def insert_video_frame_timestamp(video_filename, video_sampling_path, start_time, sample_interval=2.0, duration_ratio=1.0, verbose=False):
# get list of file to process
frame_list = uploader.get_total_file_list(video_sampling_path)
if not len(frame_list):
# WARNING LOG
print("No video frames were sampled.")
return
video_frame_timestamps = timestamps_from_filename(video_filename,
frame_list,
start_time,
sample_interval,
duration_ratio)
for image, timestamp in tqdm(zip(frame_list,
video_frame_timestamps), desc="Inserting frame capture time"):
try:
exif_edit = ExifEdit(image)
exif_edit.add_date_time_original(timestamp)
exif_edit.write()
except:
# ERROR LOG
print("Could not insert timestamp into video frame " +
os.path.basename(image)[:-4])
continue
def save_local_mapping(import_path):
local_mapping_filepath = os.path.join(os.path.dirname(
import_path), import_path + "_mapillary_image_uuid_to_local_path_mapping.csv")
total_files = uploader.get_total_file_list(import_path)
local_mapping = []
for file in tqdm(total_files, desc="Reading image uuids"):
image_file_uuid = None
relative_path = file.lstrip(os.path.abspath(import_path))
log_rootpath = uploader.log_rootpath(file)
image_description_json_path = os.path.join(
log_rootpath, "mapillary_image_description.json")
if os.path.isfile(image_description_json_path):
image_description_json = processing.load_json(
image_description_json_path)
if "MAPPhotoUUID" in image_description_json:
image_file_uuid = image_description_json["MAPPhotoUUID"]
else:
print(
"Error, photo uuid not in mapillary_image_description.json log file.")
else:
image_exif = exif_read.ExifRead(file)
image_description = json.loads(
image_exif.extract_image_description())
if "MAPPhotoUUID" in image_description:
image_file_uuid = str(image_description["MAPPhotoUUID"])
else:
print("Warning, image {} EXIF does not contain mapillary image description and mapillary_image_description.json log file does not exist. Try to process the image using mapillary_tools.".format(file))
if image_file_uuid:
local_mapping.append((relative_path, image_file_uuid))
return local_mapping
def insert_video_frame_timestamp(video_filename,
video_sampling_path,
start_time,
sample_interval=2.0,
duration_ratio=1.0,
verbose=False):
# get list of file to process
frame_list = uploader.get_total_file_list(video_sampling_path)
if not len(frame_list):
# WARNING LOG
print("No video frames were sampled.")
return
video_frame_timestamps = timestamps_from_filename(video_filename,
frame_list, start_time,
sample_interval,
duration_ratio)
for image, timestamp in tqdm(zip(frame_list, video_frame_timestamps),
desc="Inserting frame capture time"):
try:
exif_edit = ExifEdit(image)
exif_edit.add_date_time_original(timestamp)
exif_edit.write()
except:
# ERROR LOG
print("Could not insert timestamp into video frame " +
os.path.basename(image)[:-4])
continue
def insert_video_frame_timestamp(import_path, start_time, sample_interval, duration_ratio=1.0, verbose=False):
# get list of file to process
frame_list = uploader.get_total_file_list(import_path)
if not len(frame_list):
if verbose:
print("No video frames were sampled.")
return
video_frame_timestamps = timestamps_from_filename(frame_list,
start_time,
sample_interval,
duration_ratio)
for image, timestamp in zip(frame_list,
video_frame_timestamps):
try:
exif_edit = ExifEdit(image)
exif_edit.add_date_time_original(timestamp)
exif_edit.write()
except:
if verbose:
print("Could not insert timestamp into video frame " +
os.path.basename(image)[:-4])
continue
def download(import_path,
user_name,
output_folder,
number_threads=10,
verbose=False):
total_files = uploader.get_total_file_list(import_path)
rows = []
local_mapping = save_local_mapping(import_path)
signal.signal(signal.SIGTERM, service_shutdown)
signal.signal(signal.SIGINT, service_shutdown)
try:
user_properties = uploader.authenticate_user(user_name)
except:
print("Error, user authentication failed for user " + user_name)
print(
"Make sure your user credentials are correct, user authentication is required for images to be downloaded from Mapillary."
)
return None
if "user_upload_token" in user_properties:
token = user_properties["user_upload_token"]
else:
print("Error, failed to obtain user token, please try again.")
return None
do_sleep = False
while not check_files_downloaded(local_mapping, output_folder, do_sleep):
do_sleep = True
lock = threading.Lock()
downloaded_images = {
"failed": 0,
"nbr": 0,
"success": 0,
}
threads = []
try:
for i in range(number_threads):
t = BlurDownloader(lock, downloaded_images, local_mapping,
output_folder, token)
threads.append(t)
t.start()
while True:
any_alive = False
for t in threads:
any_alive = (any_alive or t.is_alive())
if not any_alive:
break
time.sleep(0.5)
except ServiceExit:
for t in threads:
t.shutdown_flag.set()
for t in threads:
t.join()
break
def inform_processing_start(import_path, len_process_file_list, process, skip_subfolders=False):
total_file_list = uploader.get_total_file_list(
import_path, skip_subfolders)
print("Running {} for {} images, skipping {} images.".format(process,
len_process_file_list,
len(total_file_list) - len_process_file_list))
def insert_video_frame_timestamp(import_path,
start_time,
sample_interval,
duration_ratio=1.0,
verbose=False):
# get list of file to process
frame_list = uploader.get_total_file_list(import_path)
if not len(frame_list):
if verbose:
print("No video frames were sampled.")
return
video_frame_timestamps = timestamps_from_filename(frame_list, start_time,
sample_interval,
duration_ratio)
for image, timestamp in zip(frame_list, video_frame_timestamps):
try:
exif_edit = ExifEdit(image)
exif_edit.add_date_time_original(timestamp)
exif_edit.write()
except:
if verbose:
print("Could not insert timestamp into video frame " +
os.path.basename(image)[:-4])
continue
def save_local_mapping(import_path):
local_mapping_filepath = os.path.join(os.path.dirname(
import_path), import_path + "_mapillary_image_uuid_to_local_path_mapping.csv")
total_files = uploader.get_total_file_list(import_path)
local_mapping = []
for file in tqdm(total_files, desc="Reading image uuids"):
image_file_uuid = None
relative_path = file.lstrip(os.path.abspath(import_path))
log_rootpath = uploader.log_rootpath(file)
image_description_json_path = os.path.join(
log_rootpath, "mapillary_image_description.json")
if os.path.isfile(image_description_json_path):
image_description_json = processing.load_json(
image_description_json_path)
if "MAPPhotoUUID" in image_description_json:
image_file_uuid = image_description_json["MAPPhotoUUID"]
else:
print(
"Error, photo uuid not in mapillary_image_description.json log file.")
else:
image_exif = exif_read.ExifRead(file)
image_description = json.loads(
image_exif.extract_image_description())
if "MAPPhotoUUID" in image_description:
image_file_uuid = str(image_description["MAPPhotoUUID"])
else:
print("Warning, image {} EXIF does not contain mapillary image description and mapillary_image_description.json log file does not exist. Try to process the image using mapillary_tools.".format(file))
if image_file_uuid:
local_mapping.append((relative_path, image_file_uuid))
return local_mapping
def inform_processing_start(import_path, len_process_file_list, process, skip_subfolders=False):
total_file_list = uploader.get_total_file_list(
import_path, skip_subfolders)
print("Running {} for {} images, skipping {} images.".format(process,
len_process_file_list,
len(total_file_list) - len_process_file_list))
def download(import_path, user_name, output_folder, number_threads=10, verbose=False):
total_files = uploader.get_total_file_list(import_path)
rows = []
local_mapping = save_local_mapping(import_path)
signal.signal(signal.SIGTERM, service_shutdown)
signal.signal(signal.SIGINT, service_shutdown)
try:
user_properties = uploader.authenticate_user(user_name)
except:
print("Error, user authentication failed for user " + user_name)
print("Make sure your user credentials are correct, user authentication is required for images to be downloaded from Mapillary.")
return None
if "user_upload_token" in user_properties:
token = user_properties["user_upload_token"]
else:
print("Error, failed to obtain user token, please try again.")
return None
do_sleep = False
while not check_files_downloaded(local_mapping, output_folder, do_sleep):
do_sleep = True
lock = threading.Lock()
downloaded_images = {
"failed": 0,
"nbr": 0,
"success": 0,
}
threads = []
try:
for i in range(number_threads):
t = BlurDownloader(lock, downloaded_images,
local_mapping, output_folder, token)
threads.append(t)
t.start()
while True:
any_alive = False
for t in threads:
any_alive = (any_alive or t.is_alive())
if not any_alive:
break
time.sleep(0.5)
except ServiceExit:
for t in threads:
t.shutdown_flag.set()
for t in threads:
t.join()
break
def upload(import_path,
manual_done=False,
verbose=False,
skip_subfolders=False,
video_file=None,
number_threads=None,
max_attempts=None):
'''
Upload local images to Mapillary
Args:
import_path: Directory path to where the images are stored.
verbose: Print extra warnings and errors.
skip_subfolders: Skip images stored in subdirectories.
manual_done: Prompt user to confirm upload finalization.
Returns:
Images are uploaded to Mapillary and flagged locally as uploaded.
'''
# sanity check if video file is passed
if video_file and not (os.path.isdir(video_file)
or os.path.isfile(video_file)):
print("Error, video path " + video_file +
" does not exist, exiting...")
sys.exit(1)
# in case of video processing, adjust the import path
if video_file:
# set sampling path
video_sampling_path = processing.sampled_video_frames_rootpath(
video_file)
import_path = os.path.join(
os.path.abspath(import_path),
video_sampling_path) if import_path else os.path.join(
os.path.dirname(video_file), video_sampling_path)
# basic check for all
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" does not exist, exiting...")
sys.exit(1)
# get list of file to process
total_file_list = uploader.get_total_file_list(import_path,
skip_subfolders)
upload_file_list = uploader.get_upload_file_list(import_path,
skip_subfolders)
failed_file_list = uploader.get_failed_upload_file_list(
import_path, skip_subfolders)
success_file_list = uploader.get_success_upload_file_list(
import_path, skip_subfolders)
if len(success_file_list) == len(total_file_list):
print("All images have already been uploaded")
sys.exit()
if len(failed_file_list):
upload_failed = raw_input(
"Retry uploading previously failed image uploads? [y/n]: ")
# if yes, add images to the upload list
if upload_failed in ["y", "Y", "yes", "Yes"]:
upload_file_list.extend(failed_file_list)
# verify the images in the upload list, they need to have the image
# description and certain MAP properties
upload_file_list = [f for f in upload_file_list if verify_mapillary_tag(f)]
if not len(upload_file_list):
print("No images to upload.")
print(
'Please check if all images contain the required Mapillary metadata. If not, you can use "mapillary_tools process" to add them'
)
sys.exit(1)
# get upload params
params = {}
for image in total_file_list:
log_root = uploader.log_rootpath(image)
upload_params_path = os.path.join(log_root,
"upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
params[image] = json.load(
jf, object_hook=uploader.ascii_encode_dict)
# inform how many images are to be uploaded and how many are being skipped
# from upload
print("Uploading {} images with valid mapillary tags (Skipping {})".format(
len(upload_file_list),
len(total_file_list) - len(upload_file_list)))
# call the actual upload, passing the list of images, the root of the
# import and the upload params
uploader.upload_file_list(upload_file_list, params, number_threads,
max_attempts)
# finalize manual uploads if necessary
finalize_file_list = uploader.get_finalize_file_list(
import_path, skip_subfolders)
# if manual uploads a DONE file needs to be uploaded to let the harvester
# know the sequence is done uploading
if len(finalize_file_list):
finalize_all = 1
if manual_done:
finalize_all = uploader.prompt_to_finalize("uploads")
if finalize_all:
# get the s3 locations of the sequences
finalize_params = uploader.process_upload_finalization(
finalize_file_list, params)
uploader.finalize_upload(finalize_params)
# flag finalization for each file
uploader.flag_finalization(finalize_file_list)
else:
print("Uploads will not be finalized.")
print(
"If you wish to finalize your uploads, run the upload tool again."
)
sys.exit()
uploader.print_summary(upload_file_list)
def upload(import_path, manual_done=False, verbose=False, skip_subfolders=False):
'''
Upload local images to Mapillary
Args:
import_path: Directory path to where the images are stored.
verbose: Print extra warnings and errors.
skip_subfolders: Skip images stored in subdirectories.
manual_done: Prompt user to confirm upload finalization.
Returns:
Images are uploaded to Mapillary and flagged locally as uploaded.
