Merge pull request #635 from sglvladi/video_processing_demo_updates

Fix video processing tutorial

docs/demos/Video_Processing.py

@@ -89,7 +89,7 @@
 
 if not os.path.exists(VIDEO_PATH):
     yt = YouTube('http://www.youtube.com/watch?v=MNn9qKG2UFI')
-    yt.streams[0].download(filename=VIDEO_FILENAME)
+    yt.streams.get_by_itag(18).download(filename=VIDEO_PATH)
 
 # %%
 # Building the video reader
@@ -470,8 +470,8 @@ def draw_detections(image, detections, show_class=False, show_score=False):
 prior_state = GaussianState(StateVector(np.zeros((6,1))),
                             CovarianceMatrix(np.diag([100**2, 30**2, 100**2, 30**2, 100**2, 100**2])))
 deleter_init = UpdateTimeStepsDeleter(time_steps_since_update=3)
-initiator = MultiMeasurementInitiator(prior_state, measurement_model, deleter_init,
-                                      data_associator, updater, min_points=10)
+initiator = MultiMeasurementInitiator(prior_state, deleter_init, data_associator, updater,
+                                      measurement_model, min_points=10)
 
 # %%
 # Track Deletion

docs/source/auto_demos/Video_Processing.ipynb

@@ -54,7 +54,7 @@
       },
       "outputs": [],
       "source": [
-        "import os\nfrom pytube import YouTube\nVIDEO_FILENAME = 'sample1'\nVIDEO_EXTENTION = '.mp4'\nVIDEO_PATH = os.path.join(os.getcwd(), VIDEO_FILENAME+VIDEO_EXTENTION)\n\nif not os.path.exists(VIDEO_PATH):\n    yt = YouTube('http://www.youtube.com/watch?v=MNn9qKG2UFI')\n    yt.streams[0].download(filename=VIDEO_FILENAME)"
+        "import os\nfrom pytube import YouTube\nVIDEO_FILENAME = 'sample1'\nVIDEO_EXTENTION = '.mp4'\nVIDEO_PATH = os.path.join(os.getcwd(), VIDEO_FILENAME+VIDEO_EXTENTION)\n\nif not os.path.exists(VIDEO_PATH):\n    yt = YouTube('http://www.youtube.com/watch?v=MNn9qKG2UFI')\n    yt.streams.get_by_itag(18).download(filename=VIDEO_PATH)"
       ]
     },
     {
@@ -363,7 +363,7 @@
       },
       "outputs": [],
       "source": [
-        "from stonesoup.types.state import GaussianState\nfrom stonesoup.types.array import CovarianceMatrix, StateVector\nfrom stonesoup.initiator.simple import MultiMeasurementInitiator\nfrom stonesoup.deleter.time import UpdateTimeStepsDeleter\nprior_state = GaussianState(StateVector(np.zeros((6,1))),\n                            CovarianceMatrix(np.diag([100**2, 30**2, 100**2, 30**2, 100**2, 100**2])))\ndeleter_init = UpdateTimeStepsDeleter(time_steps_since_update=3)\ninitiator = MultiMeasurementInitiator(prior_state, measurement_model, deleter_init,\n                                      data_associator, updater, min_points=10)"
+        "from stonesoup.types.state import GaussianState\nfrom stonesoup.types.array import CovarianceMatrix, StateVector\nfrom stonesoup.initiator.simple import MultiMeasurementInitiator\nfrom stonesoup.deleter.time import UpdateTimeStepsDeleter\nprior_state = GaussianState(StateVector(np.zeros((6,1))),\n                            CovarianceMatrix(np.diag([100**2, 30**2, 100**2, 30**2, 100**2, 100**2])))\ndeleter_init = UpdateTimeStepsDeleter(time_steps_since_update=3)\ninitiator = MultiMeasurementInitiator(prior_state, deleter_init, data_associator, updater,\n                                      measurement_model, min_points=10)"
       ]
     },
     {
@@ -437,7 +437,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.5"
+      "version": "3.9.6"
     }
   },
   "nbformat": 4,

docs/source/auto_demos/Video_Processing.py.md5

@@ -1 +1 @@
-3bb4f60e68c434061bcc4598c423df3f
+7b6743387b9f94bdc50f5289135ecf45

docs/source/auto_demos/Video_Processing.rst

@@ -114,7 +114,7 @@ shown bellow will download the video and save it your working directory as ``sam
 
     if not os.path.exists(VIDEO_PATH):
         yt = YouTube('http://www.youtube.com/watch?v=MNn9qKG2UFI')
-        yt.streams[0].download(filename=VIDEO_FILENAME)
+        yt.streams.get_by_itag(18).download(filename=VIDEO_PATH)
 
 
 
@@ -239,7 +239,6 @@ read and visualise these frames using `matplotlib`.
     ani = animation.ArtistAnimation(fig, artists, interval=20, blit=True, repeat_delay=200)
 
 
-
 .. image::  ./images/sphx_glr_Video_Processing_001.gif
    :align: center
 
@@ -530,7 +529,6 @@ of how to read and visualise these detections using `matplotlib`.
     ani2 = animation.ArtistAnimation(fig2, artists2, interval=20, blit=True, repeat_delay=200)
 
 
-
 .. image:: ./images/sphx_glr_Video_Processing_002.gif
    :align: center
 
@@ -736,8 +734,8 @@ that have not been associated to a measurement in the last 3 frames.
     prior_state = GaussianState(StateVector(np.zeros((6,1))),
                                 CovarianceMatrix(np.diag([100**2, 30**2, 100**2, 30**2, 100**2, 100**2])))
     deleter_init = UpdateTimeStepsDeleter(time_steps_since_update=3)
-    initiator = MultiMeasurementInitiator(prior_state, measurement_model, deleter_init,
-                                          data_associator, updater, min_points=10)
+    initiator = MultiMeasurementInitiator(prior_state, deleter_init, data_associator, updater,
+                                          measurement_model, min_points=10)
 
 
 
@@ -904,7 +902,7 @@ Running the tracker
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 4 minutes  21.159 seconds)
+   **Total running time of the script:** ( 2 minutes  38.615 seconds)
 
 
 .. _sphx_glr_download_auto_demos_Video_Processing.py: