def make_project(project_dir, photos_dir):
'Make a new project and add the photos from the photos_dir to it.'
log("Making project " + project_dir)
doc = PhotoScan.Document(
) # Operate on a new document for batch proecssing
#doc = PhotoScan.app.document # Use the current open document in PhotoScan
# Add the photos to a chunk
chunk = doc.addChunk()
photos_dir = os.path.join(project_dir, photos_dir)
photos = os.listdir(photos_dir)
photos = [os.path.join(photos_dir, p) for p in photos]
log("Found {} photos in {}".format(len(photos), photos_dir))
if not chunk.addPhotos(photos):
log("ERROR: Failed to add photos: " + str(photos))
# Save the new project
project_name = make_project_filename(project_dir, "psz")
log("Saving: " + project_name)
if not doc.save(project_name):
log("ERROR: Failed to save project: " + project_name)
return doc
def make_project(project_dir, chunk_dirs):
'Make a new project and a chunk for each directory.'
log("Making project " + project_dir)
# Create new doc
doc = PhotoScan.Document(
) # Operate on a new document for batch proecssing
#doc = PhotoScan.app.document # Use the current open document in PhotoScan
# Go through each chunk directory
for chunk_dir in chunk_dirs:
chunk = doc.addChunk() # Create the chunk
chunk.label = os.path.basename(chunk_dir)
photos = os.listdir(chunk_dir) # Get the photos filenames
photos = [os.path.join(chunk_dir, p)
for p in photos] # Make them into a full path
log("Found {} photos in {}".format(len(photos), chunk_dir))
if not chunk.addPhotos(photos):
log("ERROR: Failed to add photos: " + str(photos))
# Save the new project
project_name = make_project_filename(project_dir, "psz")
log("Saving: " + project_name)
if not doc.save(project_name):
log("ERROR: Failed to save project: " + project_name)
return doc
def open_project(project_dir):
log("Opening project " + project_dir)
project_name = make_project_filename(project_dir, "psz")
doc = PhotoScan.Document()
if not doc.open(project_name):
log("ERROR: Cold not open document: " + project_name)
return doc
def create_new_project(self):
if not os.path.exists(path=self.project_file_name + self.PROJECT_TYPE):
new_project = PhotoScan.Document()
chunk = new_project.addChunk()
new_project.save(
path=self.project_file_name + self.PROJECT_TYPE,
chunks=[chunk]
)
def main():
#prompting for path to photos
path_photos = PhotoScan.app.getExistingDirectory("Specify INPUT photo folder(containing all metashape files):")
path_export = PhotoScan.app.getExistingDirectory("Specify EXPORT folder:")
#processing parameters
accuracy = PhotoScan.Accuracy.HighAccuracy #align photos accuracy
preselection = PhotoScan.Preselection.GenericPreselection
keypoints = 40000 #align photos key point limit
tiepoints = 10000 #align photos tie point limit
threshold=0.5
fold_list = os.listdir(path_photos)
for folder in fold_list:
#print("folder name is : "+folder)
#loading images
folderPath = path_photos + "\\" + folder
image_list = os.listdir(folderPath)
photo_list = list()
for photo in image_list:
if ("jpg" or "jpeg" or "JPG" or "JPEG") in photo.lower():
photo_list.append(os.path.join(folderPath,photo))
doc = PhotoScan.Document()
doc.save(path_export+"\\"+folder+".psx")
chunk=doc.addChunk()
chunk.addPhotos(photo_list)
#align photos
chunk.matchPhotos(accuracy = accuracy, preselection = preselection, filter_mask = False, keypoint_limit = keypoints, tiepoint_limit = tiepoints)
chunk.alignCameras()
#Removing points outside bounding box
chunk = doc.chunks[-1]
R = chunk.region.rot #Bounding box rotation matrix
C = chunk.region.center #Bounding box center vertor
size = chunk.region.size
if not (chunk.point_cloud and chunk.enabled):
continue
elif not len(chunk.point_cloud.points):
continue
for point in chunk.point_cloud.points:
if point.valid:
v = point.coord
v.size = 3
v_c = v - C
v_r = R.t() * v_c
if abs(v_r.x) > abs(size.x / 2.):
point.valid = False
elif abs(v_r.y) > abs(size.y / 2.):
point.valid = False
elif abs(v_r.z) > abs(size.z / 2.):
point.valid = False
else:
continue
#Points outside the region were removed.