'''
# basic check for all
import_path = os.path.abspath(import_path)
if not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" doesnt not exist, exiting...")
sys.exit()
# get list of file to process
total_file_list = uploader.get_total_file_list(
import_path, skip_subfolders)
upload_file_list = uploader.get_upload_file_list(
import_path, skip_subfolders)
failed_file_list = uploader.get_failed_upload_file_list(
import_path, skip_subfolders)
success_file_list = uploader.get_success_upload_file_list(
import_path, skip_subfolders)
if len(success_file_list) == len(total_file_list):
print("All images have already been uploaded")
sys.exit()
if len(failed_file_list):
upload_failed = raw_input(
"Retry uploading previously failed image uploads? [y/n]: ")
# if yes, add images to the upload list
if upload_failed in ["y", "Y", "yes", "Yes"]:
upload_file_list.extend(failed_file_list)
# verify the images in the upload list, they need to have the image
# description and certain MAP properties
upload_file_list = [f for f in upload_file_list if verify_mapillary_tag(f)]
if not len(upload_file_list):
print("No images to upload.")
print('Please check if all images contain the required Mapillary metadata. If not, you can use "mapillary_tools process" to add them')
sys.exit()
# get upload params
params = {}
for image in total_file_list:
log_root = uploader.log_rootpath(import_path, image)
upload_params_path = os.path.join(
log_root, "upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
params[image] = json.load(
jf, object_hook=uploader.ascii_encode_dict)
# inform how many images are to be uploaded and how many are being skipped
# from upload
print("Uploading {} images with valid mapillary tags (Skipping {})".format(
len(upload_file_list), len(total_file_list) - len(upload_file_list)))
# call the actual upload, passing the list of images, the root of the
# import and the upload params
uploader.upload_file_list(upload_file_list, import_path, params)
# finalize manual uploads if necessary
finalize_file_list = uploader.get_finalize_file_list(
import_path, skip_subfolders)
# if manual uploads a DONE file needs to be uploaded to let the harvester
# know the sequence is done uploading
if len(finalize_file_list):
finalize_all = 1
if manual_done:
finalize_all = uploader.prompt_to_finalize("uploads")
if finalize_all:
# get the s3 locations of the sequences
finalize_params = uploader.process_upload_finalization(
finalize_file_list, params)
uploader.finalize_upload(finalize_params)
# flag finalization for each file
uploader.flag_finalization(import_path, finalize_file_list)
else:
print("Uploads will not be finalized.")
print("If you wish to finalize your uploads, run the upload tool again.")
sys.exit()
uploader.print_summary(upload_file_list)
def process_csv(import_path,
csv_path,
filename_column=None,
timestamp_column=None,
latitude_column=None,
longitude_column=None,
heading_column=None,
altitude_column=None,
gps_week_column=None,
time_format="%Y:%m:%d %H:%M:%S.%f",
convert_gps_time=False,
convert_utc_time=False,
delimiter=",",
header=False,
meta_columns=None,
meta_names=None,
meta_types=None,
verbose=False,
keep_original=False):
# sanity checks
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" doesnt not exist, exiting...")
sys.exit(1)
if not csv_path or not os.path.isfile(csv_path):
print(
"Error, csv file not provided or does not exist. Please specify a valid path to a csv file."
)
sys.exit(1)
# get list of file to process
process_file_list = uploader.get_total_file_list(import_path)
if not len(process_file_list):
print("No images found in the import path " + import_path)
sys.exit(1)
if gps_week_column != None and convert_gps_time == False:
print(
"Error, in order to parse timestamp provided as a combination of GPS week and GPS seconds, you must specify timestamp column and flag --convert_gps_time, exiting..."
)
sys.exit(1)
if (convert_gps_time != False
or convert_utc_time != False) and timestamp_column == None:
print(
"Error, if specifying a flag to convert timestamp, timestamp column must be provided, exiting..."
)
sys.exit(1)
column_indexes = [
filename_column, timestamp_column, latitude_column, longitude_column,
heading_column, altitude_column, gps_week_column
]
if any([column == 0 for column in column_indexes]):
print(
"Error, csv column numbers start with 1, one of the columns specified is 0."
)
sys.exit(1)
column_indexes = map(lambda x: x - 1 if x else None, column_indexes)
# checks for meta arguments if any
meta_columns, meta_names, meta_types = validate_meta_data(
meta_columns, meta_names, meta_types)
# open and process csv
csv_data = read_csv(csv_path, delimiter=delimiter, header=header)
# align by filename column if provided, otherwise align in order of image
# names
file_names = None
if filename_column:
file_names = csv_data[filename_column - 1]
else:
if verbose:
print(
"Warning, filename column not provided, images will be aligned with the csv data in order of the image filenames."
)
# process each image
for idx, image in tqdm(enumerate(process_file_list),
desc="Inserting csv data in image EXIF"):
# get image entry index
image_index = get_image_index(image, file_names) if file_names else idx
if image_index == None:
print("Warning, no entry found in csv file for image " + image)
continue
# get required data
timestamp, lat, lon, heading, altitude = parse_csv_geotag_data(
csv_data, image_index, column_indexes, convert_gps_time,
convert_utc_time, time_format)
# get meta data
meta = parse_csv_meta_data(csv_data, image_index, meta_columns,
meta_types, meta_names)
# insert in image EXIF
exif_edit = ExifEdit(image)
if timestamp:
exif_edit.add_date_time_original(timestamp)
if lat and lon:
exif_edit.add_lat_lon(lat, lon)
if heading:
exif_edit.add_direction(heading)
if altitude:
exif_edit.add_altitude(altitude)
if meta:
exif_edit.add_image_history(meta["MAPMetaTags"])
filename = image
filename_keep_original = processing.processed_images_rootpath(image)
if os.path.isfile(filename_keep_original):
os.remove(filename_keep_original)
if keep_original:
if not os.path.isdir(os.path.dirname(filename_keep_original)):
os.makedirs(os.path.dirname(filename_keep_original))
filename = filename_keep_original
try:
exif_edit.write(filename=filename)
except:
print("Error, image EXIF could not be written back for image " +
image)
return None
def post_process(import_path,
split_import_path=None,
video_import_path=None,
summarize=False,
move_images=False,
move_duplicates=False,
move_uploaded=False,
save_as_json=False,
list_file_status=False,
push_images=False,
skip_subfolders=False,
verbose=False,
save_local_mapping=False):
# return if nothing specified
if not summarize and not move_images and not list_file_status and not push_images and not move_duplicates and not move_uploaded and not save_local_mapping:
print("No post processing action specified.")
return
# sanity check if video file is passed
if video_import_path and not os.path.isdir(video_import_path):
print("Error, video path " + video_import_path +
" does not exist, exiting...")
sys.exit(1)
# in case of video processing, adjust the import path
if video_import_path:
# set sampling path
video_sampling_path = "mapillary_sampled_video_frames"
import_path = os.path.join(os.path.abspath(import_path), video_sampling_path) if import_path else os.path.join(
os.path.abspath(video_import_path), video_sampling_path)
# basic check for all
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" does not exist, exiting...")
