def add_network_tasks_to_queue(chunks, tasks):
"""Adds network tasks to queue."""
network_tasks = []
network_client = PhotoScan.NetworkClient()
network_client.connect(SERVER_IP)
for task_parameters in tasks:
new_network_task = PhotoScan.NetworkTask()
for chunk in chunks:
new_network_task.frames.append((chunk.key, 0))
new_network_task.name = task_parameters['name']
for key in task_parameters:
if key != 'name':
new_network_task.params[key] = task_parameters[key]
network_tasks.append(new_network_task)
network_save = PhotoScan.app.document.path.replace(SHARED_ROOT, '')
batch_id = network_client.createBatch(network_save, network_tasks)
network_client.resumeBatch(batch_id)
def runNetwork(project_path,
argstring,
tname='RunScript',
PSscript='scripts/reef3D/PyToolbox/PSmodel.py'):
''''
Run a task over the network
'''
client = PhotoScan.NetworkClient()
task1 = PhotoScan.NetworkTask()
task1.name = tname
task1.params['path'] = PSscript #path to the script to be executed
task1.params[
'args'] = argstring #string of the arguments with space as separator
client.connect('agisoft-qmgr.aims.gov.au') #server ip
batch_id = client.createBatch(proj_path, [task1])
client.resumeBatch(batch_id)
print("Job started...")
def runNetwork(proj_path,
argstring,
tname='RunScript',
PSscript='scripts/reef3D/PyToolbox/PSmodel.py'):
''''
Run a task over the network
'''
client = PhotoScan.NetworkClient()
# VIDEO_FILENAME=argstring.split(" ")[2]
# VIDEO_FILENAME=VIDEO_FILENAME.strip('"')
# doc = PhotoScan.Document(os.path.join(proj_dir,VIDEO_FILENAME + '.psx'))
# doc.open("...")
task1 = PhotoScan.NetworkTask()
task1.name = tname
task1.params['path'] = PSscript #path to the script to be executed
task1.params[
'args'] = argstring #string of the arguments with space as separator
client.connect('agisoft-qmgr.aims.gov.au') #server ip
batch_id = client.createBatch(proj_path, [task1])
client.resumeBatch(batch_id)
client.disconnect()
print("Job started...")
def export_ortho(
self, proc_type
): # универсальная процедура экспорта для локлаьной и для сетевой обработки
#global chunk
''' ЭТО ПРОВЕРКА ДЛЯ ПОСТРОЕНИЯ ОРТО ПЕРЕД РАБОТОЙ В ТЕКУЩЕЙ ВЕРСИИ ФУНКЦИЯ ОТКЛЮЧЕНА!!
if self.checkExportOrtho.isChecked()==True:
statOrthoBuild=True
else:
statOrthoBuild=False
# 000000 Проверка на наличие ортофото или дем перед работой
if (doc.chunk.orthomosaic==None and statOrthoBuild==False):
PhotoScan.app.messageBox('Нет орто!!')
return
elif (doc.chunk.elevation==None and statOrthoBuild==True):
PhotoScan.app.messageBox('Нет ДЕМ!!')
return
'''
#Определение вида экспорта - орто или дем
if self.CheckOrtho_Radio.isChecked() == True:
ExportType = 'ORTHO'
elif self.CheckDem_Radio.isChecked() == True:
ExportType = 'DEM'
else:
AssertionError("Какой процесс экспорта?")
#ПРОВЕРКИ НАЛИЧИЯ ДЕМ И ОРТО
if (doc.chunk.orthomosaic == None and ExportType == 'ORTHO'):
PhotoScan.app.messageBox('Нет орто!!')
return
elif (doc.chunk.elevation == None and ExportType == 'DEM'):
PhotoScan.app.messageBox('Нет ДЕМ!!')
return
file_format = self.file_format.currentText()
print('orthoBounds=', len(self.orthoBounds))
task = [] #Это СПИСОК тасков
DifPix = float(self.dif_pix.text())
if self.block_size.currentText() == 'Full':
BlockSize = 0
else:
BlockSize = int(self.block_size.currentText())
# Цикл для запуска ортофото локально или для забивания стека на сеть из массива
try:
for cu_string in self.orthoBounds:
OName = cu_string[0]
XMLeft = float(cu_string[1])
YMDown = float(cu_string[2])
sizeXM = float(cu_string[3])
sizeYM = float(cu_string[4])
shapeNumber = int(cu_string[5])
cu_Region = self.OrthoBoundCalc(
XMLeft, YMDown, sizeXM, sizeYM
) #Функция вычисления границ # изменить под сетевую обработку с тайлами
if file_format == 'JPG' and ExportType == 'ORTHO':
fileoutname = self.OUT_dir + "\\ortho_" + OName + ".jpg"
elif file_format == 'TIF' and ExportType == 'ORTHO':
fileoutname = self.OUT_dir + "\\ortho_" + OName + ".tif"
elif file_format == 'TIF' and ExportType == 'DEM':
fileoutname = self.OUT_dir + "\\dem_" + OName + ".tif"
else:
print("Формат файла?")
