def enqueue_packet(project_string_id,
session,
media_url = None,
media_type = None,
file_id = None,
file_name = None,
job_id = None,
batch_id = None,
directory_id = None,
source_directory_id = None,
instance_list = None,
video_split_duration = None,
frame_packet_map = None,
remove_link = None,
add_link = None,
copy_instance_list = None,
commit_input = False,
task_id = None,
video_parent_length = None,
type = None,
task_action = None,
external_map_id = None,
original_filename = None,
external_map_action = None,
enqueue_immediately = False,
mode = None,
allow_duplicates = False,
extract_labels_from_batch = False):
"""
Creates Input() object and enqueues it for media processing
Returns Input() object that was created
:param packet_data:
:return:
"""
diffgram_input = Input()
project = Project.get(session, project_string_id)
diffgram_input.file_id = file_id
diffgram_input.task_id = task_id
diffgram_input.batch_id = batch_id
diffgram_input.video_parent_length = video_parent_length
diffgram_input.remove_link = remove_link
diffgram_input.add_link = add_link
diffgram_input.copy_instance_list = copy_instance_list
diffgram_input.external_map_id = external_map_id
diffgram_input.original_filename = original_filename
diffgram_input.external_map_action = external_map_action
diffgram_input.task_action = task_action
diffgram_input.mode = mode
diffgram_input.project = project
diffgram_input.media_type = media_type
diffgram_input.type = "from_url"
diffgram_input.url = media_url
diffgram_input.video_split_duration = video_split_duration
diffgram_input.allow_duplicates = allow_duplicates
if instance_list:
diffgram_input.instance_list = {}
diffgram_input.instance_list['list'] = instance_list
if frame_packet_map:
diffgram_input.frame_packet_map = frame_packet_map
# print(diffgram_input.frame_packet_map)
session.add(diffgram_input)
session.flush()
if batch_id and extract_labels_from_batch:
upload_tools = Upload(session = session, project = project, request = None)
upload_tools.extract_instance_list_from_batch(input = diffgram_input,
input_batch_id = batch_id,
file_name = file_name)
# Expect temp dir to be None here.
# because each machine should assign it's own temp dir
# Something else to consider for future here!
# Once this is part of input, it will be smoothly handled at right time as part of
# processing queue
diffgram_input.job_id = job_id
# Process media handles checking if the directory id is valid
diffgram_input.directory_id = directory_id
diffgram_input.source_directory_id = source_directory_id
diffgram_input_id = diffgram_input.id
queue_limit = 0
if media_type == "image":
queue_limit = 30 # 50
if media_type == "video":
queue_limit = 1
if settings.PROCESS_MEDIA_ENQUEUE_LOCALLY_IMMEDIATELY is True or enqueue_immediately:
print('diffgram_input_id', diffgram_input_id)
if commit_input:
regular_methods.commit_with_rollback(session = session)
item = PrioritizedItem(
priority = 10000, # individual frames have a priority here.
input_id = diffgram_input_id,
media_type = media_type)
add_item_to_queue(item)
else:
diffgram_input.processing_deferred = True # Default
return diffgram_input
def add_frame_to_queue(self,
frame,
index: int,
original_filename: str,
project: Project,
directory_id,
video,
length,
video_parent_file: File,
global_frame_number=None,
initial_global_frame=None):
"""
Where frame is:
a HxWxN np.array, where N=1 for mask clips and N=3 for RGB clips.
https://zulko.github.io/moviepy/ref/VideoClip/VideoClip.html
Careful we don't have self. context here
Cautions
* We purposely do not not pass the job id, since we only want to original
video to be added to the job
Question,
is it correct we create input class in part to maintain
same concepts / format even for video frames?
Answer: For example see frame_end_number is used to pass information
Makes more sense to have it all in there then the PrioritizedItem() thing
long term
Also thinking in terms of logging
And yes of course, then it's complete reuse of the component
Jan 20, 2020
Note we purposely do NOT commit this as it creates unneeded
db overhead, so instead we only use it as a local object
to maintain consistency of design
which means we do NOT want to add to add it a sesion
ie self.session.add(input)
"""
input = Input()
# Use input for class attributes,
# but don't add it to the session for video?
# TODO use File.new() for consistency here (ie as we add new things)
# Single frame naming
input.original_filename = original_filename + "_" + str(index)
input.extension = ".jpg"
input.media_type = "frame"
input.temp_dir = tempfile.mkdtemp()
input.project = project
input.directory_id = directory_id
input.parent_file_id = video_parent_file.id
input.frame_packet_map = self.input.frame_packet_map
# caution length is estimated. frame_count
# is calculated as we roll through this so can't use it yet
# Question: clarity on difference between numbers.
# (I know estimate but still.)
input.video_parent_length = length
input.parent_input_id = self.input.id
input.project_id = self.project.id
# This is a temporary usage thing only
# Note database persisted
# Context of needing it to be defined so existing instances
# Can use it (vs having to get video from db each time,
# prior we defined this on first frame.
input.root_blob_path_to_frames = video.root_blob_path_to_frames
input = self.get_instance_list_from_packet_map(
input=input,
frame_number=index,
global_frame_number=global_frame_number,
initial_global_frame=initial_global_frame,
from_video_split=self.input.type == 'from_video_split')
"""
For frame priority, the original genesis was doing the last frame last
but, I think it also makese sense to process in order in general.
An alternative would be to say put a flag on the last frame
but using order feels like a more general solution, assuming no suprises
or extra overhead.
Storing frames
Maybe don't attach video_parent_file
because it leads to not bound errors in ORM fairly easily.
"""
# TODO, consider sending data as a "raw" blob
# to cloud storage, then setting "processing deferred" to True here.
# Process frames of videos started before new videos
item = process_media.PrioritizedItem(
priority=100 + index, # Process in frame priority
input=input,
raw_numpy_image=frame,
file_is_numpy_array=True,
video_id=video.id,
frame_number=index,
global_frame_number=global_frame_number,
media_type=input.media_type)
process_media.add_item_to_queue(item)