sys.exit(1)
if save_local_mapping:
local_mapping = save_local_mapping(import_path)
with open(local_mapping_filepath, "w") as csvfile:
csvwriter = csv.writer(csvfile, delimiter=",")
for row in local_mapping:
csvwriter.writerow(row)
else:
print("Reading import logs for import path {}...".format(import_path))
# collect logs
summary_dict = {}
status_list_dict = {}
total_files = uploader.get_total_file_list(import_path)
total_files_count = len(total_files)
# upload logs
uploaded_files = uploader.get_success_upload_file_list(
import_path, skip_subfolders)
uploaded_files_count = len(uploaded_files)
failed_upload_files = uploader.get_failed_upload_file_list(
import_path, skip_subfolders)
failed_upload_files_count = len(failed_upload_files)
to_be_finalized_files = uploader.get_finalize_file_list(import_path)
to_be_finalized_files_count = len(to_be_finalized_files)
summary_dict["total images"] = total_files_count
summary_dict["upload summary"] = {
"successfully uploaded": uploaded_files_count,
"failed uploads": failed_upload_files_count,
"uploaded to be finalized": to_be_finalized_files_count
}
status_list_dict["successfully uploaded"] = uploaded_files
status_list_dict["failed uploads"] = failed_upload_files
status_list_dict["uploaded to be finalized"] = to_be_finalized_files
# process logs
summary_dict["process summary"] = {}
process_steps = ["user_process", "import_meta_process", "geotag_process",
"sequence_process", "upload_params_process", "mapillary_image_description"]
process_status = ["success", "failed"]
for step in process_steps:
process_success = len(processing.get_process_status_file_list(
import_path, step, "success", skip_subfolders))
process_failed = len(processing.get_process_status_file_list(
import_path, step, "failed", skip_subfolders))
summary_dict["process summary"][step] = {
"failed": process_failed,
"success": process_success
}
duplicates_file_list = processing.get_duplicate_file_list(
import_path, skip_subfolders)
duplicates_file_list_count = len(duplicates_file_list)
summary_dict["process summary"]["duplicates"] = duplicates_file_list_count
status_list_dict["duplicates"] = duplicates_file_list
# processed for upload
to_be_uploaded_files = uploader.get_upload_file_list(
import_path, skip_subfolders)
to_be_uploaded_files_count = len(to_be_uploaded_files)
summary_dict["process summary"]["processed_not_yet_uploaded"] = to_be_uploaded_files_count
status_list_dict["processed_not_yet_uploaded"] = to_be_uploaded_files
# summary
if summarize:
print("")
print("Import summary for import path {} :".format(import_path))
print(json.dumps(summary_dict, indent=4))
ipc.send('summary', summary_dict)
if save_as_json:
try:
processing.save_json(summary_dict, os.path.join(
import_path, "mapillary_import_summary.json"))
except Exception as e:
print("Could not save summary into json at {}, due to {}".format(
os.path.join(import_path, "mapillary_import_summary.json"), e))
# list file status
if list_file_status:
print("")
print("List of file status for import path {} :".format(import_path))
print(json.dumps(status_list_dict, indent=4))
if save_as_json:
try:
processing.save_json(status_list_dict, os.path.join(
import_path, "mapillary_import_image_status_list.json"))
except Exception as e:
print("Could not save image status list into json at {}, due to {}".format(
os.path.join(import_path, "mapillary_import_image_status_list.json"), e))
# push images that were uploaded successfully
# collect upload params
if push_images:
to_be_pushed_files = uploader.get_success_only_manual_upload_file_list(
import_path, skip_subfolders)
params = {}
for image in tqdm(to_be_pushed_files, desc="Pushing images"):
log_root = uploader.log_rootpath(image)
upload_params_path = os.path.join(
log_root, "upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
params[image] = json.load(
jf, object_hook=uploader.ascii_encode_dict)
# get the s3 locations of the sequences
finalize_params = uploader.process_upload_finalization(
to_be_pushed_files, params)
uploader.finalize_upload(finalize_params)
# flag finalization for each file
uploader.flag_finalization(to_be_pushed_files)
if move_images or move_duplicates or move_uploaded:
print("")
print("Note that images will be moved along with their mapillary logs in order to preserve the import status")
defualt_split_import_path = os.path.join(
import_path, "mapillary_import_split_images")
if not split_import_path:
final_split_path = defualt_split_import_path
print("")
print(
"Split import path not provided and will therefore be set to default path {}".format(defualt_split_import_path))
if split_import_path:
if not os.path.isfile(split_import_path):
final_split_path = defualt_split_import_path
print("Split import path does not exist, split import path will be set to default path {}".format(
defualt_split_import_path))
else:
final_split_path = split_import_path
print("")
print("Splitting import path {} into {} based on image import status...".format(
import_path, final_split_path))
if move_images:
move_duplicates = True
move_uploaded = True
# move failed uploads
if not len(failed_upload_files):
print("")
print(
"There are no failed upload images in the specified import path.")
else:
failed_upload_path = os.path.join(
final_split_path, "upload_failed")
if not os.path.isdir(failed_upload_path):
os.makedirs(failed_upload_path)
for failed in failed_upload_files:
failed_upload_image_path = os.path.join(
failed_upload_path, os.path.basename(failed))
os.rename(failed, failed_upload_path)
failed_upload_log_path = os.path.dirname(uploader.log_rootpath(
failed_upload_image_path))
if not os.path.isdir(failed_upload_log_path):
os.makedirs(failed_upload_log_path)
shutil.move(uploader.log_rootpath(failed),
failed_upload_log_path)
print("")
print("Done moving failed upload images to {}".format(
failed_upload_path))
if move_duplicates:
if not len(duplicates_file_list):
print("")
print("There were no duplicates flagged in the specified import path. If you are processing the images with mapillary_tools and would like to flag duplicates, you must specify --advanced --flag_duplicates")
else:
duplicate_path = os.path.join(
final_split_path, "duplicates")
if not os.path.isdir(duplicate_path):
os.makedirs(duplicate_path)
for duplicate in duplicates_file_list:
duplicate_image_path = os.path.join(
duplicate_path, os.path.basename(duplicate))
os.rename(duplicate, duplicate_image_path)
duplicate_log_path = os.path.dirname(uploader.log_rootpath(
duplicate_image_path))
if not os.path.isdir(duplicate_log_path):
os.makedirs(duplicate_log_path)
shutil.move(uploader.log_rootpath(duplicate),
duplicate_log_path)
print("")
print("Done moving duplicate images to {}".format(
duplicate_path))
if move_uploaded:
if not len(uploaded_files):
print("")
print(
"There are no successfuly uploaded images in the specified import path.")
else:
upload_success_path = os.path.join(
final_split_path, "upload_success")
if not os.path.isdir(upload_success_path):
os.makedirs(upload_success_path)
for uploaded in uploaded_files:
uploaded_image_path = os.path.join(
upload_success_path, os.path.basename(uploaded))
os.rename(uploaded, upload_success_path)
uploaded_log_path = os.path.dirname(uploader.log_rootpath(
uploaded_image_path))
if not os.path.isdir(uploaded_log_path):
os.makedirs(uploaded_log_path)
shutil.move(uploader.log_rootpath(uploaded),
uploaded_log_path)
print("")
print("Done moving successfully uploaded images to {}".format(
upload_success_path))
def upload(import_path, verbose=False, skip_subfolders=False, number_threads=None, max_attempts=None, video_import_path=None, dry_run=False,api_version=1.0):
'''
Upload local images to Mapillary
Args:
import_path: Directory path to where the images are stored.
verbose: Print extra warnings and errors.
skip_subfolders: Skip images stored in subdirectories.
Returns:
Images are uploaded to Mapillary and flagged locally as uploaded.
'''
# sanity check if video file is passed
if video_import_path and (not os.path.isdir(video_import_path) and not os.path.isfile(video_import_path)):
print("Error, video path " + video_import_path +
" does not exist, exiting...")
sys.exit(1)
# in case of video processing, adjust the import path
if video_import_path:
# set sampling path
video_sampling_path = "mapillary_sampled_video_frames"
video_dirname = video_import_path if os.path.isdir(
video_import_path) else os.path.dirname(video_import_path)
import_path = os.path.join(os.path.abspath(import_path), video_sampling_path) if import_path else os.path.join(
os.path.abspath(video_dirname), video_sampling_path)
# basic check for all
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" does not exist, exiting...")
sys.exit(1)
# get list of file to process
total_file_list = uploader.get_total_file_list(
import_path, skip_subfolders)
upload_file_list = uploader.get_upload_file_list(
import_path, skip_subfolders)
failed_file_list = uploader.get_failed_upload_file_list(
import_path, skip_subfolders)
success_file_list = uploader.get_success_upload_file_list(
import_path, skip_subfolders)
to_finalize_file_list = uploader.get_finalize_file_list(
import_path, skip_subfolders)
if len(success_file_list) == len(total_file_list):
print("All images have already been uploaded")
else:
if len(failed_file_list):
upload_failed = raw_input(
"Retry uploading previously failed image uploads? [y/n]: ") if not ipc.is_enabled() else 'y'
# if yes, add images to the upload list
if upload_failed in ["y", "Y", "yes", "Yes"]:
upload_file_list.extend(failed_file_list)
# verify the images in the upload list, they need to have the image
# description and certain MAP properties
upload_file_list = [
f for f in upload_file_list if verify_mapillary_tag(f)]
if not len(upload_file_list) and not len(to_finalize_file_list):
print("No images to upload.")
print('Please check if all images contain the required Mapillary metadata. If not, you can use "mapillary_tools process" to add them')
sys.exit(1)
if len(upload_file_list):
# get upload params for the manual upload images, group them per sequence
# and separate direct upload images
params = {}
list_per_sequence_mapping = {}
direct_upload_file_list = []
for image in upload_file_list:
log_root = uploader.log_rootpath(image)
upload_params_path = os.path.join(
log_root, "upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
params[image] = json.load(
jf, object_hook=uploader.ascii_encode_dict)
sequence = params[image]["key"]
if sequence in list_per_sequence_mapping:
list_per_sequence_mapping[sequence].append(image)
else:
list_per_sequence_mapping[sequence] = [image]
else:
direct_upload_file_list.append(image)
# inform how many images are to be uploaded and how many are being skipped
# from upload
print("Uploading {} images with valid mapillary tags (Skipping {})".format(
len(upload_file_list), len(total_file_list) - len(upload_file_list)))
if api_version==2.0:
uploder.uploadfile_list
if len(direct_upload_file_list):
uploader.upload_file_list_direct(
direct_upload_file_list, number_threads, max_attempts)
for idx, sequence in enumerate(list_per_sequence_mapping):
uploader.upload_file_list_manual(
list_per_sequence_mapping[sequence], params, idx, number_threads, max_attempts)
if len(to_finalize_file_list):
params = {}
sequences = []
for image in to_finalize_file_list:
log_root = uploader.log_rootpath(image)
upload_params_path = os.path.join(
log_root, "upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
image_params = json.load(
jf, object_hook=uploader.ascii_encode_dict)
sequence = image_params["key"]
if sequence not in sequences:
params[image] = image_params
sequences.append(sequence)
for image in params:
uploader.upload_done_file(**params[image])
uploader.flag_finalization(to_finalize_file_list)
uploader.print_summary(upload_file_list)
def interpolation(data,
file_in_path=None,
file_format="csv",
time_column=0,
delimiter=",",
time_utc=False,
time_format="%Y-%m-%dT%H:%M:%SZ",
header=False,
keep_original=False,
import_path=None,
max_time_delta=1,
verbose=False):
if not data:
print_error("Error, you must specify the data for interpolation." +
'Choose between "missing_gps" or "identical_timestamps"')
sys.exit(1)
if not import_path and not file_in_path:
print_error("Error, you must specify a path to data, either path to directory with images or path to an external log file.")
sys.exit(1)
if file_in_path:
if not os.path.isfile(file_in_path):
print_error("Error, specified input file does not exist, exiting...")
sys.exit(1)
if file_format != "csv":
print_error("Only csv file format is supported at the moment, exiting...")
sys.exit(1)
csv_data = process_csv.read_csv(
file_in_path, delimiter=delimiter, header=header)
if data == "identical_timestamps":
timestamps = csv_data[time_column]
timestamps_datetime = [process_csv.format_time(
timestamp, time_utc, time_format) for timestamp in timestamps]
timestamps_interpolated = processing.interpolate_timestamp(
timestamps_datetime)
csv_data[time_column] = format_datetime(
timestamps_interpolated, time_utc, time_format)
file_out = file_in_path if not keep_original else file_in_path[
:-4] + "_processed." + file_format
with open(file_out, "w") as csvfile:
csvwriter = csv.writer(csvfile, delimiter=delimiter)
for row in zip(*csv_data):
csvwriter.writerow(row)
sys.exit()
elif data == "missing_gps":
print_error(
"Error, missing gps interpolation in an external log file not supported yet, exiting...")
sys.exit(1)
else:
print_error("Error unsupported data for interpolation, exiting...")
sys.exit(1)
if import_path:
if not os.path.isdir(import_path):
print_error("Error, specified import path does not exist, exiting...")