if proc_type == 'local': #КОММАНДЫ для локальной обработки
print('Обработка локально')
''' ПОСТРОЕНИЕ ОРТОФОТО В ЭТОЙ ВЕРСИИ ОТКЛЮЧЕНО
if statOrthoBuild==True:
#chunk.buildOrthomosaic(surface=PhotoScan.ElevationData, blending=PhotoScan.MosaicBlending, color_correction=False, projection=self.out_crs, region=cu_Region,dx=DifPix, dy=DifPix)
chunk.buildOrthomosaic(surface=PhotoScan.ElevationData, blending=PhotoScan.MosaicBlending, projection=self.out_crs, region=cu_Region,dx=DifPix, dy=DifPix)
'''
if CommandStack == 1 and ExportType == 'ORTHO':
if file_format == 'JPG':
chunk.exportOrthomosaic(fileoutname,
format="jpg",
projection=self.out_crs,
region=cu_Region,
dx=DifPix,
dy=DifPix,
blockw=BlockSize,
blockh=BlockSize,
write_kml=False,
write_world=True)
elif file_format == 'TIF':
chunk.exportOrthomosaic(fileoutname,
format="tif",
projection=self.out_crs,
region=cu_Region,
dx=DifPix,
dy=DifPix,
blockw=BlockSize,
blockh=BlockSize,
write_kml=False,
write_world=True,
tiff_compression="jpeg",
tiff_big=False)
#сжатие LZW
#elif file_format=='TIF': chunk.exportOrthomosaic(fileoutname, format="tif", region=cu_Region, projection=self.out_crs,dx=DifPix, dy=DifPix, blockw=BlockSize, blockh=BlockSize, write_kml=False, write_world=True, tiff_compression="lzw", tiff_big=False)
else:
print("Формат файла?")
elif CommandStack == 5 and ExportType == 'ORTHO':
if file_format == 'JPG':
chunk.exportOrthomosaic(
fileoutname,
PhotoScan.RasterFormatTiles,
PhotoScan.ImageFormatJPEG,
region=cu_Region,
projection=self.out_crs,
dx=DifPix,
dy=DifPix,
blockw=BlockSize,
blockh=BlockSize,
write_kml=False,
write_world=True)
elif file_format == 'TIF':
chunk.exportOrthomosaic(
fileoutname,
PhotoScan.RasterFormatTiles,
PhotoScan.ImageFormatTIFF,
region=cu_Region,
projection=self.out_crs,
dx=DifPix,
dy=DifPix,
blockw=BlockSize,
blockh=BlockSize,
write_kml=False,
write_world=True,
tiff_compression=PhotoScan.TiffCompressionJPEG,
tiff_big=False)
#сжатие LZW
#elif file_format=='TIF': chunk.exportOrthomosaic(fileoutname, PhotoScan.RasterFormatTiles,PhotoScan.ImageFormatTIFF, region=cu_Region, projection=self.out_crs,dx=DifPix, dy=DifPix, blockw=BlockSize, blockh=BlockSize, write_kml=False, write_world=True, tiff_compression=PhotoScan.TiffCompressionLZW, tiff_big=False)
else:
print("Формат файла?")
elif CommandStack == 1 and ExportType == 'DEM':
print("Экспорт ДЕМ локально")
if file_format == 'TIF':
chunk.exportDem(fileoutname,
format="tif",
projection=self.out_crs,
region=cu_Region,
dx=DifPix,
dy=DifPix,
blockw=BlockSize,
blockh=BlockSize,
write_kml=False,
write_world=True,
tiff_big=False)
elif CommandStack == 5 and ExportType == 'DEM':
print("Экспорт ДЕМ локально")
if file_format == 'TIF':
chunk.exportDem(fileoutname,
PhotoScan.RasterFormatTiles,
PhotoScan.ImageFormatTIFF,
region=cu_Region,
projection=self.out_crs,
dx=DifPix,
dy=DifPix,
blockw=BlockSize,
blockh=BlockSize,
write_kml=False,
write_world=True,
tiff_big=False)
elif proc_type == 'net':
print('Обработка по сети')
''' ПОСТРОЕНИЕ ОРТОФОТО В ЭТОЙ ВЕРСИИ ОТКЛЮЧЕНО
#Построить ортофото
if statOrthoBuild==True:
workBuild = PhotoScan.NetworkTask() # СОздаем ворк и забиваем его параметрами
#Версионность
if CommandStack==1:
workBuild.params['ortho_surface'] = 0
workBuild.params['resolution_x'] = DifPix
workBuild.params['resolution_y'] = DifPix
elif CommandStack==5:
workBuild.params['ortho_surface'] = 4
workBuild.params['resolution'] = DifPix
else:
return
workBuild.name = "BuildOrthomosaic"
workBuild.frames.append((chunk.key,0))
workBuild.params['network_distribute'] = True
task.append(workBuild) #Добавляем задачу построения в таск
'''
#Экспортировать ортофото
workExport = PhotoScan.NetworkTask(
) # СОздаем ворк и забиваем его параметрами
#ВЕРСИОННОСТЬ
if CommandStack == 1 and ExportType == 'ORTHO':
workExport.name = "ExportOrthomosaic"
workExport.params['resolution_x'] = DifPix
workExport.params['resolution_y'] = DifPix
if file_format == 'JPG':
workExport.params['raster_format'] = 2
elif file_format == 'TIF':
workExport.params['raster_format'] = 1
else:
print("Формат файла?")
elif CommandStack == 5 and ExportType == 'ORTHO':
workExport.name = "ExportRaster"
workExport.params['resolution'] = DifPix
if file_format == 'JPG':
workExport.params['image_format'] = 1
elif file_format == 'TIF':
workExport.params[
'image_format'] = 2 #Значение на шару!!! ПРОВЕРИТЬ
else:
print("Формат файла?")
elif CommandStack == 1 and ExportType == 'DEM':
print("Экспорт ДЕМ по сети")
workExport.name = "ExportDem"
workExport.params['resolution_x'] = DifPix
workExport.params['resolution_y'] = DifPix
elif CommandStack == 5 and ExportType == 'DEM': #НЕ ОТЛАЖЕНО ПАРАМЕТРЫ НА ШАРУ
print("Экспорт ДЕМ по сети")
workExport.name = "ExportOrthomosaic"
workExport.params['resolution'] = DifPix
pass
else:
return
workExport.frames.append((chunk.key, 0))
workExport.params['write_world'] = 1
if self.block_size.currentText(
) == 'Full': # Условие на запись тайлов
workExport.params['write_tiles'] = 0
else:
workExport.params['write_tiles'] = 1
workExport.params['tile_width'] = BlockSize
workExport.params['tile_height'] = BlockSize
workExport.params[
'path'] = fileoutname #выходная дирректория с именем файла
workExport.params['region'] = cu_Region
# ВНИМАНИЕ! По сети нельзя экспортировать в пользовательской проекции ИЛИ проекция должна быть НА ВСЕХ НОДАХ
workExport.params[
'projection'] = self.out_crs.authority #Из объекта проекция берется только ее номер EPSG::32637
#ВНИМАНИЕ ЭКСПОРТ ОТКЛЮЧЕН!!!!
task.append(workExport) #Добавляем задачу в таск
else:
print('Пока не задано')
PhotoScan.app.messageBox('Обработка закончена')
except Exception as e:
print(e)
PhotoScan.app.messageBox('Что-то пошло не так ((')
return
#break
#Запуск сетевого стека, таска в обработку
if proc_type == 'net':
print(ProjectLocalPath_auto)
print(ProjectPath)
client.connect(ServerIP)
batch_id = client.createBatch(ProjectPath, task)
if batch_id == None: #Проверка наличия проекта в сети
PhotoScan.app.messageBox(
'<B>Этот проект уже запущен в обработку!!!<B>')
self.unlock_export(5)
else:
print('Проект работает под номером ', batch_id)
client.resumeBatch(batch_id)
self.unlock_export(5)
PhotoScan.app.messageBox(
'Проект поставлен в очередь сетевой обработки')
client.disconnect()
pass
addr_file.close()
# Create a PhotoScan Network Client object named 'client'
client = PhotoScan.NetworkClient()
# Combines the path to where the project is to be saved with the name of the project in order to save, open, and access the project in the script
filePath = (path + docName)
# Create a PhotoScan Document object and name it 'doc'
doc = PhotoScan.app.document
# Open the document that was previously created by MatchPhotos.py using the filePath variable we created
doc.open(filePath)
# Set the read only variable to false in order to enable editing
doc.read_only = False
#Task 2 or Align Cameras Task
# Create a PhotoScan Network Task object called 'task2'
task2 = PhotoScan.NetworkTask()
# Add all the chunks and frames(if applicable) to the network task so it has access to them
for c in doc.chunks:
task2.chunks.append(c.key)
task2.frames.append((c.key, 0))
print("Added Chunk and Frame")
# Names the task
task2.name = "AlignCameras"
# Applies the task to the chunks we added to the task
task2.params['apply'] = task2.chunks
# Grants the task permission to distribute the processing onto our client
task2.params['network_distribute'] = True
# Connect to the IP Address of the PhotoScan server node we read in from address.txt
client.connect(addr_str)
# Create a batch to submit to the server node
addr_file.close()
# Create a PhotoScan Network Client object named 'client'
client = PhotoScan.NetworkClient()
# Combines the path to where the project is to be saved with the name of the project in order to save, open, and access the project in the script
filePath = (path + docName)
# Create a PhotoScan Document object and name it 'doc'
doc = PhotoScan.app.document
# Open the document that was previously created by MatchPhotos.py using the filePath variable we created
doc.open(filePath)
# Set the read only variable to false in order to enable editing
doc.read_only = False
# Task 3 or Build Depth Maps Task
# Create a PhotoScan Network Task object called 'task3'
task3 = PhotoScan.NetworkTask()
# Add all the chunks and frames(if applicable) to the network task so it has access to them
for c in doc.chunks:
task3.chunks.append(c.key)
task3.frames.append((c.key, 0))
# Names the task
task3.name = "BuildDepthMaps"
# Applies the task to the chunks we added to the task
task3.params['apply'] = task3.chunks
# Set the processing quality to Ultra, which is the highest quality for PhotoScan
task3.params['downscale'] = int(PhotoScan.UltraQuality)
# Set filtering to not filter
task3.params['filter'] = int(PhotoScan.FilterMode.NoFiltering)
# Tells the task not to look for previously created depth maps since this task is creating the first one for the project
task3.params['reuse_depth'] = False
# Grants the task permission to distribute the processing onto our client
addr_file.close()
# Create a PhotoScan Network Client object named 'client'
client = PhotoScan.NetworkClient()
# Combines the path to where the project is to be saved with the name of the project in order to save, open, and access the project in the script
filePath = (path + docName)
# Create a PhotoScan Document object and name it 'doc'
doc = PhotoScan.app.document
# Open the document that was previously created by MatchPhotos.py using the filePath variable we created
doc.open(filePath)
# Set the read only variable to false in order to enable editing
doc.read_only = False
#Task 4 or Build Dense Cloud Task
# Create a PhotoScan Network Task object called 'task4'
task4 = PhotoScan.NetworkTask()
# Add all the chunks and frames(if applicable) to the network task so it has access to them
for c in doc.chunks:
task4.chunks.append(c.key)
task4.frames.append((c.key, 0))
# Names the task
task4.name = "BuildDenseCloud"
# Applies the task to the chunks we added to the task
task4.params['apply'] = task4.chunks
# Set the processing quality to Ultra, which is the highest quality for PhotoScan
task4.params['downscale'] = int(PhotoScan.UltraQuality)
# Set filtering to not filter
task4.params['filter'] = int(PhotoScan.FilterMode.NoFiltering)
# Grants the task permission to distribute the processing onto our client
task4.params['network_distribute'] = True
addr_file.close()
# Create a PhotoScan Network Client object named 'client'
client = PhotoScan.NetworkClient()
