471d41d587cd381ebd2e4ce8d057b22807a Mon Sep 17 00:00:00 2001 From: Alex Liberzon Date: Fri, 1 Mar 2024 00:19:29 +0200 Subject: [PATCH 2/3] Update test_calibration_optimize.ipynb --- tests/test_calibration_optimize.ipynb | 182 ++++++++++++++++++++++++-- 1 file changed, 170 insertions(+), 12 deletions(-) diff --git a/tests/test_calibration_optimize.ipynb b/tests/test_calibration_optimize.ipynb index 8d6bfb4..54c725e 100644 --- a/tests/test_calibration_optimize.ipynb +++ b/tests/test_calibration_optimize.ipynb @@ -2,25 +2,23 @@ "cells": [ { "cell_type": "code", - "execution_count": 5, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ - "# test calibration using scipy.optimize\n", - "\n", - "import numpy as np\n", - "import scipy.optimize as opt" + "# test calibration using scipy.optimize\n" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "import unittest\n", "\n", "import numpy as np\n", + "import scipy.optimize as opt\n", "\n", "from openptv_python.calibration import (\n", " Calibration,\n", @@ -31,12 +29,15 @@ ")\n", "from openptv_python.parameters import ControlPar, OrientPar, VolumePar, read_control_par\n", "from openptv_python.tracking_frame_buf import TargetArray\n", - "from openptv_python.trafo import arr_metric_to_pixel" + "from openptv_python.trafo import arr_metric_to_pixel\n", + "from openptv_python.imgcoord import img_coord\n", + "from openptv_python.trafo import pixel_to_metric\n", + "from openptv_python.tracking_frame_buf import Target\n" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -92,7 +93,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -103,7 +104,7 @@ "External calibration using clicked points. ... ok\n", "\n", "----------------------------------------------------------------------\n", - "Ran 1 test in 0.120s\n", + "Ran 1 test in 0.014s\n", "\n", "OK\n" ] @@ -122,10 +123,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -133,6 +134,163 @@ "source": [ "unittest.main(argv=[''], verbosity=2, exit=False)" ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "control_file_name = \"testing_folder/corresp/control.par\"\n", + "control = read_control_par(control_file_name)\n", + "\n", + "orient_par_file_name = \"testing_folder/corresp/orient.par\"\n", + "orient_par = OrientPar().from_file(orient_par_file_name)\n", + "\n", + "cal = Calibration().from_file(\n", + " \"testing_folder/calibration/cam1.tif.ori\",\n", + " \"testing_folder/calibration/cam1.tif.addpar\",\n", + ")\n", + "orig_cal = Calibration().from_file(\n", + " \"testing_folder/calibration/cam1.tif.ori\",\n", + " \"testing_folder/calibration/cam1.tif.addpar\")" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "ref_pts = np.array(\n", + " [\n", + " [-40.0, -25.0, 8.0],\n", + " [40.0, -15.0, 0.0],\n", + " [40.0, 15.0, 0.0],\n", + " [40.0, 0.0, 8.0],\n", + " ]\n", + ")\n", + "\n", + "# Fake the image points by back-projection\n", + "targets = arr_metric_to_pixel(\n", + " image_coordinates(ref_pts, cal, control.mm),\n", + " control,\n", + ")\n", + "\n", + "cal.set_pos(np.array([0, 0, 100]))\n", + "cal.set_angles(np.array([0, 0, 0]))\n", + "\n", + "# Jigg the fake detections to give raw_orient some challenge.\n", + "targets[:, 1] -= 0.1" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "targs = [Target() for _ in targets]\n", + "\n", + "for ptx, pt in enumerate(targets):\n", + " targs[ptx].x = pt[0]\n", + " targs[ptx].y = pt[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "\n", + "def residual(calibration_array, ref_pts, targs, control, cc):\n", + " # print(calibration_array)\n", + " # print(ref_pts)\n", + " # print(targs)\n", + " # print(control)\n", + " # print(calibration_array)\n", + " \n", + " c = Calibration()\n", + " c.set_pos(calibration_array[:3])\n", + " c.set_angles(calibration_array[3:])\n", + " c.int_par.cc = cc\n", + " c.update_rotation_matrix()\n", + " \n", + " \n", + " # print(f\"{c.get_pos()=}\")\n", + " \n", + " residual = 0\n", + " for i in range(len(targs)):\n", + " xc, yc = pixel_to_metric(targs[i].x, targs[i].y, control)\n", + " # print(f\"{xc=}, {yc=} mm\")\n", + " \n", + " xp, yp = img_coord(ref_pts[i], c, control.mm)\n", + " # print(f\"{xp=}, {yp=} mm\")\n", + " residual += ((xc - xp)**2 + (yc - yp)**2)\n", + " \n", + " # print(f\"{residual=}\")\n", + " \n", + " return residual" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "x0 = np.hstack([cal.get_pos(), cal.get_angles()])\n", + "cc = orig_cal.int_par.cc\n", + "\n", + "sol = opt.minimize(residual, x0, args=(ref_pts, targs, control, cc), method='Nelder-Mead', tol=1e-6)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sol.x=array([-3.79876331e+00, 