sys.exit(1)
# get list of files to process
process_file_list = uploader.get_total_file_list(import_path)
if not len(process_file_list):
print("No images found in the import path " + import_path)
sys.exit(1)
if data == "missing_gps":
# get geotags from images and a list of tuples with images missing geotags
# and their timestamp
geotags, missing_geotags = processing.get_images_geotags(
process_file_list)
if not len(missing_geotags):
print("No images in directory {} missing geotags, exiting...".format(
import_path))
sys.exit(1)
if not len(geotags):
print("No images in directory {} with geotags.".format(import_path))
sys.exit(1)
sys.stdout.write("Interpolating gps for {} images missing geotags.".format(
len(missing_geotags)))
for image, timestamp in tqdm(missing_geotags, desc="Interpolating missing gps"):
# interpolate
try:
lat, lon, bearing, elevation = interpolate_lat_lon(
geotags, timestamp, max_time_delta)
except Exception as e:
print_error("Error, {}, interpolation of latitude and longitude failed for image {}".format(
e, image))
continue
# insert into exif
exif_edit = ExifEdit(image)
if lat and lon:
exif_edit.add_lat_lon(lat, lon)
else:
print_error(
"Error, lat and lon not interpolated for image {}.".format(image))
if bearing:
exif_edit.add_direction(bearing)
else:
if verbose:
print(
"Warning, bearing not interpolated for image {}.".format(image))
if elevation:
exif_edit.add_altitude(elevation)
else:
if verbose:
print(
"Warning, altitude not interpolated for image {}.".format(image))
meta = {}
add_meta_tag(meta, "booleans", "interpolated_gps", True)
exif_edit.add_image_history(meta["MAPMetaTags"])
file_out = image if not keep_original else image[:-
4] + "_processed."
exif_edit.write(filename=file_out)
elif data == "identical_timestamps":
sys.stdout.write("Loading image timestamps.")
# read timestamps
timestamps = []
for image in tqdm(process_file_list, desc="Interpolating identical timestamps"):
# load exif
exif = ExifRead(image)
timestamp = exif.extract_capture_time()
if timestamp:
timestamps.append(timestamp)
else:
print("Capture could not be extracted for image {}.".format(image))
# interpolate
timestamps_interpolated = processing.interpolate_timestamp(
timestamps)
print("")
sys.stdout.write("Interpolating identical timestamps.")
counter = 0
# write back
for image, timestamp in tqdm(zip(process_file_list, timestamps_interpolated), desc="Writing capture time in image EXIF"):
# print progress
counter += 1
sys.stdout.write('.')
if (counter % 100) == 0:
print("")
# load exif
exif_edit = ExifEdit(image)
exif_edit.add_date_time_original(timestamp)
# write to exif
file_out = image if not keep_original else image[
:-4] + "_processed."
exif_edit.write(filename=file_out)
sys.exit()
else:
print_error("Error unsupported data for interpolation, exiting...")
sys.exit(1)
print("")
def post_process(import_path,
split_import_path=None,
video_import_path=None,
summarize=False,
move_all_images=False,
move_duplicates=False,
move_uploaded=False,
move_sequences=False,
save_as_json=False,
list_file_status=False,
push_images=False,
skip_subfolders=False,
verbose=False,
save_local_mapping=False):
# return if nothing specified
if not any([summarize, move_all_images, list_file_status, push_images, move_duplicates, move_uploaded, save_local_mapping, move_sequences]):
print("No post processing action specified.")
return
# sanity check if video file is passed
if video_import_path and not os.path.isdir(video_import_path) and not os.path.isfile(video_import_path):
print("Error, video path " + video_import_path +
" does not exist, exiting...")
sys.exit(1)
if move_all_images:
move_sequences = True
move_duplicates = True
move_uploaded = True
# in case of video processing, adjust the import path
if video_import_path:
# set sampling path
video_sampling_path = "mapillary_sampled_video_frames"
video_dirname = video_import_path if os.path.isdir(
video_import_path) else os.path.dirname(video_import_path)
import_path = os.path.join(os.path.abspath(import_path), video_sampling_path) if import_path else os.path.join(
os.path.abspath(video_dirname), video_sampling_path)
# basic check for all
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" does not exist, exiting...")
sys.exit(1)
if save_local_mapping:
local_mapping = save_local_mapping(import_path)
with open(local_mapping_filepath, "w") as csvfile:
csvwriter = csv.writer(csvfile, delimiter=",")
for row in local_mapping:
csvwriter.writerow(row)
if push_images:
to_be_pushed_files = uploader.get_success_only_manual_upload_file_list(
import_path, skip_subfolders)
params = {}
for image in tqdm(to_be_pushed_files, desc="Pushing images"):
log_root = uploader.log_rootpath(image)
upload_params_path = os.path.join(
log_root, "upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
params[image] = json.load(
jf, object_hook=uploader.ascii_encode_dict)
# get the s3 locations of the sequences
finalize_params = uploader.process_upload_finalization(
to_be_pushed_files, params)
uploader.finalize_upload(finalize_params)
# flag finalization for each file
uploader.flag_finalization(to_be_pushed_files)
if any([summarize, list_file_status, move_uploaded]):
# upload logs
uploaded_files = uploader.get_success_upload_file_list(
import_path, skip_subfolders)
uploaded_files_count = len(uploaded_files)
failed_upload_files = uploader.get_failed_upload_file_list(
import_path, skip_subfolders)
failed_upload_files_count = len(failed_upload_files)
to_be_finalized_files = uploader.get_finalize_file_list(import_path)
to_be_finalized_files_count = len(to_be_finalized_files)
to_be_uploaded_files = uploader.get_upload_file_list(
import_path, skip_subfolders)
to_be_uploaded_files_count = len(to_be_uploaded_files)
if any([summarize, move_sequences]):
total_files = uploader.get_total_file_list(import_path)
total_files_count = len(total_files)
if any([summarize, move_duplicates, list_file_status]):
duplicates_file_list = processing.get_duplicate_file_list(
import_path, skip_subfolders)
duplicates_file_list_count = len(duplicates_file_list)
if summarize:
summary_dict = {}
summary_dict["total images"] = total_files_count
summary_dict["upload summary"] = {
"successfully uploaded": uploaded_files_count,
"failed uploads": failed_upload_files_count,
"uploaded to be finalized": to_be_finalized_files_count
}
# process logs
summary_dict["process summary"] = {}
process_steps = ["user_process", "import_meta_process", "geotag_process",
"sequence_process", "upload_params_process", "mapillary_image_description"]
process_status = ["success", "failed"]
for step in process_steps:
process_success = len(processing.get_process_status_file_list(
import_path, step, "success", skip_subfolders))
process_failed = len(processing.get_process_status_file_list(
import_path, step, "failed", skip_subfolders))
summary_dict["process summary"][step] = {
"failed": process_failed,
"success": process_success
}
summary_dict["process summary"]["duplicates"] = duplicates_file_list_count