# Combines the path to where the project is to be saved with the name of the project in order to save, open, and access the project in the script
filePath = (path + docName)
# Create a PhotoScan Document object and name it 'doc'
doc = PhotoScan.app.document
# Open the document that was previously created by MatchPhotos.py using the filePath variable we created
doc.open(filePath)
# Set the read only variable to false in order to enable editing
doc.read_only = False
#Task 6 or Build DEM Task
# Create a PhotoScan Network Task object called 'task6'
task6 = PhotoScan.NetworkTask()
# Add all the chunks and frames(if applicable) to the network task so it has access to them
for c in doc.chunks:
task6.chunks.append(c.key)
task6.frames.append((c.key,0))
# Names the task
task6.name = "BuildDEM"
# Applies the task to the chunks we added to the task
task6.params['apply'] = task6.chunks
#Set the Dense Cloud as the source data to be used to construct the mesh
task6.params['source_data'] = int(PhotoScan.DataSource.DenseCloudData)
#Enable deafult Interpolation
task6.params['interpolation'] = int(PhotoScan.Interpolation.EnabledInterpolation)
# Grants the task permission to distribute the processing onto our client
task6.params['network_distribute'] = True
addr_file.close()
# Create a PhotoScan Network Client object named 'client'
client = PhotoScan.NetworkClient()
# Combines the path to where the project is to be saved with the name of the project in order to save, open, and access the project in the script
filePath = (path + docName)
# Create a PhotoScan Document object and name it 'doc'
doc = PhotoScan.app.document
# Open the document that was previously created by MatchPhotos.py using the filePath variable we created
doc.open(filePath)
# Set the read only variable to false in order to enable editing
doc.read_only = False
#Task 5 or Build Mesh Task
# Create a PhotoScan Network Task object called 'task5'
task5 = PhotoScan.NetworkTask()
# Add all the chunks and frames(if applicable) to the network task so it has access to them
for c in doc.chunks:
task5.chunks.append(c.key)
task5.frames.append((c.key, 0))
# Names the task
task5.name = "BuildMesh"
# Applies the task to the chunks we added to the task
task5.params['apply'] = task5.chunks
# Set the processing quality to Ultra, which is the highest quality for PhotoScan
#task5.params['downscale'] = int(PhotoScan.UltraQuality)
# Set filtering to not filter
task5.params['filter'] = int(PhotoScan.FilterMode.NoFiltering)
#Set the Dense Cloud as the source data to be used to construct the mesh
task5.params['source_data'] = int(PhotoScan.DataSource.DenseCloudData)
#Enable deafult Interpolation
addr_file.close()
# Create a PhotoScan Network Client object named 'client'
client = PhotoScan.NetworkClient()
# Combines the path to where the project is to be saved with the name of the project in order to save, open, and access the project in the script
filePath = (path + docName)
# Create a PhotoScan Document object and name it 'doc'
doc = PhotoScan.app.document
# Open the document that was previously created by MatchPhotos.py using the filePath variable we created
doc.open(filePath)
# Set the read only variable to false in order to enable editing
doc.read_only = False
#Task 7 or Build Orthomosaic Task
# Create a PhotoScan Network Task object called 'task7'
task7 = PhotoScan.NetworkTask()
# Add all the chunks and frames(if applicable) to the network task so it has access to them
for c in doc.chunks:
task7.chunks.append(c.key)
task7.frames.append((c.key, 0))
# Names the task
task7.name = "BuildOrtho"
# Applies the task to the chunks we added to the task
task7.params['apply'] = task7.chunks
# Sets the blending mode to Mosaic Blending
task7.params['blending_mode'] = int(PhotoScan.BlendingMode.MosaicBlending)
# Tells the task to enable hole filling
task7.params['fill_holes'] = True
# Tells task to get surface data from the previously created Elevation Model(DEM)
task7.params['ortho_surface'] = int(PhotoScan.DataSource.ElevationData)
# Grants the task permission to distribute the processing onto our client
photos = []
# Using glob, grab all the photos from the photos folder and add them to the list
for photo in glob.glob(sourceFolderPath):
photos.append(photo)
# Add all the photos from the list to the chunk
chunk.addPhotos(photos)
# Set the read only variable to false in order to enable editing
doc.read_only = False
# Saves the current state of the project
doc.save()
# Task 1 or Match Photos Task
# Create a PhotoScan Network Task object called 'task1'
task1 = PhotoScan.NetworkTask()
# Add all the chunks and frames(if applicable) to the network task so it has access to them
for c in doc.chunks:
task1.frames.append((c.key, 0))
task1.chunks.append(c.key)
print(c)
print("Added Chunk and Frame")
# Names the task
task1.name = "MatchPhotos"
# Sets the matching accuracy to the highest accuracy possible
task1.params['downscale'] = int(PhotoScan.HighestAccuracy)
# Grants the task permission to distribute the processing onto our client
task1.params['network_distribute'] = True
# Connect to the IP Address of the PhotoScan server node we read in from address.txt
client.connect(addr_str)