3.77309709e+01, 4.03575316e+02, -8.61982784e-02,\n", + " -6.33837589e-02, 5.14334685e-02])\n", + "[-1.09061963e+02 -6.50148291e+01 -3.06884099e-01 1.52130822e-01\n", + " -3.07664759e-01 -3.82423146e-03]\n" + ] + } + ], + "source": [ + "print(f\"{sol.x=}\")\n", + "print(sol.x - np.hstack([orig_cal.get_pos(), orig_cal.get_angles()]))" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "93.58853214427855\n" + ] + } + ], + "source": [ + "print( residual(np.hstack([orig_cal.get_pos(), orig_cal.get_angles()]), ref_pts, targs, control, orig_cal.int_par.cc))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From d84374523f4d30203513e63be3a7d26ca8141aa8 Mon Sep 17 00:00:00 2001 From: Alex Liberzon Date: Sat, 2 Mar 2024 21:44:27 +0200 Subject: [PATCH 3/3] changed ap52, TargetArray and now we can compare optimization TargetArray is now list[Target] ap52_dtype is deprecated and we have just an array of [0,0,0,0,1,0] float64 - maybe this was the whole point? --- openptv_python/calibration.py | 50 +- openptv_python/orientation.py | 107 +- openptv_python/tracking_frame_buf.py | 38 +- openptv_python/trafo.py | 49 +- tests/test_calibration_optimize.ipynb | 6004 ++++++++++++++++++++++++- tests/test_orientation.py | 59 +- tests/test_read_targets.py | 5 +- 7 files changed, 6047 insertions(+), 265 deletions(-) diff --git a/openptv_python/calibration.py b/openptv_python/calibration.py index 3415aa4..e286d6a 100644 --- a/openptv_python/calibration.py +++ b/openptv_python/calibration.py @@ -70,16 +70,17 @@ def rotation_matrix(ext: np.ndarray) -> None: Interior = np.array( (0, 0, 0), dtype = interior_dtype).view(np.recarray) -ap52_dtype = np.dtype([ - ('k1', np.float64), - ('k2', np.float64), - ('k3', np.float64), - ('p1', np.float64), - ('p2', np.float64), - ('scx', np.float64), - ('she', np.float64) - ]) -ap_52 = np.array((0, 0, 0, 0, 0, 1, 0), dtype = ap52_dtype).view(np.recarray) +# ap52_dtype = np.dtype([ +# ('k1', np.float64), +# ('k2', np.float64), +# ('k3', np.float64), +# ('p1', np.float64), +# ('p2', np.float64), +# ('scx', np.float64), +# ('she', np.float64) +# ]) +ap_52 = np.array((0, 0, 0, 0, 0, 1, 0), dtype = np.float64) +# ap_52 = np.array((0, 0, 0, 0, 0, 1, 0), dtype = ap52_dtype).view(np.recarray) mmlut_dtype = np.dtype([ ('origin', np.float64, 3), @@ -177,9 +178,10 @@ def from_file(cls, ori_file: str, add_file: str | None): else: # print("no addpar fallback used") # Waits for proper logging. print("No addpar file found. Using default values for radial distortion") - ret.added_par.k1 = ret.added_par.k2 = ret.added_par.k3 \ - = ret.added_par.p1 = ret.added_par.p2 = ret.added_par.she = 0.0 - ret.added_par.scx = 1.0 + # ret.added_par.k1 = ret.added_par.k2 = ret.added_par.k3 \ + # = ret.added_par.p1 = ret.added_par.p2 = ret.added_par.she = 0.0 + # ret.added_par.scx = 1.0 + ret.added_par = np.array([0,0,0,0,0,1,0], dtype=np.float64) return ret # print(f"Calibration data read from files {ori_file} and {add_file}") @@ -300,7 +302,9 @@ def set_radial_distortion(self, dist_coeffs: np.ndarray) -> None: if dist_coeffs.shape != (3,): raise ValueError("Expected a 3-element array") - self.added_par.k1, self.added_par.k2, self.added_par.k3 = dist_coeffs + self.added_par[:3] = dist_coeffs + + # self.added_par.k1, self.added_par.k2, self.added_par.k3 = dist_coeffs def get_radial_distortion(self): @@ -309,7 +313,8 @@ def get_radial_distortion(self): array, from lowest power to highest. """ - return np.r_[self.added_par.k1, self.added_par.k2, self.added_par.k3] + # return np.r_[self.added_par.k1, self.added_par.k2, self.added_par.k3] + return self.added_par[:3] def set_decentering(self, decent: np.ndarray) -> None: """ @@ -322,11 +327,13 @@ def set_decentering(self, decent: np.ndarray) -> None: if decent.shape != (2,): raise ValueError("Expected a 2-element list") - self.added_par.p1, self.added_par.p2 = decent + # self.added_par.p1, self.added_par.p2 = decent + self.added_par[3:5] = decent def get_decentering(self): """Return the decentering parameters [1] as a 2 element array, (p_1, p_2).""" - return np.r_[self.added_par.p1, self.added_par.p2] + # return np.r_[self.added_par.p1, self.added_par.p2] + return self.added_par[3:5] def set_affine_distortion(self, affine: np.ndarray) -> None: """ @@ -339,11 +346,13 @@ def set_affine_distortion(self, affine: np.ndarray) -> None: if affine.shape != (2,): raise ValueError("Expected a 2-element list") - self.added_par.scx, self.added_par.she = affine + # self.added_par.scx, self.added_par.she = affine + self.added_par[5:] = affine def get_affine(self): """Return the affine transform parameters [1] as a 2 element array, (scx, she).""" - return np.r_[self.added_par.scx, self.added_par.she] + # return np.r_[self.added_par.scx, self.added_par.she] + return self.added_par[5:] def set_glass_vec(self, gvec: np.ndarray): """ @@ -368,7 +377,8 @@ def get_glass_vec(self) -> np.ndarray: def set_added_par(self, ap52_array: np.ndarray): """Set added par from an numpy array of parameters.""" - self.added_par = np.array(tuple(ap52_array.tolist()), dtype = ap52_dtype).view(np.recarray) + # self.added_par = np.array(tuple(ap52_array.tolist()), dtype = ap52_dtype).view(np.recarray) + self.added_par = ap52_array def copy(self, new_copy): """Copy the calibration data to a new object.""" diff --git a/openptv_python/orientation.py b/openptv_python/orientation.py index 114f5cd..8c557c0 100644 --- a/openptv_python/orientation.py +++ b/openptv_python/orientation.py @@ -16,7 +16,7 @@ from .parameters import ControlPar, MultimediaPar, OrientPar, VolumePar from .ray_tracing import ray_tracing from .sortgrid import sortgrid -from .tracking_frame_buf import Target, TargetArray +from .tracking_frame_buf import Target from .trafo import correct_brown_affine, pixel_to_metric from .vec_utils import unit_vector, vec_norm, vec_set @@ -301,14 +301,14 @@ def orient( cal.int_par.cc, cal.int_par.xh, cal.int_par.yh, - cal.added_par.k1, - cal.added_par.k2, - cal.added_par.k3, - cal.added_par.p1, - cal.added_par.p2, - cal.added_par.scx, - cal.added_par.she, - ] + cal.added_par[0], + cal.added_par[1], + cal.added_par[2], + cal.added_par[3], + cal.added_par[4], + cal.added_par[5], + cal.added_par[6] + ] # backup for changing back and forth safety_x = cal.glass_par[0] @@ -343,40 +343,40 @@ def orient( # derivatives of distortion parameters r = np.sqrt(xp * xp + yp * yp) - X[n][7] = cal.added_par.scx - X[n + 1][7] = np.sin(cal.added_par.she) + X[n][7] = cal.added_par[5] # cal.added_par[5] + X[n + 1][7] = np.sin(cal.added_par[6]) #np.sin(cal.added_par[6]) X[n][8] = 0 X[n + 1][8] = 1 - X[n][9] = cal.added_par.scx * xp * r * r + X[n][9] = cal.added_par[5] * xp * r * r X[n + 1][9] = yp * r * r - X[n][10] = cal.added_par.scx * xp * pow(r, 4) + X[n][10] = cal.added_par[5] * xp * pow(r, 4) X[n + 1][10] = yp * pow(r, 4) - X[n][11] = cal.added_par.scx * xp * pow(r, 6) + X[n][11] = cal.added_par[5] * xp * pow(r, 6) X[n + 1][11] = yp * pow(r, 6) - X[n][12] = cal.added_par.scx * (2 * xp * xp + r * r) + X[n][12] = cal.added_par[5] * (2 * xp * xp + r * r) X[n + 1][12] = 2 * xp * yp - X[n][13] = 2 * cal.added_par.scx * xp * yp + X[n][13] = 2 * cal.added_par[5] * xp * yp X[n + 1][13] = 2 * yp * yp + r * r - qq = cal.added_par.k1 * r * r - qq += cal.added_par.k2 * pow(r, 4) - qq += cal.added_par.k3 * pow(r, 6) + qq = cal.added_par[0] * r * r + qq += cal.added_par[1] * pow(r, 4) + qq += cal.added_par[2] * pow(r, 6) qq += 1 X[n][14] = ( xp * qq - + cal.added_par.p1 * (r * r + 2 * xp * xp) - + 2 * cal.added_par.p2 * xp * yp + + cal.added_par[3] * (r * r + 2 * xp * xp) + + 2 * cal.added_par[4] * xp * yp ) X[n + 1][14] = 0 - X[n][15] = -np.cos(cal.added_par.she) * yp - X[n + 1][15] = -np.sin(cal.added_par.she) * yp + X[n][15] = -np.cos(cal.added_par[6]) * yp + X[n + 1][15] = -np.sin(cal.added_par[6]) * yp # numeric derivatives of projection coordinates over external parameters, # 3D position and the angles @@ -449,13 +449,13 @@ def orient( y[n_obs + 0] = ident[0] - cal.int_par.cc y[n_obs + 1] = ident[1] - cal.int_par.xh y[n_obs + 2] = ident[2] - cal.int_par.yh - y[n_obs + 3] = ident[3] - cal.added_par.k1 - y[n_obs + 4] = ident[4] - cal.added_par.k2 - y[n_obs + 5] = ident[5] - cal.added_par.k3 - y[n_obs + 6] = ident[6] - cal.added_par.p1 - y[n_obs + 7] = ident[7] - cal.added_par.p2 - y[n_obs + 8] = ident[8] - cal.added_par.scx - y[n_obs + 9] = ident[9] - cal.added_par.she + y[n_obs + 3] = ident[3] - cal.added_par[0] + y[n_obs + 4] = ident[4] - cal.added_par[1] + y[n_obs + 5] = ident[5] - cal.added_par[2] + y[n_obs + 6] = ident[6] - cal.added_par[3] + y[n_obs + 7] = ident[7] - cal.added_par[4] + y[n_obs + 8] = ident[8] - cal.added_par[5] + y[n_obs + 9] = ident[9] - cal.added_par[6] # weights for i in range(n_obs): @@ -540,13 +540,13 @@ def orient( cal.int_par.cc += beta[6] cal.int_par.xh += beta[7] cal.int_par.yh += beta[8] - cal.added_par.k1 += beta[9] - cal.added_par.k2 += beta[10] - cal.added_par.k3 += beta[11] - cal.added_par.p1 += beta[12] - cal.added_par.p2 += beta[13] - cal.added_par.scx += beta[14] - cal.added_par.she += beta[15] + cal.added_par[0] += beta[9] + cal.added_par[1] += beta[10] + cal.added_par[2] += beta[11] + cal.added_par[3] += beta[12] + cal.added_par[4] += beta[13] + cal.added_par[5] += beta[14] + cal.added_par[6] += beta[15] if