#Read reprojection error and delete any 0.5 or greater
f = PhotoScan.PointCloud.Filter()
f.init(chunk, criterion=PhotoScan.PointCloud.Filter.ReprojectionError)
f.removePoints(threshold)
doc.save()
# How to launch
# ./photoscan-pro/photoscan.sh -r "path_to_script.py"
import PhotoScan
import os
doc = PhotoScan.Document()
path = "/home/ben/Downloads/photoscan/monument/3_views/" #path to the image folder
# chunk = PhotoScan.Chunk()
chunk = doc.addChunk()
chunk.label = "New Chunk"
# doc.chunks.add(chunk)
photos_list = os.listdir(path)
tofList = []
for tof in photos_list:
tofList.append(path + "/" + tof)
print(tofList)
# for photo_name in tofList: #adding all files from the folder
chunk.addPhotos(tofList)
#Align Photos
chunk.matchPhotos(accuracy=PhotoScan.HighAccuracy)
# chunk.matchPhotos(accuracy = "high", preselection="disabled", filter_mask=False, point_limit=40000)
chunk.alignCameras()
# chunk.alignPhotos()
def process(images_path, output_path, reference_path, model_name):
# Font settings
os.environ['QT_QPA_FONTDIR'] = '/usr/share/fonts/truetype/dejavu/'
# Below code was to enable all available GPUs, was throwing an error.
#PhotoScan.app.gpu_mask = 2 ** len(PhotoScan.app.enumGPUDevices()) - 1 #setting GPU mask
PhotoScan.app.gpu_mask = 3 # gpu_mask is a bitmask. 3 in binary = 11 so only two GPUs are used.
if PhotoScan.app.gpu_mask:
PhotoScan.app.cpu_enable = False
else:
PhotoScan.app.cpu_enable = True
### Processing parameters
accuracy = PhotoScan.Accuracy.HighAccuracy #align photos accuracy
reference_preselection = False
generic_preselection = True
keypoints = 40000 # Align photos key point limit
tiepoints = 4000 # Align photos tie point limit
source = PhotoScan.DataSource.DenseCloudData # Build mesh/DEM source
surface = PhotoScan.SurfaceType.Arbitrary # Build mesh surface type
quality = PhotoScan.Quality.MediumQuality # Build dense cloud quality
filtering = PhotoScan.FilterMode.AggressiveFiltering # Depth filtering
interpolation = PhotoScan.Interpolation.EnabledInterpolation # Build mesh interpolation
mosaic_blending = PhotoScan.BlendingMode.MosaicBlending # Blending mode
average_blending = PhotoScan.BlendingMode.AverageBlending
disabled_blending = PhotoScan.BlendingMode.DisabledBlending
face_num = PhotoScan.FaceCount.HighFaceCount # Build mesh polygon count
mapping = PhotoScan.MappingMode.GenericMapping #Build texture mapping
atlas_size = 4096
TYPES = ["jpg", "jpeg", "tif", "tiff", "png"]
# Load images into master list of fore and aft.
list_photos_master = load_images(TYPES, images_path)
# Create PhotoScan document
project_file = os.path.join(output_path, "Model.psx")
doc = PhotoScan.Document()
doc.save(project_file)
chunk = doc.addChunk()
chunk.label = model_name
print("Saving PhotoScan project to: ", project_file)
print("Chunk label: ", str(chunk.label))
# Add Images to Chunk
chunk.addPhotos(list_photos_master)
# Load ref file.
chunk.loadReference(path=reference_path,
format=PhotoScan.ReferenceFormat.ReferenceFormatCSV,
columns='zanxy',
delimiter=',')
# Set coordinate system for lat lon values.
chunk.crs = PhotoScan.CoordinateSystem("EPSG::4326")
# TODO Load calibration parameters from file
# Create Sensor definitions
sensor_fore = chunk.addSensor()
sensor_fore.label = "Fore Sensor"
sensor_fore.type = PhotoScan.Sensor.Type.Frame
sensor_fore.width = chunk.cameras[-1].sensor.width
sensor_fore.height = chunk.cameras[-1].sensor.height
sensor_fore.pixel_size = [0.00345, 0.00345]
sensor_fore.focal_length = 6.7 # Focal length is 10.4mm, 14.6mm effective length in water.
