Correct batch processing section documentation and native multiproces…

…sing.

docs/tutorial/reconstruction_system/make_fragments.rst

@@ -86,11 +86,16 @@ Batch processing
 
 .. literalinclude:: ../../../examples/python/reconstruction_system/make_fragments.py
    :language: python
-   :lineno-start: 181
-   :lines: 27,182-205
+   :start-at: def process_single_fragment(fragment_id, color_files, depth_files, n_files,
    :linenos:
+   :lineno-match:
+
+The ``process_single_fragment`` function calls each individual function explained above.
+The ``run`` function determines the number of fragments to generate based on the number
+of images in the dataset and the configuration value ``n_frames_per_fragment``.
+Subsequently, it invokes ``process_single_fragment`` for each of these fragments.
+Furthermore, it leverages multiprocessing to speed up computation of all fragments.
 
-The main function calls each individual function explained above.
 
 .. _reconstruction_system_make_fragments_results:
 

examples/python/reconstruction_system/make_fragments.py

@@ -8,6 +8,7 @@
 # examples/python/reconstruction_system/make_fragments.py
 
 import math
+import multiprocessing
 import os, sys
 import numpy as np
 import open3d as o3d
@@ -172,13 +173,14 @@ def run(config):
         math.ceil(float(n_files) / config['n_frames_per_fragment']))
 
     if config["python_multi_threading"] is True:
-        from joblib import Parallel, delayed
-        import multiprocessing
-        import subprocess
-        MAX_THREAD = min(multiprocessing.cpu_count(), n_fragments)
-        Parallel(n_jobs=MAX_THREAD)(delayed(process_single_fragment)(
-            fragment_id, color_files, depth_files, n_files, n_fragments, config)
-                                    for fragment_id in range(n_fragments))
+        max_workers = min(max(1, multiprocessing.cpu_count() - 1), n_fragments)
+        # Prevent over allocation of open mp threads in child processes
+        os.environ['OMP_NUM_THREADS'] = '1'
+        mp_context = multiprocessing.get_context('spawn')
+        with mp_context.Pool(processes=max_workers) as pool:
+            args = [(fragment_id, color_files, depth_files, n_files,
+                     n_fragments, config) for fragment_id in range(n_fragments)]
+            pool.starmap(process_single_fragment, args)
     else:
         for fragment_id in range(n_fragments):
             process_single_fragment(fragment_id, color_files, depth_files,