flags.interfflag: cal.glass_par[0] += e1[0] * nGl * beta[16] @@ -606,14 +606,14 @@ def raw_orient( beta = np.zeros(6) pos = np.zeros(3) - cal.added_par.k1 = 0 - cal.added_par.k2 = 0 - cal.added_par.k3 = 0 - cal.added_par.p1 = 0 - cal.added_par.p2 = 0 - cal.added_par.scx = 1 - cal.added_par.she = 0 - + # cal.added_par[0] = 0 + # cal.added_par[1] = 0 + # cal.added_par[2] = 0 + # cal.added_par[3] = 0 + # cal.added_par[4] = 0 + # cal.added_par[5] = 1 + # cal.added_par[6] = 0 + cal.added_par = np.array([0, 0, 0, 0, 0, 1, 0], dtype=np.float64) itnum = 0 stopflag = False @@ -787,7 +787,7 @@ def external_calibration( def full_calibration( cal: Calibration, ref_pts: np.ndarray, - img_pts: TargetArray, + img_pts: np.ndarray, cparam: ControlPar, orient_par: OrientPar, dm: float = 1e-6, @@ -832,7 +832,16 @@ def full_calibration( ValueError if iteration did not converge. """ err_est = np.empty((NPAR + 1), dtype=np.float64) - residuals = orient(cal, cparam, len(ref_pts), ref_pts, img_pts, orient_par, err_est, dm=dm, drad=drad) + + # convert numpy array to list of Target objects + targs = [Target() for _ in img_pts] + + for ptx, pt in enumerate(img_pts): + targs[ptx].x = pt[0] + targs[ptx].y = pt[1] + targs[ptx].pnr = ptx + + residuals = orient(cal, cparam, len(ref_pts), ref_pts, targs, orient_par, err_est, dm=dm, drad=drad) # free(orip) @@ -844,7 +853,7 @@ def full_calibration( ret = np.empty((len(img_pts), 2)) used = np.empty(len(img_pts), dtype=np.int_) - for ix, img_pt in enumerate(img_pts): + for ix, img_pt in enumerate(targs): ret[ix] = (residuals[2 * ix], residuals[2 * ix + 1]) used[ix] = img_pt.pnr @@ -855,7 +864,7 @@ def full_calibration( def match_detection_to_ref( cal: Calibration, ref_pts: np.ndarray, - img_pts: TargetArray, + img_pts: List[Target], cparam: ControlPar, eps: int = 25, ) -> List[Target]: diff --git a/openptv_python/tracking_frame_buf.py b/openptv_python/tracking_frame_buf.py index f585b07..2526ab9 100644 --- a/openptv_python/tracking_frame_buf.py +++ b/openptv_python/tracking_frame_buf.py @@ -136,31 +136,31 @@ def sort_target_y(targets: List[Target]) -> List[Target]: """Sort targets by y coordinate.""" return sorted(targets, key=lambda t: t.y) -class TargetArray(list): - """Target array class.""" +# class TargetArray(list): +# """Target array class.""" - def __init__(self, num_targets: int = 0): - super().__init__(Target() for item in range(num_targets)) +# def __init__(self, num_targets: int = 0): +# super().__init__(Target() for item in range(num_targets)) - def __setitem__(self, index, item): - super().__setitem__(index, item) +# def __setitem__(self, index, item): +# super().__setitem__(index, item) - def insert(self, index, item): - super().insert(index, item) +# def insert(self, index, item): +# super().insert(index, item) - def append(self, item): - super().append(str(item)) +# def append(self, item): +# super().append(str(item)) - def extend(self, other): - if isinstance(other, type(self)): - super().extend(other) - else: - super().extend(item for item in other) +# def extend(self, other): +# if isinstance(other, type(self)): +# super().extend(other) +# else: +# super().extend(item for item in other) - @property - def num_targs(self): - """Return the number of targets in the list.""" - return len(self) +# @property +# def num_targs(self): +# """Return the number of targets in the list.""" +# return len(self) def read_targets(file_base: str, frame_num: int) -> List[Target]: diff --git a/openptv_python/trafo.py b/openptv_python/trafo.py index db0c7c0..0487c5f 100644 --- a/openptv_python/trafo.py +++ b/openptv_python/trafo.py @@ -146,32 +146,37 @@ def fast_arr_metric_to_pixel( @njit(fastmath=True, cache=True, nogil=True) def distort_brown_affine(x: float, y: float, - ap: np.recarray, + ap: np.ndarray, ) -> Tuple[float, float]: - """Distort a point using the Brown affine model.""" + """Distort a point using the Brown affine model. + + ap: ap52_dtype: np.recarray with fields k1, k2, k3, p1, p2, scx, she + presented here as a np.array + + """ if x == 0 and y == 0: return 0, 0 r = np.sqrt(x**2 + y**2) x += ( - x * (ap.k1 * r**2 + ap.k2 * r**4 + ap.k3 * r**6) - + ap.p1 * (r**2 + 2 * x**2) - + 2 * ap.p2 * x * y + x * (ap[0] * r**2 + ap[1] * r**4 + ap[2] * r**6) + + ap[3] * (r**2 + 2 * x**2) + + 2 * ap[4] * x * y ) y += ( - y * (ap.k1 * r**2 + ap.k2 * r**4 + ap.k3 * r**6) - + ap.p2 * (r**2 + 2 * y**2) - + 2 * ap.p1 * x * y + y * (ap[0] * r**2 + ap[1] * r**4 + ap[2] * r**6) + + ap[4] * (r**2 + 2 * y**2) + + 2 * ap[3] * x * y ) - x1 = ap.scx * x - np.sin(ap.she) * y - y1 = np.cos(ap.she) * y + x1 = ap[5] * x - np.sin(ap[6]) * y + y1 = np.cos(ap[6]) * y return x1, y1 @njit(fastmath=True, cache=True, nogil=True) -def correct_brown_affine(x: float, y: float, ap: np.recarray, tol: float = 1e-5) -> Tuple[float, float]: +def correct_brown_affine(x: float, y: float, ap: np.ndarray, tol: float = 1e-5) -> Tuple[float, float]: """Correct a distorted point using the Brown affine model.""" r, rq, xq, yq = 0.0, 0.0, x, y itnum = 0 @@ -180,28 +185,28 @@ def correct_brown_affine(x: float, y: float, ap: np.recarray, tol: float = 1e-5) return xq, yq rq = np.sqrt(x**2 + y**2) - two_p1 = 2 * ap.p1 - two_p2 = 2 * ap.p2 - cos_she = np.cos(ap.she) - sin_she = np.sin(ap.she) + two_p1 = 2 * ap[3] + two_p2 = 2 * ap[4] + cos_she = np.cos(ap[6]) + sin_she = np.sin(ap[6]) while True: r = rq - common_term = (ap.k1 * r**2 + ap.k2 * r**4 + ap.k3 * r**6) + common_term = (ap[0] * r**2 + ap[1] * r**4 + ap[2] * r**6) xq_common = xq * common_term yq_common = yq * common_term xq = ( - (x + yq * sin_she) / ap.scx + (x + yq * sin_she) / ap[5] - xq_common - - ap.p1 * (r**2 + 2 * xq**2) + - ap[3] * (r**2 + 2 * xq**2) - two_p2 * xq * yq ) yq = ( y / cos_she - yq_common - - ap.p2 * (r**2 + 2 * yq**2) + - ap[4] * (r**2 + 2 * yq**2) - two_p1 * xq * yq ) @@ -217,16 +222,16 @@ def correct_brown_affine(x: float, y: float, ap: np.recarray, tol: float = 1e-5) r = rq x1 = ( - (x + yq * sin_she) / ap.scx + (x + yq * sin_she) / ap[5] - xq * common_term - - ap.p1 * (r**2 + 2 * xq**2) + - ap[3] * (r**2 + 2 * xq**2) - two_p2 * xq * yq ) y1 = ( y / cos_she - yq * common_term - - ap.p2 * (r**2 + 2 * yq**2) + - ap[4] * (r**2 + 2 * yq**2) - two_p1 * xq * yq ) diff --git a/tests/test_calibration_optimize.ipynb b/tests/test_calibration_optimize.ipynb index 54c725e..a5a4b11 100644 --- a/tests/test_calibration_optimize.ipynb +++ b/tests/test_calibration_optimize.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 21, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -11,24 +11,21 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ - "import unittest\n", - "\n", "import numpy as np\n", "import scipy.optimize as opt\n", "\n", - "from openptv_python.calibration import (\n", - " Calibration,\n", - ")\n", + "from openptv_python.calibration import Calibration\n", "from openptv_python.imgcoord import image_coordinates\n", "from openptv_python.orientation import (\n", " external_calibration,\n", + " full_calibration\n", ")\n", - "from openptv_python.parameters import ControlPar, OrientPar, VolumePar, read_control_par\n", - "from openptv_python.tracking_frame_buf import TargetArray\n", + "from openptv_python.parameters import ControlPar, OrientPar, read_control_par\n", + "from openptv_python.tracking_frame_buf import Target\n", "from openptv_python.trafo import arr_metric_to_pixel\n", "from openptv_python.imgcoord import img_coord\n", "from openptv_python.trafo import pixel_to_metric\n", @@ -37,78 +34,9 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [], - "source": [ - "class TestGradientDescent(unittest.TestCase):\n", - " # Based on the C tests in liboptv/check_orientation.c\n", - "\n", - " def setUp(self):\n", - " control_file_name = \"testing_folder/corresp/control.par\"\n", - " # self.control = ControlPar(4)\n", - " self.control = read_control_par(control_file_name)\n", - "\n", - " self.orient_par_file_name = \"testing_folder/corresp/orient.par\"\n", - " self.orient_par = OrientPar().from_file(self.orient_par_file_name)\n", - "\n", - " self.cal = Calibration().from_file(\n", - " \"testing_folder/calibration/cam1.tif.ori\",\n", - " \"testing_folder/calibration/cam1.tif.addpar\",\n", - " )\n", - " self.orig_cal = Calibration().from_file(\n", - " \"testing_folder/calibration/cam1.tif.ori\",\n", - " \"testing_folder/calibration/cam1.tif.addpar\",\n", - " )\n", - "\n", - " \n", - " def test_external_calibration(self):\n", - " \"\"\"External calibration using clicked points.\"\"\"\n", - " ref_pts = np.array(\n", - " [\n", - " [-40.0, -25.0, 8.0],\n", - " [40.0, -15.0, 0.0],\n", - " [40.0, 15.0, 0.0],\n", - " [40.0, 0.0, 8.0],\n", - " ]\n", - " )\n", - "\n", - " # Fake the image points by back-projection\n", - " targets = arr_metric_to_pixel(\n", - " image_coordinates(ref_pts, self.cal, self.control.mm),\n", - " self.control,\n", - " )\n", - "\n", - " # Jigg the fake detections to give raw_orient some challenge.