def main():
parser = argparse.ArgumentParser()
parser.add_argument('results_file', type=str, help='Input .json filename')
parser.add_argument('base_input_folder', type=str, help='Input image folder')
parser.add_argument('base_output_folder', type=str, help='Output image folder')
options = SeparateDetectionsIntoFoldersOptions()
parser.add_argument('--animal_threshold', type=float, default=options.animal_threshold,
help='Confidence threshold for the animal category')
parser.add_argument('--human_threshold', type=float, default=options.human_threshold,
help='Confidence threshold for the human category')
parser.add_argument('--vehicle_threshold', type=float, default=options.vehicle_threshold,
help='Confidence threshold for vehicle category')
parser.add_argument('--nthreads', type=int, default=options.n_threads,
help='Number of threads to use for parallel operation')
parser.add_argument('--allow_existing_directory', action='store_true',
help='Proceed even if the target directory exists and is not empty')
if len(sys.argv[1:])==0:
parser.print_help()
parser.exit()
args = parser.parse_args()
# Convert to an options object
args_to_object(args, options)
separate_detections_into_folders(options)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('input_file', type=str, help='Input .json filename')
parser.add_argument('output_file', type=str, help='Output .json filename')
parser.add_argument('--query', type=str, default=None, help='Query string to search for (omitting this matches all)')
parser.add_argument('--replacement', type=str, default=None, help='Replace [query] with this')
parser.add_argument('--confidence_threshold', type=float, default=None, help='Remove detections below this confidence level')
parser.add_argument('--split_folders', action='store_true', help='Split .json files by leaf-node folder')
parser.add_argument('--split_folder_param', type=int, help='Directory level count for n_from_bottom and n_from_top splitting')
parser.add_argument('--split_folder_mode', type=str, help='Folder level to use for splitting ("top" or "bottom")')
parser.add_argument('--make_folder_relative', action='store_true', help='Make image paths relative to their containing folder (only meaningful with split_folders)')
parser.add_argument('--overwrite_json_files', action='store_true', help='Overwrite output files')
parser.add_argument('--copy_jsons_to_folders', action='store_true', help='When using split_folders and make_folder_relative, copy jsons to their corresponding folders (relative to output_file)')
parser.add_argument('--create_folders', action='store_true', help='When using copy_jsons_to_folders, create folders that don''t exist')
if len(sys.argv[1:]) == 0:
parser.print_help()
parser.exit()
args = parser.parse_args()
# Convert to an options object
options = SubsetJsonDetectorOutputOptions()
if args.create_folders:
options.copy_jsons_to_folders_directories_must_exist = False
args_to_object(args, options)
subset_json_detector_output(args.input_file, args.output_file, options)
def main():
parser = argparse.ArgumentParser(description=(
'Run the MegaDetector each frame in a video, optionally producing a new video with detections annotated'
))
parser.add_argument('model_file', type=str, help='MegaDetector model file')
parser.add_argument('input_video_file',
type=str,
help='video file to process')
parser.add_argument(
'--output_json_file',
type=str,
default=None,
help='.json output file, defaults to [video file].json')
parser.add_argument('--output_video_file',
type=str,
default=None,
help='video output file, defaults to [video file].mp4')
parser.add_argument(
'--render_output_video',
type=bool,
default=False,
help='enable/disable video output rendering (default False)')
parser.add_argument(
'--delete_output_frames',
type=bool,
default=False,
help='enable/disable temporary file detection (default True)')
parser.add_argument(
'--confidence_threshold',
type=float,
default=0.8,
help="dont render boxes with confidence below this threshold")
parser.add_argument('--n_cores',
type=int,
default=1,
help='number of cores to use for detection (CPU only)')
parser.add_argument('--debug_max_frames',
type=int,
default=-1,
help='trim to N frames for debugging')
args = parser.parse_args()
options = ProcessVideoOptions()
args_to_object(args, options)
process_video(options)
def main():
parser = argparse.ArgumentParser(description=('Run MegaDetector on each frame in a video (or every Nth frame), optionally producing a new video with detections annotated'))
parser.add_argument('model_file', type=str,
help='MegaDetector model file')
parser.add_argument('input_video_file', type=str,
help='video file (or folder) to process')
parser.add_argument('--recursive', action='store_true',
help='recurse into [input_video_file]; only meaningful if a folder is specified as input')
parser.add_argument('--frame_folder', type=str, default=None,
help='folder to use for intermediate frame storage, defaults to a folder in the system temporary folder')
parser.add_argument('--rendering_folder', type=str, default=None,
help='folder to use for renderred frame storage, defaults to a folder in the system temporary folder')
parser.add_argument('--output_json_file', type=str,
default=None, help='.json output file, defaults to [video file].json')
parser.add_argument('--output_video_file', type=str,
default=None, help='video output file (or folder), defaults to [video file].mp4 for files, or [video file]_annotated] for folders')
parser.add_argument('--render_output_video', action='store_true',
help='enable video output rendering (not rendered by default)')
parser.add_argument('--keep_output_frames',
action='store_true', help='Disable the deletion of intermediate images (pre- and post-detection rendered frames)')
parser.add_argument('--rendering_confidence_threshold', type=float,