sensor_fore.antenna.location_ref = PhotoScan.Vector([0.38, 0, 0.25])
sensor_aft = chunk.addSensor()
sensor_aft.label = "Aft Sensor"
sensor_aft.type = PhotoScan.Sensor.Type.Frame
sensor_aft.width = chunk.cameras[-1].sensor.width
sensor_aft.height = chunk.cameras[-1].sensor.height
sensor_aft.pixel_size = [0.00345, 0.00345]
sensor_aft.focal_length = 6.7
sensor_aft.antenna.location_ref = PhotoScan.Vector([0.53, 0, 0.25])
for camera in chunk.cameras:
if "F" in camera.label:
camera.sensor = sensor_fore
print("Added ", camera.label, "to fore group")
elif "A" in camera.label:
camera.sensor = sensor_aft
print("Added ", camera.label, "to aft group")
else:
print("No sensor defined for ", camera.label)
# Add scalebars between stereo images
# This is the baseline between two cameras.
# Iver3 system is 6" baseline, 0.1524 meters.
index = 0
while (True):
scalebar = chunk.addScalebar(chunk.cameras[index],
chunk.cameras[index + 1])
scalebar.reference.distance = 0.1524
index += 2
if index >= len(chunk.cameras):
break
### Estimate image quality
chunk.estimateImageQuality(chunk.cameras)
badImages = 0
#for camera in chunk.cameras:
# if float(camera.photo.meta["Image/Quality"]) < 0.5:
# camera.enabled = False
# badImages+=1
print("Removed ", badImages, " from chunk")
### Align photos
chunk.matchPhotos(accuracy=accuracy,
generic_preselection=generic_preselection,
reference_preselection=reference_preselection,
filter_mask=False,
keypoint_limit=keypoints,
tiepoint_limit=tiepoints,
progress=progress_print)
chunk.alignCameras()
chunk.optimizeCameras()
chunk.resetRegion()
doc.read_only = False
doc.save()
###building dense cloud
chunk.buildDepthMaps(quality=quality,
filter=filtering,
progress=progress_print)
chunk.buildDenseCloud(point_colors=True, progress=progress_print)
doc.save()
###building mesh
chunk.buildModel(surface=surface,
source=source,
interpolation=interpolation,
face_count=face_num,
progress=progress_print)
doc.save()
###build texture
chunk.buildUV(mapping=mapping, count=1, progress=progress_print)
chunk.buildTexture(blending=mosaic_blending,
size=atlas_size,
progress=progress_print)
doc.save()
###export model
chunk.exportModel(path=os.path.join(output_path, chunk.label + ".obj"),
binary=False,
texture_format=PhotoScan.ImageFormatJPEG,
texture=True,
normals=False,
colors=False,
cameras=False,
format=PhotoScan.ModelFormatOBJ)
### Export GeoTiff file
chunk.buildDem(source=source,
interpolation=interpolation,
projection=chunk.crs,
progress=progress_print)
chunk.exportDem(
path=os.path.join(output_path, chunk.label + '_DEM.jpeg'),
image_format=PhotoScan.ImageFormat.ImageFormatJPEG,
raster_transform=PhotoScan.RasterTransformType.RasterTransformPalette,
projection=chunk.crs,
nodata=-32767,
write_kml=True,
write_world=True,
write_scheme=True,
tiff_big=True)
# Export orthomosaic
chunk.buildOrthomosaic(surface=PhotoScan.DataSource.ElevationData,
blending=mosaic_blending,
fill_holes=True)
chunk.exportOrthomosaic(path=os.path.join(
output_path,
chunk.label + '_' + str(mosaic_blending) + '_orthomosaic.tif'),
projection=chunk.crs)
chunk.buildOrthomosaic(surface=PhotoScan.DataSource.ElevationData,
blending=average_blending,
fill_holes=True)
chunk.exportOrthomosaic(path=os.path.join(
output_path,
chunk.label + '_' + str(average_blending) + '_orthomosaic.tif'),
projection=chunk.crs)
chunk.buildOrthomosaic(surface=PhotoScan.DataSource.ElevationData,
blending=disabled_blending,
fill_holes=True)
chunk.exportOrthomosaic(path=os.path.join(
output_path,
chunk.label + '_' + str(disabled_blending) + '_orthomosaic.tif'),
projection=chunk.crs)
### Export camera poses
export_camera_pose(
chunk, os.path.join(output_path, chunk.label + '_camera_pose.csv'))
### Generate report
chunk.exportReport(os.path.join(output_path, chunk.label + '_report.pdf'))
print("Processed " + chunk.label)
return True
def process(path):
PhotoScan.app.gpu_mask = 2 ** len(PhotoScan.app.enumGPUDevices()) - 1 #setting GPU mask
if PhotoScan.app.gpu_mask:
PhotoScan.app.cpu_enable = False
else:
PhotoScan.app.cpu_enable = True
### processing parameters
accuracy = PhotoScan.Accuracy.HighAccuracy #align photos accuracy
reference_preselection = False
generic_preselection = True