\n", - " targets[:, 1] -= 0.1\n", - "\n", - " self.assertTrue(external_calibration(self.cal, ref_pts, targets, self.control))\n", - " np.testing.assert_array_almost_equal(\n", - " self.cal.get_angles(), self.orig_cal.get_angles(), decimal=3\n", - " )\n", - " np.testing.assert_array_almost_equal(\n", - " self.cal.get_pos(), self.orig_cal.get_pos(), decimal=3\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 24, + "execution_count": 3, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "test_external_calibration (__main__.TestGradientDescent)\n", - "External calibration using clicked points. ... ok\n", - "\n", - "----------------------------------------------------------------------\n", - "Ran 1 test in 0.014s\n", - "\n", - "OK\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -117,27 +45,86 @@ " -1.31470856e-07 4.02517087e-06]\n", "Residuals: []\n", "rank: 6\n", - "singular_values: None\n" + "singular_values: None\n", + "Coefficients (beta): [-4.25882590e-07 4.80825222e-07 6.29760235e-07 -6.93208604e-10\n", + " -1.31524482e-09 1.38712355e-10 6.37062243e-09 -1.99771542e-09\n", + " 1.87539971e-08 1.20982734e-23 3.48242641e-21 9.95530889e-19\n", + " -3.20792894e-24 -9.94728623e-25 1.26333821e-25 2.14317243e-25] \n", + " Residuals: [] \n", + " singular_values: None \n", + " rank: 16 \n", + " \n" ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ - "unittest.main(argv=[''], verbosity=2, exit=False)" + "\n", + "control_file_name = \"testing_folder/corresp/control.par\"\n", + "# self.control = ControlPar(4)\n", + "control = read_control_par(control_file_name)\n", + "\n", + "orient_par_file_name = \"testing_folder/corresp/orient.par\"\n", + "orient_par = OrientPar().from_file(orient_par_file_name)\n", + "\n", + "cal = Calibration().from_file(\n", + " \"testing_folder/calibration/cam1.tif.ori\",\n", + " \"testing_folder/calibration/cam1.tif.addpar\",\n", + ")\n", + "orig_cal = Calibration().from_file(\n", + " \"testing_folder/calibration/cam1.tif.ori\",\n", + " \"testing_folder/calibration/cam1.tif.addpar\",\n", + ")\n", + "\n", + "\n", + "# def test_external_calibration(self):\n", + "\"\"\"External calibration using clicked points.\"\"\"\n", + "ref_pts = np.array(\n", + " [\n", + " [-40.0, -25.0, 8.0],\n", + " [40.0, -15.0, 0.0],\n", + " [40.0, 15.0, 0.0],\n", + " [40.0, 0.0, 8.0],\n", + " ]\n", + ")\n", + "\n", + "# Fake the image points by back-projection\n", + "targets = arr_metric_to_pixel(\n", + " image_coordinates(ref_pts, cal, control.mm),\n", + " control,\n", + ")\n", + "\n", + "# Jigg the fake detections to give raw_orient some challenge.\n", + "targets[:, 1] -= 0.1\n", + "\n", + "external_calibration(cal, ref_pts, targets, control)\n", + "\n", + "np.testing.assert_array_almost_equal(\n", + " cal.get_angles(), orig_cal.get_angles(), decimal=3\n", + ")\n", + "np.testing.assert_array_almost_equal(\n", + " cal.get_pos(), orig_cal.get_pos(), decimal=3\n", + ")\n", + "\n", + "\n", + "_, _, _ = full_calibration(\n", + " cal,\n", + " ref_pts,\n", + " targets,\n", + " control,\n", + " orient_par\n", + " )\n", + "\n", + "np.testing.assert_array_almost_equal(\n", + " cal.get_angles(), orig_cal.get_angles(), decimal=3\n", + ")\n", + "np.testing.assert_array_almost_equal(\n", + " cal.get_pos(), orig_cal.get_pos(), decimal=3\n", + ")" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -158,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -186,7 +173,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -199,25 +186,84 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ + "# def residual(calibration_array, ref_pts, targs, control, cc):\n", + "# # print(calibration_array)\n", + "# # print(ref_pts)\n", + "# # print(targs)\n", + "# # print(control)\n", + "# # print(calibration_array)\n", + " \n", + "# c = Calibration()\n", + "# c.set_pos(calibration_array[:3])\n", + "# c.set_angles(calibration_array[3:])\n", + "# c.int_par.cc = cc\n", + "# c.update_rotation_matrix()\n", + " \n", + " \n", + "# # print(f\"{c.get_pos()=}\")\n", + " \n", + "# residual = 0\n", + "# for i in range(len(targs)):\n", + "# xc, yc = pixel_to_metric(targs[i].x, targs[i].y, control)\n", + "# # print(f\"{xc=}, {yc=} mm\")\n", + " \n", + "# xp, yp = img_coord(ref_pts[i], c, control.mm)\n", + "# # print(f\"{xp=}, {yp=} mm\")\n", + "# residual += ((xc - xp)**2 + (yc - yp)**2)\n", + " \n", + "# # print(f\"{residual=}\")\n", + " \n", + "# return residual" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# x0 = np.hstack([cal.get_pos(), cal.get_angles()])\n", + "# cc = orig_cal.int_par.cc\n", "\n", - "\n", - "def residual(calibration_array, ref_pts, targs, control, cc):\n", + "# sol = opt.minimize(residual, x0, args=(ref_pts, targs, control, cc), method='Nelder-Mead', tol=1e-6)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# print( residual(np.hstack([orig_cal.get_pos(), orig_cal.get_angles()]), ref_pts, targs, control, orig_cal.int_par.cc))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "import copy\n", + "def added_par_residual(added_par_array, ref_pts, targs, control, cal):\n", " # print(calibration_array)\n", " # print(ref_pts)\n", " # print(targs)\n", " # print(control)\n", " # print(calibration_array)\n", - " \n", " c = Calibration()\n", - " c.set_pos(calibration_array[:3])\n", - " c.set_angles(calibration_array[3:])\n", - " c.int_par.cc = cc\n", - " c.update_rotation_matrix()\n", - " \n", + " c = copy.deepcopy(cal)\n", + " c.added_par = added_par_array\n", " \n", " # print(f\"{c.get_pos()=}\")\n", " \n", @@ -237,60 +283,5768 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay 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"multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "sol.x=array([-2.22546580e-03, 1.70567795e-06, -3.75579841e-10, -1.43985798e-03,\n", + " -1.07047604e-03, 1.07511509e+00, 8.82840749e-04])\n" + ] + } + ], "source": [ - "x0 = np.hstack([cal.get_pos(), cal.get_angles()])\n", - "cc = orig_cal.int_par.cc\n", + "x0 = np.array(cal.added_par.tolist())\n", "\n", - "sol = opt.minimize(residual, x0, args=(ref_pts, targs, control, cc), method='Nelder-Mead', tol=1e-6)" + "sol = opt.minimize(added_par_residual, x0, args=(ref_pts, targs, control, cal), method='Nelder-Mead', tol=1e-6)\n", + "print(f\"{sol.x=}\")\n", + "# print(sol.x - np.hstack([orig_cal.get_pos(), orig_cal.get_angles()]))\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "sol.x=array([-3.79876331e+00, 3.77309709e+01, 4.03575316e+02, -8.61982784e-02,\n", - " -6.33837589e-02, 5.14334685e-02])\n", - "[-1.09061963e+02 -6.50148291e+01 -3.06884099e-01 1.52130822e-01\n", - " -3.07664759e-01 -3.82423146e-03]\n" + "[0. 0. 0. 0. 0. 1. 0.]\n", + "[-2.22546580e-03 1.70567795e-06 -3.75579841e-10 -1.43985798e-03\n", + " -1.07047604e-03 1.07511509e+00 8.82840749e-04]\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "Coefficients (beta): [ 1.75210295e+01 1.61886453e+01 -9.85117679e-01 -1.41948530e-01\n", + " 1.49755845e-01 -3.73757019e-02 5.32519029e-04 5.16738324e-02\n", + " -3.26663704e-02 -2.23363230e-19 -5.25144772e-17 -1.49038956e-14\n", + " 4.27884986e-20 -3.26817763e-20 4.37601823e-22 -9.93928331e-22] \n", + " Residuals: [] \n", + " singular_values: None \n", + " rank: 16 \n", + " \n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "multimed_r_nlay stopped after 40 iterations\n", + "Coefficients (beta): [ 4.35354651e-23 -9.58410085e-24 2.44311581e-23 -3.81844354e-22\n", + " -2.05550842e-21 5.01212242e-23 -9.91129061e-24 2.22178845e-25\n", + " 1.12830459e-28 -3.41946585e-12 -8.56806960e-12 6.42172735e-19\n", + " 7.35687222e-14 -4.19029078e-15 -8.62741036e-14 4.64343698e-17] \n", + " Residuals: [] \n", + " singular_values: None \n", + " rank: 7 \n", + " \n", + "[-2.22546580e-03 1.70567795e-06 -3.75579841e-10 -1.43985798e-03\n", + " -1.07047604e-03 1.07511509e+00 8.82840749e-04]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/user/Documents/repos/openptvpy/openptv-python/openptv_python/orientation.py:577: RuntimeWarning: invalid value encountered in sqrt\n", + " sigmabeta[i] = sigmabeta[NPAR] * np.sqrt(XPX[i][i])\n" ] } ], "source": [ - "print(f\"{sol.x=}\")\n", - "print(sol.x - np.hstack([orig_cal.get_pos(), orig_cal.get_angles()]))" + "# print(sol.x)\n", + "print(cal.added_par)\n", + "cal.set_added_par(sol.x)\n", + "print(cal.added_par)\n", + "full_calibration(cal, ref_pts, targets, control, orient_par)\n", + "print(cal.added_par)" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "93.58853214427855\n" + "[17.52102953 16.18864526 99.01488232]\n", + "[-0.14194853 0.14975585 -0.0373757 ]\n", + "[ -2.42252617 3.22403363 100.00053252]\n", + "[-0.00143986 -0.00107048]\n", + "[-2.22546580e-03 1.70567795e-06 -3.75579841e-10 -1.43985798e-03\n", + " -1.07047604e-03 1.07511509e+00 8.82840749e-04]\n" ] } ], "source": [ - "print( residual(np.hstack([orig_cal.get_pos(), orig_cal.get_angles()]), ref_pts, targs, control, orig_cal.int_par.cc))" + "print(cal.get_pos())\n", + "print(cal.get_angles())\n", + "print(cal.get_primary_point())\n", + "print(cal.get_decentering())\n", + "print(cal.added_par)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/tests/test_orientation.py b/tests/test_orientation.py index 5e07d2c..951f2ab 100644 --- a/tests/test_orientation.py +++ b/tests/test_orientation.py @@ -14,7 +14,7 @@ weighted_dumbbell_precision, ) from openptv_python.parameters import ControlPar, OrientPar, VolumePar, read_control_par -from openptv_python.tracking_frame_buf import TargetArray +from openptv_python.tracking_frame_buf