Improved Resolve render and ingest

storytoolkitai/core/toolkit_ops/toolkit_ops.py

@@ -3401,10 +3401,11 @@ def start_resolve_render_and_monitor(self, monitor_callback: callable=None, **kw
  render_file_paths.append(os.path.join(render_job['TargetDir'], render_job['OutputFilename']))
 
  # when mots_resolve finishes the render job,
- # it should also add a .json file with the same name
+ # it should also add a .json file with the same name,
  # so we'll just monitor to see if the .json file is there
  # monitoring the rendered file itself not might be a good idea
  # since it might already exist before the render is done
+ # we will call this file the render.json file
  monitor_file_path = str(render_job['OutputFilename']) + '.json'
 
  # delete the file we're monitoring if it's already there
@@ -3516,9 +3517,8 @@ def check_process(wait_time=2):
  check_times += 1
 
  if check_times >= 10:
- logger.error("CLI subprocess is still running after {} seconds. Assuming render is running."
- "Aborting check function to save resources."
- .format(wait_time * check_times))
+ logger.info("CLI subprocess is still running after {} seconds. Assuming render is running. "
+ "Aborting check function to save resources.".format(wait_time * check_times))
 
  # check one more time if the process is still running
  exit_code = process.poll()

storytoolkitai/ui/toolkit_ui.py

@@ -7111,20 +7111,15 @@ def button_nle_transcribe_timeline(self, transcription_task='transcribe', **kwar
  Used to render a timeline in Resolve and add it to the ingest window, once it's rendered
  """
 
- # get info from resolve
- # todo: this needs to be done using the NLE object in the future
- try:
- resolve_data = self.toolkit_ops_obj.resolve_api.get_resolve_data()
- # in case of exception still create a dict with an empty resolve object
- except:
- resolve_data = {'resolve': None}
+ # get the current NLE timeline if it exists
+ nle_current_timeline_name = NLE.current_timeline.get('name', None) \
+ if NLE and hasattr(NLE, 'current_timeline') else None
 
  # set an empty target directory for future use
  target_dir = ''
+ file_name = None
 
- if resolve_data is not None and resolve_data['resolve'] != None \
- and 'currentTimeline' in resolve_data and \
- resolve_data['currentTimeline'] != '' and resolve_data['currentTimeline'] is not None:
+ if nle_current_timeline_name:
 
  # use the initial dir of the project if we are in one
  initial_target_dir = self.get_project_last_target_dir(self.current_project)
@@ -7133,16 +7128,13 @@ def button_nle_transcribe_timeline(self, transcription_task='transcribe', **kwar
  if not initial_target_dir:
  initial_target_dir = self.stAI.initial_target_dir
 
- # get the current timeline from Resolve
- currentTimelineName = resolve_data['currentTimeline']['name']
-
  # ask the user where to save the files
  while target_dir == '' or not os.path.exists(os.path.join(target_dir)):
- logger.info("Prompting user for render path.")
+ logger.debug("Ingesting NLE timeline - Prompting user for render path.")
  # target_dir = self.ask_for_target_dir(target_dir=last_target_dir)
 
  target_file = self.ask_for_save_file(target_dir=initial_target_dir,
- initialfile=currentTimelineName
+ initialfile=nle_current_timeline_name
  )
  if target_file:
  # get the file_name
@@ -7157,23 +7149,19 @@ def button_nle_transcribe_timeline(self, transcription_task='transcribe', **kwar
 
  # cancel if the user presses cancel
  if not target_dir:
- logger.info("User canceled transcription operation.")
+ logger.debug("Ingesting NLE timeline stopped - User canceled operation.")
  return
 
- # send the timeline name via kwargs
- kwargs['timeline_name'] = currentTimelineName
-
- # get the current project name from Resolve
- if 'currentProject' in resolve_data and resolve_data['currentProject'] is not None:
- # get the project name from Resolve
- kwargs['project_name'] = resolve_data['currentProject']
-
  # suspend NLE polling while we're rendering
  NLE.suspend_polling = True
 
  # and wait for a second to make sure that the last poll was executed
  time.sleep(1)
 
+ if not file_name:
+ logger.warning("Ingesting NLE timeline stopped - File name not defined.")
+ return
+
  # generate a unique id to keep track of this file in the queue and transcription log
  if kwargs.get('queue_id', None) is None:
  kwargs['queue_id'] = self.toolkit_ops_obj.processing_queue.generate_queue_id(name=file_name)
@@ -7197,18 +7185,23 @@ def button_nle_transcribe_timeline(self, transcription_task='transcribe', **kwar
  self.notify_via_os("Starting Render", "Starting Render in Resolve",
  "Saving into {} and starting render.".format(target_dir))
 
- render_monitor, render_file_paths \
- = self.toolkit_ops_obj.start_resolve_render_and_monitor(
- target_dir=target_dir, render_preset=render_preset, start_render=False,
- add_file_suffix=False, add_date=False, add_timestamp=True, file_name=file_name,
- )
+ render_monitor, render_file_paths = \
+ self.toolkit_ops_obj.start_resolve_render_and_monitor(
+  target_dir=target_dir, render_preset=render_preset, start_render=False,
+  add_file_suffix=False, add_date=False, add_timestamp=True, file_name=file_name,
+  )
 
- # turn the rendered files into a string separated by commas with each element between double quotes
+ # turn the rendered files into a string separated by commas with each element between double quotes,
  # so they fit the files input in the ingest window
  if len(render_file_paths) > 1:
  render_file_paths = ', '.join(['"{}"'.format(f) for f in render_file_paths])
  else:
- render_file_paths = '{}'.format(render_file_paths[0])
+ # add double quotes to the file path if it contains spaces or commas
+ if ' ' in render_file_paths[0] or ',' in render_file_paths[0]:
+ render_file_paths = '"{}"'.format(render_file_paths[0])
+
+ else:
+ render_file_paths = '{}'.format(render_file_paths[0])
 
  # add the done function to the render monitor
  # - when the monitor reaches the done state, it will call the function button_transcribe