keypoints = 40000 #align photos key point limit
tiepoints = 4000 #align photos tie point limit
source = PhotoScan.DataSource.DenseCloudData #build mesh/DEM source
surface = PhotoScan.SurfaceType.Arbitrary #build mesh surface type
quality = PhotoScan.Quality.MediumQuality #build dense cloud quality
filtering = PhotoScan.FilterMode.AggressiveFiltering #depth filtering
interpolation = PhotoScan.Interpolation.EnabledInterpolation #build mesh interpolation
blending = PhotoScan.BlendingMode.MosaicBlending #blending mode
face_num = PhotoScan.FaceCount.HighFaceCount #build mesh polygon count
mapping = PhotoScan.MappingMode.GenericMapping #build texture mapping
atlas_size = 4096
TYPES = ["jpg", "jpeg", "tif", "tiff"]
###end of processing parameters definition
print("Processing " + path)
list_files = os.listdir(path)
list_photos = list()
for entry in list_files: #finding image files
file = path + "/" + entry
if os.path.isfile(file):
if file[-3:].lower() in TYPES:
list_photos.append(file)
if not(len(list_photos)):
print("No images in " + path)
return False
doc = PhotoScan.Document()
doc.save(path + "/" + path.rsplit("/", 1)[1] + ".psx")
chunk = doc.addChunk()
chunk.label = path.rsplit("/", 1)[1]
###align photos
chunk.addPhotos(list_photos)
chunk.matchPhotos(accuracy = accuracy, generic_preselection = generic_preselection, reference_preselection = reference_preselection, filter_mask = False, keypoint_limit = keypoints, tiepoint_limit = tiepoints)
chunk.alignCameras()
chunk.optimizeCameras()
chunk.resetRegion()
doc.save()
###building dense cloud
chunk.buildDepthMaps(quality = quality, filter = filtering)
chunk.buildDenseCloud(point_colors = True, keep_depth = False)
doc.save()
###building mesh
chunk.buildModel(surface = surface, source = source, interpolation = interpolation, face_count = face_num)
doc.save()
###build texture
chunk.buildUV(mapping = mapping, count = 1)
chunk.buildTexture(blending = blending, size = atlas_size)
doc.save()
###export model
chunk. exportModel(path = path + "/" + chunk.label + ".obj", binary=False, texture_format=ImageFormatJPEG, texture=True, normals=False, colors=False, cameras=False, format = PhotoScan.ModelFormatOBJ)
print("Processed " + chunk.label)
return True
def generate3D(filePath):
fullPathPhotoDirectoryName = filePath
# Define: AlignPhotosAccuracy ["high", "medium", "low"]
#change me
print("\n**enum gpu devices", PhotoScan.app.enumGPUDevices())
print("\n**gpu mask ", PhotoScan.app.gpu_mask)
TireAuditDataRoot = os.path.dirname(
os.path.dirname(fullPathPhotoDirectoryName)) + "\\"
#1 PhotoScanInputGCPFileTireAuditMarkers=generate_3DSettings.photoScanGCPFile
#1 PhotoScanInputGCPFileAgisoftMarkers=TireAuditDataRoot+"gcp_agisoft.csv"
#1 PhotoScanInputGCPFileAgisoftMarkers=TireAuditDataRoot+"foo4.txt"
PhotoScanInputCalibFile = generate_3DSettings.photoScanCalibrationFile
#fdebug.write("\n ********************* TireAuditDataRoot PhotoScanInputCalibFile PhotoScanInputGCPFileAgisoftMarkers PhotoScanInputGCPFileAgisoftMarkers PhotoScanInputCalibFile\n ",TireAuditDataRoot , PhotoScanInputCalibFile , PhotoScanInputGCPFileAgisoftMarkers, PhotoScanInputGCPFileAgisoftMarkers ,PhotoScanInputCalibFile)
PhotoScanPlyFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanPlyName
PhotoScanLogFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanLogName
PhotoScanDebugFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanDebugName
PhotoScanProjectFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanProjectName
PhotoScanReprojectionErrorsFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanReprojectionErrorsName
#PhotoScanMarkerFile = fullPathPhotoDirectoryName+"\\"+generate_codesSettings.markerInformationPixelToCode
#fdebug.write("\n*********** Checking for %s \n", PhotoScanProjectFile)
# if path already has a psz file in exit then go onto nex directory
if os.path.exists(PhotoScanProjectFile):
#fdebug.write("\n*********** already proceessed %s \n", PhotoScanProjectFile)
exit
fdebug = open(PhotoScanDebugFile, 'w')
flog = open(PhotoScanLogFile, 'w')
start = time.time()
#####pattern = 'IMG_*[02468].JPG'
pattern = 'IMG_*'
#print 'Pattern :', pattern
print("abc")
#files = os.listdir('.')