summary_dict["process summary"]["processed_not_yet_uploaded"] = to_be_uploaded_files_count
print("Import summary for import path {} :".format(import_path))
print(json.dumps(summary_dict, indent=4))
ipc.send('summary', summary_dict)
if save_as_json:
try:
processing.save_json(summary_dict, os.path.join(
import_path, "mapillary_import_summary.json"))
except Exception as e:
print("Could not save summary into json at {}, due to {}".format(
os.path.join(import_path, "mapillary_import_summary.json"), e))
if list_file_status:
status_list_dict = {}
status_list_dict["successfully uploaded"] = uploaded_files
status_list_dict["failed uploads"] = failed_upload_files
status_list_dict["uploaded to be finalized"] = to_be_finalized_files
status_list_dict["duplicates"] = duplicates_file_list
status_list_dict["processed_not_yet_uploaded"] = to_be_uploaded_files
print("")
print("List of file status for import path {} :".format(import_path))
print(json.dumps(status_list_dict, indent=4))
if save_as_json:
try:
processing.save_json(status_list_dict, os.path.join(
import_path, "mapillary_import_image_status_list.json"))
except Exception as e:
print("Could not save image status list into json at {}, due to {}".format(
os.path.join(import_path, "mapillary_import_image_status_list.json"), e))
split_import_path = split_import_path if split_import_path else import_path
if any([move_sequences, move_duplicates, move_uploaded]):
if not os.path.isdir(split_import_path):
print("Split import path {} does not exist.".format(
split_import_path))
sys.exit(1)
destination_mapping = {}
if move_duplicates:
for image in duplicates_file_list:
destination_mapping[image] = {"basic": ["duplicates"]}
if move_uploaded:
for image in uploaded_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append("uploaded")
else:
destination_mapping[image] = {"basic": ["uploaded"]}
for image in failed_upload_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append("failed_upload")
else:
destination_mapping[image] = {"basic": ["failed_upload"]}
for image in to_be_finalized_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append(
"uploaded_not_finalized")
else:
destination_mapping[image] = {
"basic": ["uploaded_not_finalized"]}
for image in to_be_uploaded_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append("to_be_uploaded")
else:
destination_mapping[image] = {"basic": ["to_be_uploaded"]}
if move_sequences:
destination_mapping = map_images_to_sequences(
destination_mapping, total_files)
for image in destination_mapping:
basic_destination = destination_mapping[image]["basic"] if "basic" in destination_mapping[image] else [
]
sequence_destination = destination_mapping[image][
"sequence"] if "sequence" in destination_mapping[image] else ""
image_destination_path = os.path.join(*([split_import_path] + basic_destination + [
os.path.dirname(image[len(os.path.abspath(import_path)) + 1:])] + [sequence_destination, os.path.basename(image)]))
if not os.path.isdir(os.path.dirname(image_destination_path)):
os.makedirs(os.path.dirname(image_destination_path))
os.rename(image, image_destination_path)
image_logs_dir = uploader.log_rootpath(image)
destination_logs_dir = uploader.log_rootpath(image_destination_path)
if not os.path.isdir(image_logs_dir):
continue
if not os.path.isdir(os.path.dirname(destination_logs_dir)):
os.makedirs(os.path.dirname(destination_logs_dir))
os.rename(image_logs_dir, destination_logs_dir)
def interpolation(data,
file_in_path=None,
file_format="csv",
time_column=0,
delimiter=",",
time_utc=False,
time_format="%Y-%m-%dT%H:%M:%SZ",
header=False,
keep_original=False,
import_path=None,
max_time_delta=1,
verbose=False):
if not data:
print("Error, you must specify the data for interpolation.")
print('Choose between "missing_gps" or "identical_timestamps"')
sys.exit(1)
if not import_path and not file_in_path:
print(
"Error, you must specify a path to data, either path to directory with images or path to an external log file."
)
sys.exit(1)
if file_in_path:
if not os.path.isfile(file_in_path):
print("Error, specified input file does not exist, exiting...")
sys.exit(1)
if file_format != "csv":
print(
"Only csv file format is supported at the moment, exiting...")
sys.exit(1)
csv_data = process_csv.read_csv(file_in_path,
delimiter=delimiter,
header=header)
if data == "identical_timestamps":
timestamps = csv_data[time_column]
timestamps_datetime = [
process_csv.format_time(timestamp, time_utc, time_format)
for timestamp in timestamps
]
timestamps_interpolated = processing.interpolate_timestamp(
timestamps_datetime)
csv_data[time_column] = format_datetime(timestamps_interpolated,
time_utc, time_format)
file_out = file_in_path if not keep_original else file_in_path[:
-4] + "_processed." + file_format
with open(file_out, "w") as csvfile:
csvwriter = csv.writer(csvfile, delimiter=delimiter)
for row in zip(*csv_data):
csvwriter.writerow(row)
sys.exit()
elif data == "missing_gps":
print(
"Error, missing gps interpolation in an external log file not supported yet, exiting..."
)
sys.exit(1)
else:
print("Error unsupported data for interpolation, exiting...")
sys.exit(1)
if import_path:
if not os.path.isdir(import_path):
print("Error, specified import path does not exist, exiting...")
sys.exit(1)
# get list of files to process
process_file_list = uploader.get_total_file_list(import_path)
if not len(process_file_list):
print("No images found in the import path " + import_path)
sys.exit(1)
if data == "missing_gps":
# get geotags from images and a list of tuples with images missing geotags
# and their timestamp
geotags, missing_geotags = processing.get_images_geotags(
process_file_list)
if not len(missing_geotags):
print("No images in directory {} missing geotags, exiting...".
format(import_path))
sys.exit(1)
if not len(geotags):
print("No images in directory {} with geotags.".format(
import_path))
sys.exit(1)
sys.stdout.write(
"Interpolating gps for {} images missing geotags.".format(
len(missing_geotags)))
for image, timestamp in tqdm(missing_geotags,
desc="Interpolating missing gps"):
# interpolate
try:
lat, lon, bearing, elevation = interpolate_lat_lon(
geotags, timestamp, max_time_delta)
except Exception as e:
print(
"Error, {}, interpolation of latitude and longitude failed for image {}"
.format(e, image))
continue
# insert into exif
exif_edit = ExifEdit(image)
if lat and lon:
exif_edit.add_lat_lon(lat, lon)
else:
print("Error, lat and lon not interpolated for image {}.".
format(image))
if bearing:
exif_edit.add_direction(bearing)
else:
if verbose:
print(
"Warning, bearing not interpolated for image {}.".
format(image))
if elevation:
exif_edit.add_altitude(elevation)
else:
if verbose:
print(
"Warning, altitude not interpolated for image {}.".
format(image))
meta = {}
add_meta_tag(meta, "booleans", "interpolated_gps", True)
exif_edit.add_image_history(meta["MAPMetaTags"])
file_out = image if not keep_original else image[:-4] + "_processed."
exif_edit.write(filename=file_out)
elif data == "identical_timestamps":
sys.stdout.write("Loading image timestamps.")
