docs: update the jupiter notebooks

Innoptech · Aug 23, 2024 · 9f13d68 · 9f13d68
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diff --git a/notebooks/general_template_matching_example.ipynb b/notebooks/general_template_matching_example.ipynb
@@ -47,7 +47,7 @@
       "source": [
         "### Environment Set-up\n",
         "\n",
-        "* If running locally using jupyter, first install `openfdcm==0.9.0` in your environment using the installation instructions in the repository.\n",
+        "* If running locally using jupyter, first install `openfdcm==0.10.0` in your environment using the installation instructions in the repository.\n",
         "\n",
         "* If running from Google Colab, set using_colab=True below and run the cell."
       ]
@@ -76,8 +76,8 @@
         "# Install required libraries\n",
         "if using_colab:\n",
         "  import sys\n",
-        "  !{sys.executable} -m pip install openfdcm==0.9.0\n",
-        "  !git clone --branch v0.8.3 --single-branch --depth 1 https://github.com/Innoptech/OpenFDCM\n",
+        "  !{sys.executable} -m pip install openfdcm==0.10.0\n",
+        "  !git clone --branch v0.10.0 --single-branch --depth 1 https://github.com/Innoptech/OpenFDCM\n",
         "  %matplotlib inline"
       ]
     },
@@ -288,19 +288,20 @@
         "# Perform template matching using OpenFDCM\n",
         "max_tmpl_lines, max_scene_lines = 3, 10  # Combinatory search parameters, the greater deetctions the better but slower.\n",
         "depth = 30              # The [0, pi] discretization.\n",
-        "scene_padding = 1.0     # A ratio to pad the scene images used in the FDCM algorithm, use if best match may appear on image boundaries.\n",
         "coeff = 5.0             # A weighting factor to enhance the angular cost vs distance cost in FDCM algorithm.\n",
+        "scene_padding = 1.0     # A ratio to pad the scene images used in the FDCM algorithm, use if best match may appear on image boundaries.\n",
+        "distance_type = openfdcm.distance.L2 # or openfdcm.distance.L2_SQUARED or openfdcm.distance.L1\n",
         "#num_threads = 4\n",
         "\n",
         "threadpool = openfdcm.ThreadPool() # could pass num_threads here, but default is optimal\n",
+        "featuremap_params = openfdcm.Dt3CpuParameters(depth, coeff, scene_padding, distance_type)\n",
         "search_strategy = openfdcm.DefaultSearch(max_tmpl_lines, max_scene_lines)\n",
         "optimizer_strategy = openfdcm.BatchOptimize(5, threadpool)\n",
         "matcher = openfdcm.DefaultMatch()\n",
         "# Penalize each match with 1/n^tau where n is the number of line in the template\n",
         "penalizer = openfdcm.ExponentialPenalty(tau=1.5)\n",
         "\n",
         "start_time = time.time()\n",
-        "featuremap_params = openfdcm.Dt3CpuParameters(depth=depth, dt3Coeff=coeff, padding=scene_padding)\n",
         "featuremap = openfdcm.build_cpu_featuremap(scene_lines, featuremap_params, threadpool)\n",
         "raw_matches = openfdcm.search(matcher, search_strategy, optimizer_strategy, featuremap, all_templates, scene_lines)\n",
         "penalized_matches = openfdcm.penalize(penalizer, raw_matches, openfdcm.get_template_lengths(all_templates))\n",

diff --git a/notebooks/pose_extimation_example.ipynb b/notebooks/pose_extimation_example.ipynb
@@ -52,7 +52,7 @@
         "\n",
         "### Environment Set-up\n",
         "\n",
-        "* If running locally using jupyter, first install `openfdcm==0.9.0` in your environment using the installation instructions in the repository.\n",
+        "* If running locally using jupyter, first install `openfdcm==0.10.0` in your environment using the installation instructions in the repository.\n",
         "\n",
         "* If running from Google Colab, set using_colab=True below and run the cell.\n",
         "\n"
@@ -81,8 +81,8 @@
         "# Install required libraries\n",
         "if using_colab:\n",
         "  import sys\n",
-        "  !{sys.executable} -m pip install openfdcm==0.9.0\n",
-        "  !git clone --branch v0.9.0 --single-branch --depth 1 https://github.com/Innoptech/OpenFDCM\n",
+        "  !{sys.executable} -m pip install openfdcm==0.10.0\n",
+        "  !git clone --branch v0.10.0 --single-branch --depth 1 https://github.com/Innoptech/OpenFDCM\n",
         "\n"
       ]
     },
@@ -214,13 +214,14 @@
         "\n",
         "    # Perform template matching\n",
         "    max_tmpl_lines, max_scene_lines = 4, 10  # Combinatory search parameters (the higer the better but exp slower).\n",
-        "    depth = 30              # The [0, pi] discretization, the higher, the most precise but lin slower.\n",
-        "    scene_padding = 1.0     # A ratio to pad the scene images used in the FDCM algorithm, use if best match may appear on image boundaries.\n",
+        "    depth = 30              # The [0, pi] discretization.\n",
         "    coeff = 5.0             # A weighting factor to enhance the angular cost vs distance cost in FDCM algorithm.\n",
+        "    scene_padding = 1.0     # A ratio to pad the scene images used in the FDCM algorithm, use if best match may appear on image boundaries.\n",
+        "    distance_type = openfdcm.distance.L2 # or openfdcm.distance.L2_SQUARED or openfdcm.distance.L1\n",
         "    #num_threads = 4\n",
         "\n",
         "    threadpool = openfdcm.ThreadPool() # could pass num_threads here, but default is optimal\n",
-        "    featuremap_params = openfdcm.Dt3CpuParameters(depth, coeff, scene_padding)\n",
+        "    featuremap_params = openfdcm.Dt3CpuParameters(depth, coeff, scene_padding, distance_type)\n",
         "    search_strategy = openfdcm.DefaultSearch(max_tmpl_lines, max_scene_lines)\n",
         "    optimizer_strategy = openfdcm.BatchOptimize(10, threadpool)\n",
         "    matcher = openfdcm.DefaultMatch()\n",