files = os.listdir(fullPathPhotoDirectoryName)
photoList = []
for filename in fnmatch.filter(files, pattern):
#print ('Filename: %-25s %s' % (name, fnmatch.fnmatch(name, pattern)) )
#item = fullPathPhotoDirectoryName+"\\"+filename
item = os.path.join(fullPathPhotoDirectoryName, filename)
photoList.append(item)
print("\n777 Photolist is ", photoList)
doc = PhotoScan.Document()
chunk = doc.addChunk()
chunk.crs = PhotoScan.CoordinateSystem(
'LOCAL_CS["Local Coordinates",LOCAL_DATUM["Local Datum",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]]]'
)
chunk.label = "New ChunkB"
cameraDictionary = {}
user_calib = PhotoScan.Calibration()
success = user_calib.load(PhotoScanInputCalibFile)
print("\n success loading calib file ", success)
sensor = chunk.addSensor(
) #creating camera calibration group for the loaded image
sensor.label = "Calibration Group 1"
sensor.type = PhotoScan.Sensor.Type.Frame
#sensor.width = camera.photo.image().width
#sensor.height = camera.photo.image().height
sensor.width = 5312
sensor.height = 2988
sensor.fixed = True
sensor.user_calib = user_calib
#sensor.width = 3264
#1 chunk.marker_projection_accuracy=0.0002
for i, filepath in enumerate(photoList):
fdebug.write("\nxxxxxxxx filepath" + " " + filepath)
camera = chunk.addCamera()
camera.sensor = sensor
pos = filepath.find("IMG")
img = filepath[pos:]
#cameraDictionary[img]=i
cameraDictionary[img] = camera.key
camera.open(filepath)
#camera.open("c:\\Projects\\123DCatch\\Tires_25982510_B_Samsung6ChoppedExampleForTesting\\A\\IMG_14.JPG")
camera.label = img
#fdebug.write("\n filepath key", filepath, camera.key,camera.photo.image().width,camera.photo.image().height)
fdebug.write("\n filepath key" + " " + filepath + " " +
str(camera.key) + " " + camera.photo.path)
fdebug.write("\n^^^^^^^^^^ Camera Dictionary" + " " +
str(cameraDictionary))
fdebug.write("\n PhotoList &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&\n" + " " +
str(photoList))
fdebug.write("hello")
templateName = fullPathPhotoDirectoryName + "\\" + "M{filename}.JPG"
#templateName=fullPathPhotoDirectoryName+ "\\" + "M{filename}.JPG"
#successMask=chunk.importMasks(path=templateName,method='file',tolerance=10)
successMask = chunk.importMasks(
path=templateName,
source=PhotoScan.MaskSourceFile,
operation=PhotoScan.MaskOperationReplacement,
tolerance=10,
cameras=chunk.cameras)
print(
"\n***********************&&&&&&&&&&&&&&&&& successMask ************",
successMask)
#ALIGN PHOTOS
fdebug.write("---Aligning photos ...")