import Target from openptv_python.trafo import arr_metric_to_pixel @@ -54,11 +54,15 @@ def test_match_detection_to_ref(self): xy_img_pts_pixel = arr_metric_to_pixel(xy_img_pts_metric, self.control) # convert to TargetArray object - target_array = TargetArray(coords_count) + # targets = TargetArray(coords_count) + targets = [Target() for _ in range(coords_count)] for i in range(coords_count): - target_array[i].set_pnr(i) - target_array[i].set_pos((xy_img_pts_pixel[i][0], xy_img_pts_pixel[i][1])) + targets[i].pnr = i + targets[i].x = xy_img_pts_pixel[i][0] + targets[i].y = xy_img_pts_pixel[i][1] + + # set_pos((xy_img_pts_pixel[i][0], xy_img_pts_pixel[i][1])) # create randomized target array indices = np.arange(coords_count) @@ -67,10 +71,12 @@ def test_match_detection_to_ref(self): while np.all(indices == shuffled_indices): np.random.shuffle(shuffled_indices) - rand_targ_array = TargetArray(coords_count) + # rand_targ_array = TargetArray(coords_count) + rand_targ_array = [Target() for _ in range(coords_count)] for i in range(coords_count): - rand_targ_array[shuffled_indices[i]].set_pos(target_array[i].pos()) - rand_targ_array[shuffled_indices[i]].set_pnr(target_array[i].pnr) + rand_targ_array[shuffled_indices[i]].x = targets[i].x + rand_targ_array[shuffled_indices[i]].y = targets[i].y + rand_targ_array[shuffled_indices[i]].pnr = targets[i].pnr # match detection to reference matched_target_array = match_detection_to_ref( @@ -82,10 +88,7 @@ def test_match_detection_to_ref(self): # assert target array is as before for i in range(coords_count): - if ( - matched_target_array[i].pos() != target_array[i].pos() - or matched_target_array[i].pnr != target_array[i].pnr - ): + if matched_target_array[i] != targets[i]: self.fail() # pass ref_pts and img_pts with non-equal lengths @@ -334,11 +337,11 @@ def test_full_calibration(self): self.control, ) - # Full calibration works with TargetArray objects, not NumPy. - target_array = TargetArray(len(targets)) - for i, trgt in enumerate(target_array): - trgt.set_pnr(i) - trgt.set_pos(targets[i]) + # # Full calibration works with TargetArray objects, not NumPy. + # targets = TargetArray(len(targets)) + # for i, trgt in enumerate(targets): + # trgt.set_pnr(i) + # trgt.set_pos(targets[i]) # Perturb the calibration object, then compore result to original. self.cal.set_pos(self.cal.get_pos() + np.r_[15.0, -15.0, 15.0]) @@ -353,7 +356,7 @@ def test_full_calibration(self): _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -381,7 +384,7 @@ def test_full_calibration(self): _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -408,13 +411,13 @@ def test_full_calibration(self): self.orient_par.k2flag=0 self.orient_par.k3flag=0 self.orient_par.scxflag=0 - self.orient_par.sheflag=1 + self.orient_par.sheflag=0 print(f"Calibrating with the following flags: {self.orient_par}") _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -442,7 +445,7 @@ def test_full_calibration(self): _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -470,7 +473,7 @@ def test_full_calibration(self): _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -498,7 +501,7 @@ def test_full_calibration(self): _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -526,7 +529,7 @@ def test_full_calibration(self): _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -550,14 +553,14 @@ def test_full_calibration(self): self.orient_par.scxflag=0 self.orient_par.sheflag=0 self.orient_par.p1flag=1 - self.orient_par.p2floag=0 + self.orient_par.p2flag=0 print(f"Calibrating with the following flags: {self.orient_par}") _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) @@ -572,7 +575,7 @@ def test_full_calibration(self): print(f"{self.cal.get_angles()}") print(f"{self.cal.added_par}") - self.orient_par.ccflag=0 + self.orient_par.ccflag=1 self.orient_par.xhflag=0 self.orient_par.yhflag=0 self.orient_par.k1flag=0 @@ -587,7 +590,7 @@ def test_full_calibration(self): _, _, _ = full_calibration( self.cal, ref_pts, - target_array, + targets, self.control, self.orient_par ) diff --git a/tests/test_read_targets.py b/tests/test_read_targets.py index a158081..e8c087a 100644 --- a/tests/test_read_targets.py +++ b/tests/test_read_targets.py @@ -3,7 +3,6 @@ from openptv_python.tracking_frame_buf import ( Target, - TargetArray, read_targets, write_targets, ) @@ -23,7 +22,9 @@ def test_fill_target(self): def test_fill_target_array(self): """Test filling a target array.""" - tarr = TargetArray(num_targets=2) + # tarr = TargetArray(num_targets=2) + tarr = [Target() for _ in range(2)] + tarr[0].set_pos((1.5, 2.5)) tarr[1].set_pos((3.5, 4.5))