kopia lustrzana https://github.com/OpenDroneMap/ODM
516 wiersze
21 KiB
Python
516 wiersze
21 KiB
Python
import time
|
|
import datetime
|
|
import os
|
|
import sys
|
|
import threading
|
|
import signal
|
|
import zipfile
|
|
import glob
|
|
from opendm import log
|
|
from opendm import system
|
|
from opendm import config
|
|
from pyodm import Node, exceptions
|
|
from pyodm.utils import AtomicCounter
|
|
from pyodm.types import TaskStatus
|
|
from opendm.osfm import OSFMContext, get_submodel_args_dict, get_submodel_argv
|
|
from opendm.utils import double_quote
|
|
|
|
try:
|
|
import queue
|
|
except ImportError:
|
|
import Queue as queue
|
|
|
|
class LocalRemoteExecutor:
|
|
"""
|
|
A class for performing OpenSfM reconstructions and full ODM pipeline executions
|
|
using a mix of local and remote processing. Tasks are executed locally one at a time
|
|
and remotely until a node runs out of available slots for processing. This allows us
|
|
to use the processing power of the current machine as well as offloading tasks to a
|
|
network node.
|
|
"""
|
|
def __init__(self, nodeUrl, rolling_shutter = False, rerun = False):
|
|
self.node = Node.from_url(nodeUrl)
|
|
self.params = {
|
|
'tasks': [],
|
|
'threads': [],
|
|
'rolling_shutter': rolling_shutter,
|
|
'rerun': rerun
|
|
}
|
|
self.node_online = True
|
|
|
|
log.ODM_INFO("LRE: Initializing using cluster node %s:%s" % (self.node.host, self.node.port))
|
|
try:
|
|
info = self.node.info()
|
|
log.ODM_INFO("LRE: Node is online and running %s version %s" % (info.engine, info.engine_version))
|
|
except exceptions.NodeConnectionError:
|
|
log.ODM_WARNING("LRE: The node seems to be offline! We'll still process the dataset, but it's going to run entirely locally.")
|
|
self.node_online = False
|
|
except Exception as e:
|
|
raise system.ExitException("LRE: An unexpected problem happened while opening the node connection: %s" % str(e))
|
|
|
|
def set_projects(self, paths):
|
|
self.project_paths = paths
|
|
|
|
def run_reconstruction(self):
|
|
self.run(ReconstructionTask)
|
|
|
|
def run_toolchain(self):
|
|
self.run(ToolchainTask)
|
|
|
|
def run(self, taskClass):
|
|
if not self.project_paths:
|
|
return
|
|
|
|
# Shared variables across threads
|
|
class nonloc:
|
|
error = None
|
|
local_processing = False
|
|
max_remote_tasks = None
|
|
|
|
calculate_task_limit_lock = threading.Lock()
|
|
finished_tasks = AtomicCounter(0)
|
|
remote_running_tasks = AtomicCounter(0)
|
|
|
|
# Create queue
|
|
q = queue.Queue()
|
|
for pp in self.project_paths:
|
|
log.ODM_INFO("LRE: Adding to queue %s" % pp)
|
|
q.put(taskClass(pp, self.node, self.params))
|
|
|
|
def remove_task_safe(task):
|
|
try:
|
|
removed = task.remove()
|
|
except exceptions.OdmError:
|
|
removed = False
|
|
return removed
|
|
|
|
def cleanup_remote_tasks():
|
|
if self.params['tasks']:
|
|
log.ODM_WARNING("LRE: Attempting to cleanup remote tasks")
|
|
else:
|
|
log.ODM_INFO("LRE: No remote tasks left to cleanup")
|
|
|
|
for task in self.params['tasks']:
|
|
log.ODM_INFO("LRE: Removing remote task %s... %s" % (task.uuid, 'OK' if remove_task_safe(task) else 'NO'))
|
|
|
|
def handle_result(task, local, error = None, partial=False):
|
|
def cleanup_remote():
|
|
if not partial and task.remote_task:
|
|
log.ODM_INFO("LRE: Cleaning up remote task (%s)... %s" % (task.remote_task.uuid, 'OK' if remove_task_safe(task.remote_task) else 'NO'))
|
|
self.params['tasks'].remove(task.remote_task)
|
|
task.remote_task = None
|
|
|
|
if error:
|
|
log.ODM_WARNING("LRE: %s failed with: %s" % (task, str(error)))
|
|
|
|
# Special case in which the error is caused by a SIGTERM signal
|
|
# this means a local processing was terminated either by CTRL+C or
|
|
# by canceling the task.
|
|
if str(error) == "Child was terminated by signal 15":
|
|
system.exit_gracefully()
|
|
|
|
task_limit_reached = isinstance(error, NodeTaskLimitReachedException)
|
|
if task_limit_reached:
|
|
# Estimate the maximum number of tasks based on how many tasks
|
|
# are currently running
|
|
with calculate_task_limit_lock:
|
|
if nonloc.max_remote_tasks is None:
|
|
node_task_limit = 0
|
|
for t in self.params['tasks']:
|
|
try:
|
|
info = t.info(with_output=-3)
|
|
if info.status == TaskStatus.RUNNING and info.processing_time >= 0 and len(info.output) >= 3:
|
|
node_task_limit += 1
|
|
except exceptions.OdmError:
|
|
pass
|
|
|
|
nonloc.max_remote_tasks = max(1, node_task_limit)
|
|
log.ODM_INFO("LRE: Node task limit reached. Setting max remote tasks to %s" % node_task_limit)
|
|
|
|
|
|
# Retry, but only if the error is not related to a task failure
|
|
if task.retries < task.max_retries and not isinstance(error, exceptions.TaskFailedError):
|
|
# Put task back in queue
|
|
# Don't increment the retry counter if this task simply reached the task
|
|
# limit count.
|
|
if not task_limit_reached:
|
|
task.retries += 1
|
|
task.wait_until = datetime.datetime.now() + datetime.timedelta(seconds=task.retries * task.retry_timeout)
|
|
cleanup_remote()
|
|
q.task_done()
|
|
|
|
log.ODM_INFO("LRE: Re-queueing %s (retries: %s)" % (task, task.retries))
|
|
q.put(task)
|
|
if not local: remote_running_tasks.increment(-1)
|
|
return
|
|
else:
|
|
nonloc.error = error
|
|
finished_tasks.increment()
|
|
if not local: remote_running_tasks.increment(-1)
|
|
else:
|
|
if not partial:
|
|
log.ODM_INFO("LRE: %s finished successfully" % task)
|
|
finished_tasks.increment()
|
|
if not local: remote_running_tasks.increment(-1)
|
|
|
|
cleanup_remote()
|
|
if not partial: q.task_done()
|
|
|
|
def local_worker():
|
|
while True:
|
|
# Block until a new queue item is available
|
|
task = q.get()
|
|
|
|
if task is None or nonloc.error is not None:
|
|
q.task_done()
|
|
break
|
|
|
|
# Process local
|
|
try:
|
|
nonloc.local_processing = True
|
|
task.process(True, handle_result)
|
|
except Exception as e:
|
|
handle_result(task, True, e)
|
|
finally:
|
|
nonloc.local_processing = False
|
|
|
|
|
|
def remote_worker():
|
|
while True:
|
|
# Block until a new queue item is available
|
|
task = q.get()
|
|
|
|
if task is None or nonloc.error is not None:
|
|
q.task_done()
|
|
break
|
|
|
|
# Yield to local processing
|
|
if not nonloc.local_processing:
|
|
log.ODM_INFO("LRE: Yielding to local processing, sending %s back to the queue" % task)
|
|
q.put(task)
|
|
q.task_done()
|
|
time.sleep(0.05)
|
|
continue
|
|
|
|
# If we've found an estimate of the limit on the maximum number of tasks
|
|
# a node can process, we block until some tasks have completed
|
|
if nonloc.max_remote_tasks is not None and remote_running_tasks.value >= nonloc.max_remote_tasks:
|
|
q.put(task)
|
|
q.task_done()
|
|
time.sleep(2)
|
|
continue
|
|
|
|
# Process remote
|
|
try:
|
|
remote_running_tasks.increment()
|
|
task.process(False, handle_result)
|
|
except Exception as e:
|
|
handle_result(task, False, e)
|
|
|
|
# Create queue thread
|
|
local_thread = threading.Thread(target=local_worker)
|
|
if self.node_online:
|
|
remote_thread = threading.Thread(target=remote_worker)
|
|
|
|
system.add_cleanup_callback(cleanup_remote_tasks)
|
|
|
|
# Start workers
|
|
local_thread.start()
|
|
if self.node_online:
|
|
remote_thread.start()
|
|
|
|
# block until all tasks are done (or CTRL+C)
|
|
try:
|
|
while finished_tasks.value < len(self.project_paths) and nonloc.error is None:
|
|
time.sleep(0.5)
|
|
except KeyboardInterrupt:
|
|
log.ODM_WARNING("LRE: CTRL+C")
|
|
system.exit_gracefully()
|
|
|
|
# stop workers
|
|
q.put(None)
|
|
if self.node_online:
|
|
q.put(None)
|
|
|
|
# Wait for queue thread
|
|
local_thread.join()
|
|
if self.node_online:
|
|
remote_thread.join()
|
|
|
|
# Wait for all remains threads
|
|
for thrds in self.params['threads']:
|
|
thrds.join()
|
|
|
|
system.remove_cleanup_callback(cleanup_remote_tasks)
|
|
cleanup_remote_tasks()
|
|
|
|
if nonloc.error is not None:
|
|
# Try not to leak access token
|
|
if isinstance(nonloc.error, exceptions.NodeConnectionError):
|
|
raise exceptions.NodeConnectionError("A connection error happened. Check the connection to the processing node and try again.")
|
|
else:
|
|
raise nonloc.error
|
|
|
|
|
|
class NodeTaskLimitReachedException(Exception):
|
|
pass
|
|
|
|
class Task:
|
|
def __init__(self, project_path, node, params, max_retries=5, retry_timeout=10):
|
|
self.project_path = project_path
|
|
self.node = node
|
|
self.params = params
|
|
self.wait_until = datetime.datetime.now() # Don't run this task until a certain time
|
|
self.max_retries = max_retries
|
|
self.retries = 0
|
|
self.retry_timeout = retry_timeout
|
|
self.remote_task = None
|
|
|
|
def process(self, local, done):
|
|
def handle_result(error = None, partial=False):
|
|
done(self, local, error, partial)
|
|
|
|
log.ODM_INFO("LRE: About to process %s %s" % (self, 'locally' if local else 'remotely'))
|
|
|
|
if local:
|
|
self._process_local(handle_result) # Block until complete
|
|
else:
|
|
now = datetime.datetime.now()
|
|
if self.wait_until > now:
|
|
wait_for = (self.wait_until - now).seconds + 1
|
|
log.ODM_INFO("LRE: Waiting %s seconds before processing %s" % (wait_for, self))
|
|
time.sleep(wait_for)
|
|
|
|
# TODO: we could consider uploading multiple tasks
|
|
# in parallel. But since we are using the same node
|
|
# perhaps this wouldn't be a big speedup.
|
|
self._process_remote(handle_result) # Block until upload is complete
|
|
|
|
def path(self, *paths):
|
|
return os.path.join(self.project_path, *paths)
|
|
|
|
def touch(self, file):
|
|
with open(file, 'w') as fout:
|
|
fout.write("Done!\n")
|
|
|
|
def create_seed_payload(self, paths, touch_files=[]):
|
|
paths = filter(os.path.exists, map(lambda p: self.path(p), paths))
|
|
outfile = self.path("seed.zip")
|
|
|
|
with zipfile.ZipFile(outfile, "w", compression=zipfile.ZIP_DEFLATED, allowZip64=True) as zf:
|
|
for p in paths:
|
|
if os.path.isdir(p):
|
|
for root, _, filenames in os.walk(p):
|
|
for filename in filenames:
|
|
filename = os.path.join(root, filename)
|
|
filename = os.path.normpath(filename)
|
|
zf.write(filename, os.path.relpath(filename, self.project_path))
|
|
else:
|
|
zf.write(p, os.path.relpath(p, self.project_path))
|
|
|
|
for tf in touch_files:
|
|
zf.writestr(tf, "")
|
|
|
|
return outfile
|
|
|
|
def _process_local(self, done):
|
|
try:
|
|
self.process_local()
|
|
done()
|
|
except Exception as e:
|
|
done(e)
|
|
|
|
def _process_remote(self, done):
|
|
try:
|
|
self.process_remote(done)
|
|
done(error=None, partial=True) # Upload is completed, but processing is not (partial)
|
|
except Exception as e:
|
|
done(e)
|
|
|
|
def execute_remote_task(self, done, seed_files = [], seed_touch_files = [], outputs = [], ):
|
|
"""
|
|
Run a task by creating a seed file with all files in seed_files, optionally
|
|
creating empty files (for flag checks) specified in seed_touch_files
|
|
and returning the results specified in outputs. Yeah it's pretty cool!
|
|
"""
|
|
seed_file = self.create_seed_payload(seed_files, touch_files=seed_touch_files)
|
|
|
|
# Find all images
|
|
images = glob.glob(self.path("images/**"))
|
|
|
|
# Add GCP (optional)
|
|
if os.path.exists(self.path("gcp_list.txt")):
|
|
images.append(self.path("gcp_list.txt"))
|
|
|
|
# Add GEO (optional)
|
|
if os.path.exists(self.path("geo.txt")):
|
|
images.append(self.path("geo.txt"))
|
|
|
|
# Add seed file
|
|
images.append(seed_file)
|
|
|
|
class nonloc:
|
|
last_update = 0
|
|
|
|
def print_progress(percentage):
|
|
if (time.time() - nonloc.last_update >= 2) or int(percentage) == 100:
|
|
log.ODM_INFO("LRE: Upload of %s at [%s%%]" % (self, int(percentage)))
|
|
nonloc.last_update = time.time()
|
|
|
|
# Upload task
|
|
task = self.node.create_task(images,
|
|
get_submodel_args_dict(config.config()),
|
|
progress_callback=print_progress,
|
|
skip_post_processing=True,
|
|
outputs=outputs)
|
|
self.remote_task = task
|
|
|
|
# Cleanup seed file
|
|
os.remove(seed_file)
|
|
|
|
# Keep track of tasks for cleanup
|
|
self.params['tasks'].append(task)
|
|
|
|
# Check status
|
|
info = task.info()
|
|
if info.status in [TaskStatus.RUNNING, TaskStatus.COMPLETED]:
|
|
def monitor():
|
|
class nonloc:
|
|
status_callback_calls = 0
|
|
last_update = 0
|
|
|
|
def status_callback(info):
|
|
# If a task switches from RUNNING to QUEUED, then we need to
|
|
# stop the process and re-add the task to the queue.
|
|
if info.status == TaskStatus.QUEUED:
|
|
log.ODM_WARNING("LRE: %s (%s) turned from RUNNING to QUEUED. Re-adding to back of the queue." % (self, task.uuid))
|
|
raise NodeTaskLimitReachedException("Delayed task limit reached")
|
|
elif info.status == TaskStatus.RUNNING:
|
|
# Print a status message once in a while
|
|
nonloc.status_callback_calls += 1
|
|
if nonloc.status_callback_calls > 30:
|
|
log.ODM_INFO("LRE: %s (%s) is still running" % (self, task.uuid))
|
|
nonloc.status_callback_calls = 0
|
|
try:
|
|
def print_progress(percentage):
|
|
if (time.time() - nonloc.last_update >= 2) or int(percentage) == 100:
|
|
log.ODM_INFO("LRE: Download of %s at [%s%%]" % (self, int(percentage)))
|
|
nonloc.last_update = time.time()
|
|
|
|
task.wait_for_completion(status_callback=status_callback)
|
|
log.ODM_INFO("LRE: Downloading assets for %s" % self)
|
|
task.download_assets(self.project_path, progress_callback=print_progress)
|
|
log.ODM_INFO("LRE: Downloaded and extracted assets for %s" % self)
|
|
done()
|
|
except exceptions.TaskFailedError as e:
|
|
# Try to get output
|
|
try:
|
|
output_lines = task.output()
|
|
|
|
# Save to file
|
|
error_log_path = self.path("error.log")
|
|
with open(error_log_path, 'w') as f:
|
|
f.write('\n'.join(output_lines) + '\n')
|
|
|
|
msg = "(%s) failed with task output: %s\nFull log saved at %s" % (task.uuid, "\n".join(output_lines[-10:]), error_log_path)
|
|
done(exceptions.TaskFailedError(msg))
|
|
except:
|
|
log.ODM_WARNING("LRE: Could not retrieve task output for %s (%s)" % (self, task.uuid))
|
|
done(e)
|
|
except Exception as e:
|
|
done(e)
|
|
|
|
# Launch monitor thread and return
|
|
t = threading.Thread(target=monitor)
|
|
self.params['threads'].append(t)
|
|
t.start()
|
|
elif info.status == TaskStatus.QUEUED:
|
|
raise NodeTaskLimitReachedException("Task limit reached")
|
|
else:
|
|
raise Exception("Could not send task to node, task status is %s" % str(info.status))
|
|
|
|
|
|
def process_local(self):
|
|
raise NotImplementedError()
|
|
|
|
def process_remote(self, done):
|
|
raise NotImplementedError()
|
|
|
|
def __str__(self):
|
|
return os.path.basename(self.project_path)
|
|
|
|
|
|
class ReconstructionTask(Task):
|
|
def process_local(self):
|
|
octx = OSFMContext(self.path("opensfm"))
|
|
log.ODM_INFO("==================================")
|
|
log.ODM_INFO("Local Reconstruction %s" % octx.name())
|
|
log.ODM_INFO("==================================")
|
|
octx.feature_matching(self.params['rerun'])
|
|
octx.create_tracks(self.params['rerun'])
|
|
octx.reconstruct(self.params['rolling_shutter'], True, self.params['rerun'])
|
|
|
|
def process_remote(self, done):
|
|
octx = OSFMContext(self.path("opensfm"))
|
|
if not octx.is_feature_matching_done() or not octx.is_reconstruction_done() or self.params['rerun']:
|
|
self.execute_remote_task(done, seed_files=["opensfm/exif",
|
|
"opensfm/camera_models.json",
|
|
"opensfm/reference_lla.json"],
|
|
seed_touch_files=["opensfm/split_merge_stop_at_reconstruction.txt"],
|
|
outputs=["opensfm/matches", "opensfm/features",
|
|
"opensfm/reconstruction.json",
|
|
"opensfm/tracks.csv",
|
|
"cameras.json"])
|
|
else:
|
|
log.ODM_INFO("Already processed feature matching and reconstruction for %s" % octx.name())
|
|
done()
|
|
|
|
class ToolchainTask(Task):
|
|
def process_local(self):
|
|
completed_file = self.path("toolchain_completed.txt")
|
|
submodel_name = os.path.basename(self.project_path)
|
|
|
|
if not os.path.exists(completed_file) or self.params['rerun']:
|
|
log.ODM_INFO("=============================")
|
|
log.ODM_INFO("Local Toolchain %s" % self)
|
|
log.ODM_INFO("=============================")
|
|
|
|
submodels_path = os.path.abspath(self.path(".."))
|
|
argv = get_submodel_argv(config.config(), submodels_path, submodel_name)
|
|
|
|
# Re-run the ODM toolchain on the submodel
|
|
system.run(" ".join(map(double_quote, map(str, argv))), env_vars=os.environ.copy())
|
|
|
|
# This will only get executed if the command above succeeds
|
|
self.touch(completed_file)
|
|
else:
|
|
log.ODM_INFO("Already processed toolchain for %s" % submodel_name)
|
|
|
|
def process_remote(self, done):
|
|
completed_file = self.path("toolchain_completed.txt")
|
|
submodel_name = os.path.basename(self.project_path)
|
|
|
|
def handle_result(error = None):
|
|
# Mark task as completed if no error
|
|
if error is None:
|
|
self.touch(completed_file)
|
|
done(error=error)
|
|
|
|
if not os.path.exists(completed_file) or self.params['rerun']:
|
|
self.execute_remote_task(handle_result, seed_files=["opensfm/camera_models.json",
|
|
"opensfm/reference_lla.json",
|
|
"opensfm/reconstruction.json",
|
|
"opensfm/tracks.csv"],
|
|
seed_touch_files=["opensfm/features/empty",
|
|
"opensfm/matches/empty",
|
|
"opensfm/exif/empty"],
|
|
outputs=["odm_orthophoto/cutline.gpkg",
|
|
"odm_orthophoto/odm_orthophoto_cut.tif",
|
|
"odm_orthophoto/odm_orthophoto_feathered.tif",
|
|
"odm_dem",
|
|
"odm_report",
|
|
"odm_georeferencing"])
|
|
else:
|
|
log.ODM_INFO("Already processed toolchain for %s" % submodel_name)
|
|
handle_result()
|