fdebug.write("Accuracy: " + generate_3DSettings.matchAccuracy)
fdebug.write("\nBefore Matching **** \n")
if (generate_3DSettings.matchAccuracy == "Low"):
accuracyMatch = PhotoScan.Accuracy.LowAccuracy
elif (generate_3DSettings.matchAccuracy == "High"):
accuracyMatch = PhotoScan.Accuracy.HighAccuracy
else:
accuracyMatch = PhotoScan.Accuracy.MediumAccuracy
if (generate_3DSettings.modelAccuracy == "Ultra"):
accuracyModel = PhotoScan.Quality.UltraQuality
elif (generate_3DSettings.modelAccuracy == "High"):
accuracyModel = PhotoScan.Quality.HighQuality
elif (generate_3DSettings.modelAccuracy == "Low"):
accuracyModel = PhotoScan.Quality.LowQuality
elif (generate_3DSettings.modelAccuracy == "Lowest"):
accuracyModel = PhotoScan.Quality.LowestQuality
else:
accuracyModel = PhotoScan.Quality.MediumQuality
chunk.matchPhotos(accuracy=accuracyMatch,
preselection=PhotoScan.Preselection.GenericPreselection,
filter_mask=True)
fdebug.write("\nBefore Align **** \n")
chunk.alignCameras()
fdebug.write("\nBefore Optimize **** \n")
chunk.optimizeCameras()
fdebug.write("\nBefore Build Dense **** \n")
chunk.buildDenseCloud(quality=accuracyModel)
fdebug.write("\nBefore Build Model **** \n")
#chunk.buildModel(surface= PhotoScan.SurfaceType.Arbitrary, interpolation=PhotoScan.Interpolation.EnabledInterpolation , face_count=generate_3DSettings.faceCount)
#chunk.buildModel(surface= PhotoScan.SurfaceType.Arbitrary, interpolation=PhotoScan.Interpolation.EnabledInterpolation , face_count=300000)
fdebug.write("\nBefore Build Texture **** \n")
mapping = PhotoScan.MappingMode.GenericMapping #build texture mapping
chunk.buildUV(mapping=mapping, count=1)
chunk.buildTexture()
#chunk.exportModel(path=PhotoScanPlyFile, format = 'ply', texture_format='jpg')
chunk.exportModel(PhotoScanPlyFile,
format=PhotoScan.ModelFormat.ModelFormatPLY,
texture_format=PhotoScan.ImageFormat.ImageFormatJPEG)
#chunk.exportModel(path_export + "\\model.obj", format = "obj", texture_format='PhotoScan.ImageFormat.ImageFormatJPEG)
PhotoScan.app.update()
#save ground control information a
chunk.saveReference(PhotoScanReprojectionErrorsFile,
PhotoScan.ReferenceFormat.ReferenceFormatCSV)
#
# if not(chunk.saveReference(PhotoScanReprojectionErrorsFile, PhotoScan.ReferenceFormat.ReferenceFormatCSV )):
# app.messageBox("Saving GCP info failed!")
#
# SAVE PROJECT
fdebug.write("---Saving project...")
fdebug.write("File: " + PhotoScanProjectFile)
doc.save(PhotoScanProjectFile)
doc.chunks.remove(chunk)
end = time.time()
fdebug.close()
flog.write('\nelapsed time =' +
str(end - start)) # python will convert \n to os.linesep
flog.close()
return
def generate3D(filePath):
fullPathPhotoDirectoryName = filePath
# Define: AlignPhotosAccuracy ["high", "medium", "low"]
TireAuditDataRoot = os.path.dirname(
os.path.dirname(fullPathPhotoDirectoryName)) + "\\"
PhotoScanInputGCPFileTireAuditMarkers = generate_3DSettings.photoScanGCPFile
PhotoScanInputGCPFileAgisoftMarkers = TireAuditDataRoot + "gcp_agisoft.csv"
PhotoScanInputGCPFileAgisoftMarkers = TireAuditDataRoot + "foo4.txt"
PhotoScanInputCalibFile = generate_3DSettings.photoScanCalibrationFile
#fdebug.write("\n ********************* TireAuditDataRoot PhotoScanInputCalibFile PhotoScanInputGCPFileAgisoftMarkers PhotoScanInputGCPFileAgisoftMarkers PhotoScanInputCalibFile\n ",TireAuditDataRoot , PhotoScanInputCalibFile , PhotoScanInputGCPFileAgisoftMarkers, PhotoScanInputGCPFileAgisoftMarkers ,PhotoScanInputCalibFile)
PhotoScanPlyFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanPlyName
PhotoScanLogFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanLogName
PhotoScanDebugFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanDebugName
PhotoScanProjectFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanProjectName
PhotoScanReprojectionErrorsFile = fullPathPhotoDirectoryName + "\\" + generate_3DSettings.photoScanReprojectionErrorsName
PhotoScanMarkerFile = fullPathPhotoDirectoryName + "\\" + generate_codesSettings.markerInformationPixelToCode
#fdebug.write("\n*********** Checking for %s \n", PhotoScanProjectFile)
# if path already has a psz file in exit then go onto nex directory
if os.path.exists(PhotoScanProjectFile):
#fdebug.write("\n*********** already proceessed %s \n", PhotoScanProjectFile)
exit
fdebug = open(PhotoScanDebugFile, 'w')
flog = open(PhotoScanLogFile, 'w')
start = time.time()
print("\n**enum gpu devices", PhotoScan.app.enumGPUDevices())
print("\n**gpu mask ", PhotoScan.app.gpu_mask)
enumDev = PhotoScan.app.enumGPUDevices()
gpu_mask = PhotoScan.app.gpu_mask
fdebug.write("\n**enum gpu devices " +
str(PhotoScan.app.enumGPUDevices()))
fdebug.write("\n**gpu mask " + str(PhotoScan.app.gpu_mask))
#change me
#####pattern = 'IMG_*[02468].JPG'
pattern = 'IMG_*'
#print 'Pattern :', pattern
print("abc")
#files = os.listdir('.')