default=0.8, help="don't render boxes with confidence below this threshold")
parser.add_argument('--json_confidence_threshold', type=float,
default=0.0, help="don't include boxes in the .json file with confidence below this threshold")
parser.add_argument('--n_cores', type=int,
default=1, help='number of cores to use for detection (CPU only)')
parser.add_argument('--frame_sample', type=int,
default=None, help='procss every Nth frame (defaults to every frame)')
parser.add_argument('--debug_max_frames', type=int,
default=-1, help='trim to N frames for debugging (impacts model execution, not frame rendering)')
args = parser.parse_args()
options = ProcessVideoOptions()
args_to_object(args,options)
if os.path.isdir(options.input_video_file):
process_video_folder(options)
else:
process_video(options)
def main():
default_options = PostProcessingOptions()
parser = argparse.ArgumentParser()
parser.add_argument('api_output_file', action='store', type=str,
help='.json file produced by the batch inference API (detection/classification, required)')
parser.add_argument('output_dir', action='store', type=str,
help='Base directory for output (required)')
parser.add_argument('--image_base_dir', action='store', type=str,
help='Base directory for images (optional, can compute statistics without images)',
default=default_options.image_base_dir)
parser.add_argument('--ground_truth_json_file', action='store', type=str,
help='Ground truth labels (optional, can render detections without ground truth)',
default=default_options.ground_truth_json_file)
parser.add_argument('--confidence_threshold', action='store', type=float,
help='Confidence threshold for statistics and visualization',
default=default_options.confidence_threshold)
parser.add_argument('--target_recall', action='store', type=float,
help='Target recall (for statistics only)',
default=default_options.target_recall)
parser.add_argument('--num_images_to_sample', action='store', type=int,
help='Number of images to visualize (defaults to 500) (-1 to include all images)',
default=default_options.num_images_to_sample)
parser.add_argument('--viz_target_width', action='store', type=int,
help='Output image width',
default=default_options.viz_target_width)
parser.add_argument('--random_output_sort', action='store_true', help='Sort output randomly (defaults to sorting by filename)')
if len(sys.argv[1:]) == 0:
parser.print_help()
parser.exit()
args = parser.parse_args()
args.sort_html_by_filename = not args.random_output_sort
options = PostProcessingOptions()
args_to_object(args,options)
process_batch_results(options)
def main():
# With HTML (debug)
# python find_repeat_detections.py "D:\temp\tigers_20190308_all_output.json" "D:\temp\tigers_20190308_all_output.filtered.json" --renderHtml --debugMaxDir 100 --imageBase "d:\wildlife_data\tigerblobs" --outputBase "d:\temp\repeatDetections"
# Without HTML (debug)
# python find_repeat_detections.py "D:\temp\tigers_20190308_all_output.json" "D:\temp\tigers_20190308_all_output.filtered.json" --debugMaxDir 100 --imageBase "d:\wildlife_data\tigerblobs" --outputBase "d:\temp\repeatDetections"
# With HTML (for real)
# python find_repeat_detections.py "D:\temp\tigers_20190308_all_output.json" "D:\temp\tigers_20190308_all_output.filtered.json" --renderHtml --imageBase "d:\wildlife_data\tigerblobs" --outputBase "d:\temp\repeatDetections"
defaultOptions = RepeatDetectionOptions()
parser = argparse.ArgumentParser()
parser.add_argument('inputFile')
parser.add_argument('outputFile')
parser.add_argument(
'--imageBase',
action='store',
type=str,
help=
'Image base dir, relevant if renderHtml is True or if omitFilteringFolder is not set'
)
parser.add_argument(
'--outputBase',
action='store',
type=str,
help='Html output dir, only relevant if renderHtml is True')
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('--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 = RepeatDetectionOptions()
ct_utils.args_to_object(args, options)
find_repeat_detections(args.inputFile, args.outputFile, options)
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)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('results_file', type=str, help='Input .json filename')
parser.add_argument('base_input_folder',
type=str,
help='Input image folder')
parser.add_argument('base_output_folder',
type=str,
help='Output image folder')
parser.add_argument(
'--animal_threshold',
type=float,
default=default_threshold,
help='Confidence threshold for the animal category (default={})'.
format(default_threshold))
parser.add_argument(
'--human_threshold',
type=float,
default=default_threshold,
help='Confidence threshold for the human category (default={})'.format(
default_threshold))
parser.add_argument(
'--vehicle_threshold',
type=float,
default=default_threshold,
help='Confidence threshold for vehicle category (default={})'.format(
default_threshold))
parser.add_argument(
'--n_threads',
type=int,
default=1,
help='Number of threads to use for parallel operation (default=1)')
parser.add_argument(
'--allow_existing_directory',
action='store_true',
help='Proceed even if the target directory exists and is not empty')
parser.add_argument(
'--no_overwrite',
action='store_true',
help=
'Skip images that already exist in the target folder, must also specify --allow_existing_directory'
)
if len(sys.argv[1:]) == 0:
parser.print_help()
parser.exit()
args = parser.parse_args()
# Convert to an options object
options = SeparateDetectionsIntoFoldersOptions()
args_to_object(args, options)
if args.animal_threshold:
options.category_name_to_threshold['animal'] = args.animal_threshold
if args.human_threshold:
options.category_name_to_threshold['person'] = args.human_threshold
if args.vehicle_threshold:
options.category_name_to_threshold['vehicle'] = args.vehicle_threshold
options.overwrite = (not args.no_overwrite)
separate_detections_into_folders(options)
