def remove_repeat_detections(inputFile,
outputFile,
filteringDir,
options=None):
assert os.path.isfile(inputFile), "Can't find file {}".format(inputFile)
assert os.path.isdir(filteringDir), "Can't find folder {}".format(
filteringDir)
if options is None:
options = repeat_detections_core.RepeatDetectionOptions()
options.filterFileToLoad = os.path.join(
filteringDir, repeat_detections_core.DETECTION_INDEX_FILE_NAME)
options.bWriteFilteringFolder = False
repeat_detections_core.find_repeat_detections(inputFile, outputFile,
options)
options.confidenceMin, options.iouThreshold, options.occurrenceThreshold,
options.maxSuspiciousDetectionSize)
options.outputBase = os.path.join(filename_base, rde_string)
options.filenameReplacements = {'': ''}
options.debugMaxDir = -1
options.debugMaxRenderDir = -1
options.debugMaxRenderDetection = -1
options.debugMaxRenderInstance = -1
api_output_filename = list(
folder_name_to_combined_output_file.values())[job_index]
filtered_output_filename = path_utils.insert_before_extension(
api_output_filename, 'filtered_{}'.format(rde_string))
suspiciousDetectionResults = repeat_detections_core.find_repeat_detections(
api_output_filename, None, options)
clipboard.copy(os.path.dirname(suspiciousDetectionResults.filterFile))
#%% Manual RDE step
## DELETE THE ANIMALS ##
#%% Re-filtering
from api.batch_processing.postprocessing.repeat_detection_elimination import remove_repeat_detections
remove_repeat_detections.remove_repeat_detections(
inputFile=api_output_filename,
outputFile=filtered_output_filename,
filteringDir=os.path.dirname(suspiciousDetectionResults.filterFile),
def main():
defaultOptions = repeat_detections_core.RepeatDetectionOptions()
parser = argparse.ArgumentParser()
parser.add_argument('inputFile')
parser.add_argument(
'--outputFile',
action='store',
type=str,
default=None,
help=
".json file to write filtered results to... don't use this if you're going to do manual review of the repeat detection images"
)
parser.add_argument(
'--imageBase',
action='store',
type=str,
default='',
help=
'Image base dir, relevant if renderHtml is True or if omitFilteringFolder is not set'
)
parser.add_argument('--outputBase',
action='store',
type=str,
default='',
help='HTML or filtering folder output dir')
parser.add_argument(
'--filterFileToLoad',
action='store',
type=str,
default=
'', # checks for string length so default needs to be the empty string
help=
'Path to detectionIndex.json, which should be inside a folder of images that are manually verified to _not_ contain valid animals'
)
parser.add_argument(
'--confidenceMax',
action='store',
type=float,
default=defaultOptions.confidenceMax,
help=
'Detection confidence threshold; don\'t process anything above this')
parser.add_argument(
'--confidenceMin',
action='store',
type=float,
default=defaultOptions.confidenceMin,
help=
'Detection confidence threshold; don\'t process anything below this')
parser.add_argument(
'--iouThreshold',
action='store',
type=float,
default=defaultOptions.iouThreshold,
help=
'Detections with IOUs greater than this are considered "the same detection"'
)
parser.add_argument(
'--occurrenceThreshold',
action='store',
type=int,
default=defaultOptions.occurrenceThreshold,
help=
'More than this many near-identical detections in a group (e.g. a folder) is considered suspicious'
)
parser.add_argument(
'--nWorkers',
action='store',
type=int,
default=defaultOptions.nWorkers,
help='Level of parallelism for rendering and IOU computation')
parser.add_argument(
'--maxSuspiciousDetectionSize',
action='store',
type=float,
default=defaultOptions.maxSuspiciousDetectionSize,
help=
'Detections larger than this fraction of image area are not considered suspicious'
)
parser.add_argument('--renderHtml',
action='store_true',
dest='bRenderHtml',
help='Should we render HTML output?')
parser.add_argument(
'--omitFilteringFolder',
action='store_false',
dest='bWriteFilteringFolder',
help=
'Should we create a folder of rendered detections for post-filtering?')
parser.add_argument(
'--excludeClasses',
action='store',
nargs='+',
type=int,
default=defaultOptions.excludeClasses,
help=
'List of classes (ints) to exclude from analysis, separated by spaces')
parser.add_argument(
'--nDirLevelsFromLeaf',
default=0,
type=int,
help=
'Number of levels from the leaf folders to use for repeat detection (0 == leaves)'
)
parser.add_argument('--debugMaxDir', action='store', type=int, default=-1)
parser.add_argument('--debugMaxRenderDir',
action='store',
type=int,
default=-1)
parser.add_argument('--debugMaxRenderDetection',
action='store',
type=int,
default=-1)
parser.add_argument('--debugMaxRenderInstance',
action='store',
type=int,
default=-1)
parser.add_argument('--forceSerialComparisons',
action='store_false',
dest='bParallelizeComparisons')
parser.add_argument('--forceSerialRendering',
action='store_false',
dest='bParallelizeRendering')
if len(sys.argv[1:]) == 0:
parser.print_help()
parser.exit()
args = parser.parse_args()
# Convert to an options object
options = repeat_detections_core.RepeatDetectionOptions()
ct_utils.args_to_object(args, options)
repeat_detections_core.find_repeat_detections(args.inputFile,
args.outputFile, options)
options.debugMaxDir = -1
options.debugMaxRenderDir = -1
options.debugMaxRenderDetection = -1
options.debugMaxRenderInstance = -1
options.bParallelizeComparisons = False
options.bParallelizeRendering = False
options.excludeClasses = [2]
inputFilename = os.path.join(baseDir,
'detections_kitfox_20190620_short.json')
outputFilename = os.path.join(
baseDir, 'detections_kitfox_20190620_short_filter.json')
results = repeat_detections_core.find_repeat_detections(
inputFilename, outputFilename, options)
#%% Command-line driver
def main():
defaultOptions = repeat_detections_core.RepeatDetectionOptions()
parser = argparse.ArgumentParser()
parser.add_argument('inputFile')
parser.add_argument(
'--outputFile',
action='store',
type=str,
default=None,
# Exclude people and vehicles from RDE
# options.excludeClasses = [2,3]
# options.maxImagesPerFolder = 50000
# options.includeFolders = ['a/b/c']
# options.excludeFolder = ['a/b/c']
options.debugMaxDir = -1
options.debugMaxRenderDir = -1
options.debugMaxRenderDetection = -1
options.debugMaxRenderInstance = -1
# Can be None, 'xsort', or 'clustersort'
options.smartSort = 'xsort'
suspiciousDetectionResults = repeat_detections_core.find_repeat_detections(
combined_api_output_file, None, options)
# import clipboard; clipboard.copy(os.path.dirname(suspiciousDetectionResults.filterFile))
# path_utils.open_file(os.path.dirname(suspiciousDetectionResults.filterFile))
#%% Manual RDE step
## DELETE THE VALID DETECTIONS ##
#%% Re-filtering
from api.batch_processing.postprocessing.repeat_detection_elimination import remove_repeat_detections
filtered_output_filename = path_utils.insert_before_extension(
combined_api_output_file, 'filtered_{}'.format(rde_string))