files = os.listdir(fullPathPhotoDirectoryName)
photoList = []
for filename in fnmatch.filter(files, pattern):
#print ('Filename: %-25s %s' % (name, fnmatch.fnmatch(name, pattern)) )
#item = fullPathPhotoDirectoryName+"\\"+filename
item = os.path.join(fullPathPhotoDirectoryName, filename)
photoList.append(item)
print("\n777 Photolist is ", photoList)
doc = PhotoScan.Document()
chunk = doc.addChunk()
chunk.crs = PhotoScan.CoordinateSystem(
'LOCAL_CS["Local Coordinates",LOCAL_DATUM["Local Datum",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]]]'
)
#successLoad=chunk.loadReference("c:\\temp\\pgcp.csv","csv")
#successLoad=chunk.loadReference("c:\\temp\\foo1.csv","csv")
#successLoad=chunk.loadReference("c:\\temp\\dtest.csv","csv")
#print ("\n ############# Success Load is ", successLoad)
#chunk.updateTransform()
chunk.label = "New ChunkB"
cameraDictionary = {}
user_calib = PhotoScan.Calibration()
success = user_calib.load(PhotoScanInputCalibFile)
print("\n success loading calib file ", success)
sensor = chunk.addSensor(
) #creating camera calibration group for the loaded image
sensor.label = "Calibration Group 1"
sensor.type = PhotoScan.Sensor.Type.Frame
#sensor.width = camera.photo.image().width
#sensor.height = camera.photo.image().height
sensor.width = 5312
sensor.height = 2988
sensor.fixed = True
sensor.user_calib = user_calib
#sensor.width = 3264
#sensor.height = 2448
#sensor.calibration.cx=1.61822175e+03
#sensor.calibration.cy=1.26702669e+03
#sensor.calibration.fx=3.08768833e+03
#sensor.calibration.fy=3.08786068e+03
#sensor.calibration.k1=0.23148765
#sensor.calibration.k2=0.51836559
#sensor.calibration.k3=-0.48297284
# sensor.calibration.fx = 3.99411182e+03
# sensor.calibration.fy = 3.99418122e+03
# sensor.calibration.cx = 2.68713926e+03
# sensor.calibration.cy = 1.51055154e+03
# sensor.calibration.k1= 0.24503953
# sensor.calibration.k2 = -0.80636859
# sensor.calibration.k3 = 0.77637451
# sensor.user_calib.fx = 3.99411182e+03
# sensor.user_calib.fy = 3.99418122e+03
# sensor.user_calib.cx = 2.68713926e+03
# sensor.user_calib.cy = 1.51055154e+03
# sensor.user_calib.k1= 0.24503953
# sensor.user_calib.k2 = -0.80636859
# sensor.user_calib.k3 = 0.77637451
# sensor.user_calib = True
# sensor.calibration.fx = 4.05913e+03
# sensor.calibration.fy = 4.06049e+03
# sensor.calibration.cx = 2.68463e+03
# sensor.calibration.cy = 1.52241e+03
# sensor.calibration.k1= 0.273712
# sensor.calibration.k2 = -1.03971
# sensor.calibration.k3 = 1.05705
chunk.marker_projection_accuracy = 0.0002
for i, filepath in enumerate(photoList):
fdebug.write("\nxxxxxxxx filepath" + " " + filepath)
camera = chunk.addCamera()
camera.sensor = sensor
pos = filepath.find("IMG")
img = filepath[pos:]
#cameraDictionary[img]=i
cameraDictionary[img] = camera.key
camera.open(filepath)
#camera.open("c:\\Projects\\123DCatch\\Tires_25982510_B_Samsung6ChoppedExampleForTesting\\A\\IMG_14.JPG")
camera.label = img
#fdebug.write("\n filepath key", filepath, camera.key,camera.photo.image().width,camera.photo.image().height)
fdebug.write("\n filepath key" + " " + filepath + " " +
str(camera.key) + " " + camera.photo.path)
fdebug.write("\n^^^^^^^^^^ Camera Dictionary" + " " +
str(cameraDictionary))
fdebug.write("\n PhotoList &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&\n" + " " +
str(photoList))
fdebug.write("hello")
if (os.path.isfile(PhotoScanMarkerFile)):
automaticMarkers = False
else:
automaticMarkers = True
fdebug.write("\n ^^^^^^^^^^^^^^^^^ automatic markers is \n " +
str(automaticMarkers) + "\n")
if (automaticMarkers):
chunk.detectMarkers(PhotoScan.TargetType.CircularTarget20bit, 44)
print(
"\n ^^^^^^^^^^^^^^^^^ loading automatic ground contreol information\n",
PhotoScanInputGCPFileAgisoftMarkers, "\n")
successLoad = chunk.loadReference(PhotoScanInputGCPFileAgisoftMarkers,
"csv")
fdebug.write("\n succes load is" + " " + str(successLoad))
else:
markerNamePosList = []
processTAMarkers(PhotoScanMarkerFile, markerNamePosList, chunk,
cameraDictionary, fdebug)
fdebug.write(
"\n ^^^^^^^^^^^^^^^^^ loading ground contreol information\n" +
" " + PhotoScanInputGCPFileTireAuditMarkers + "\n")
#successLoad=chunk.loadReference("c:\\temp\\gcp_25982510.csv","csv")
successLoad = chunk.loadReference(
PhotoScanInputGCPFileTireAuditMarkers)
# load in ground control information
# load in masks
templateName = fullPathPhotoDirectoryName + "\\" + "M{filename}.JPG"
#templateName=fullPathPhotoDirectoryName+ "\\" + "M{filename}.JPG"
#successMask=chunk.importMasks(path=templateName,method='file',tolerance=10)
#ALIGN PHOTOS
fdebug.write("---Aligning photos ...")
fdebug.write("Accuracy: " + generate_3DSettings.matchAccuracy)
fdebug.write("\nBefore Matching **** \n")
if (generate_3DSettings.matchAccuracy == "Low"):
accuracyMatch = PhotoScan.Accuracy.LowAccuracy
elif (generate_3DSettings.matchAccuracy == "High"):
accuracyMatch = PhotoScan.Accuracy.HighAccuracy
else:
accuracyMatch = PhotoScan.Accuracy.MediumAccuracy
if (generate_3DSettings.modelAccuracy == "Ultra"):
accuracyModel = PhotoScan.Quality.UltraQuality
elif (generate_3DSettings.modelAccuracy == "High"):
accuracyModel = PhotoScan.Quality.HighQuality
elif (generate_3DSettings.modelAccuracy == "Low"):
accuracyModel = PhotoScan.Quality.LowQuality
elif (generate_3DSettings.modelAccuracy == "Lowest"):
accuracyModel = PhotoScan.Quality.LowestQuality
else:
accuracyModel = PhotoScan.Quality.MediumQuality
chunk.matchPhotos(accuracy=accuracyMatch,
preselection=PhotoScan.Preselection.GenericPreselection)
fdebug.write("\nBefore Align **** \n")
chunk.alignCameras()
fdebug.write("\nBefore Optimize **** \n")
chunk.optimizeCameras()
fdebug.write("\nBefore Build Dense **** \n")
chunk.buildDenseCloud(quality=accuracyModel)
fdebug.write("\nBefore Build Model **** \n")
chunk.buildModel(
surface=PhotoScan.SurfaceType.Arbitrary,
interpolation=PhotoScan.Interpolation.EnabledInterpolation,
face_count=generate_3DSettings.faceCount)
fdebug.write("\nBefore Build Texture **** \n")
mapping = PhotoScan.MappingMode.GenericMapping #build texture mapping
chunk.buildUV(mapping=mapping, count=1)
chunk.buildTexture()
#chunk.exportModel(path=PhotoScanPlyFile, format = 'ply', texture_format='jpg')
chunk.exportModel(PhotoScanPlyFile,
format=PhotoScan.ModelFormat.ModelFormatPLY,
texture_format=PhotoScan.ImageFormat.ImageFormatJPEG)
#chunk.exportModel(path_export + "\\model.obj", format = "obj", texture_format='PhotoScan.ImageFormat.ImageFormatJPEG)
PhotoScan.app.update()
#save ground control information a
chunk.saveReference(PhotoScanReprojectionErrorsFile,
PhotoScan.ReferenceFormat.ReferenceFormatCSV)
#
# if not(chunk.saveReference(PhotoScanReprojectionErrorsFile, PhotoScan.ReferenceFormat.ReferenceFormatCSV )):
# app.messageBox("Saving GCP info failed!")
#
# SAVE PROJECT
fdebug.write("---Saving project...")
fdebug.write("File: " + PhotoScanProjectFile)
doc.save(PhotoScanProjectFile)
doc.chunks.remove(chunk)
end = time.time()
fdebug.close()
flog.write('\nelapsed time =' +
str(end - start)) # python will convert \n to os.linesep
flog.close()
return