# read timestamps
timestamps = []
for image in tqdm(process_file_list,
desc="Interpolating identical timestamps"):
# load exif
exif = ExifRead(image)
timestamp = exif.extract_capture_time()
if timestamp:
timestamps.append(timestamp)
else:
print(
"Capture could not be extracted for image {}.".format(
image))
# interpolate
timestamps_interpolated = processing.interpolate_timestamp(
timestamps)
print("")
sys.stdout.write("Interpolating identical timestamps.")
counter = 0
# write back
for image, timestamp in tqdm(
zip(process_file_list, timestamps_interpolated),
desc="Writing capture time in image EXIF"):
# print progress
counter += 1
sys.stdout.write('.')
if (counter % 100) == 0:
print("")
# load exif
exif_edit = ExifEdit(image)
exif_edit.add_date_time_original(timestamp)
# write to exif
file_out = image if not keep_original else image[:-4] + "_processed."
exif_edit.write(filename=file_out)
sys.exit()
else:
print("Error unsupported data for interpolation, exiting...")
sys.exit(1)
print("")
def upload(import_path,
verbose=False,
skip_subfolders=False,
video_file=None,
number_threads=None,
max_attempts=None):
'''
Upload local images to Mapillary
Args:
import_path: Directory path to where the images are stored.
verbose: Print extra warnings and errors.
skip_subfolders: Skip images stored in subdirectories.
Returns:
Images are uploaded to Mapillary and flagged locally as uploaded.
'''
# sanity check if video file is passed
if video_file and not (os.path.isdir(video_file)
or os.path.isfile(video_file)):
print("Error, video path " + video_file +
" does not exist, exiting...")
sys.exit(1)
# in case of video processing, adjust the import path
if video_file:
# set sampling path
video_sampling_path = "mapillary_sampled_video_frames"
import_path = os.path.join(
os.path.abspath(import_path),
video_sampling_path) if import_path else os.path.join(
os.path.dirname(video_file), video_sampling_path)
# basic check for all
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" does not exist, exiting...")
sys.exit(1)
# get list of file to process
total_file_list = uploader.get_total_file_list(import_path,
skip_subfolders)
upload_file_list = uploader.get_upload_file_list(import_path,
skip_subfolders)
failed_file_list = uploader.get_failed_upload_file_list(
import_path, skip_subfolders)
success_file_list = uploader.get_success_upload_file_list(
import_path, skip_subfolders)
if len(success_file_list) == len(total_file_list):
print("All images have already been uploaded")
else:
if len(failed_file_list):
upload_failed = raw_input(
"Retry uploading previously failed image uploads? [y/n]: ")
# if yes, add images to the upload list
if upload_failed in ["y", "Y", "yes", "Yes"]:
upload_file_list.extend(failed_file_list)
# verify the images in the upload list, they need to have the image
# description and certain MAP properties
upload_file_list = [
f for f in upload_file_list if verify_mapillary_tag(f)
]
if not len(upload_file_list):
print("No images to upload.")
print(
'Please check if all images contain the required Mapillary metadata. If not, you can use "mapillary_tools process" to add them'
)
sys.exit(1)
# get upload params for the manual upload images, group them per sequence
# and separate direct upload images
params = {}
list_per_sequence_mapping = {}
direct_upload_file_list = []
for image in upload_file_list:
log_root = uploader.log_rootpath(image)
upload_params_path = os.path.join(log_root,
"upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
params[image] = json.load(
jf, object_hook=uploader.ascii_encode_dict)
sequence = params[image]["key"]
if sequence in list_per_sequence_mapping:
list_per_sequence_mapping[sequence].append(image)
else:
list_per_sequence_mapping[sequence] = [image]
else:
direct_upload_file_list.append(image)
# inform how many images are to be uploaded and how many are being skipped
# from upload
print("Uploading {} images with valid mapillary tags (Skipping {})".
format(len(upload_file_list),
len(total_file_list) - len(upload_file_list)))
if len(direct_upload_file_list):
uploader.upload_file_list_direct(direct_upload_file_list,
number_threads, max_attempts)
for idx, sequence in enumerate(list_per_sequence_mapping):
uploader.upload_file_list_manual(
list_per_sequence_mapping[sequence], params, idx,
number_threads, max_attempts)
uploader.print_summary(upload_file_list)
def process_csv(import_path,
csv_path,
filename_column=None,
timestamp_column=None,
latitude_column=None,
longitude_column=None,
heading_column=None,
altitude_column=None,
gps_week_column=None,
time_format="%Y:%m:%d %H:%M:%S.%f",
convert_gps_time=False,
convert_utc_time=False,
delimiter=",",
header=False,
meta_columns=None,
meta_names=None,
meta_types=None,
verbose=False,
keep_original=False):
# sanity checks
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" doesnt not exist, exiting...")
sys.exit(1)
if not csv_path or not os.path.isfile(csv_path):
print("Error, csv file not provided or does not exist. Please specify a valid path to a csv file.")
sys.exit(1)
# get list of file to process
process_file_list = uploader.get_total_file_list(import_path)
if not len(process_file_list):
print("No images found in the import path " + import_path)
sys.exit(1)
if gps_week_column != None and convert_gps_time == False:
print("Error, in order to parse timestamp provided as a combination of GPS week and GPS seconds, you must specify timestamp column and flag --convert_gps_time, exiting...")
sys.exit(1)
if (convert_gps_time != False or convert_utc_time != False) and timestamp_column == None:
print("Error, if specifying a flag to convert timestamp, timestamp column must be provided, exiting...")
sys.exit(1)
column_indexes = [filename_column, timestamp_column,
latitude_column, longitude_column, heading_column, altitude_column, gps_week_column]
if any([column == 0 for column in column_indexes]):
print("Error, csv column numbers start with 1, one of the columns specified is 0.")
sys.exit(1)
column_indexes = map(lambda x: x - 1 if x else None, column_indexes)
# checks for meta arguments if any
meta_columns, meta_names, meta_types = validate_meta_data(
meta_columns, meta_names, meta_types)
# open and process csv
csv_data = read_csv(csv_path,
delimiter=delimiter,
header=header)
# align by filename column if provided, otherwise align in order of image
# names
file_names = None
if filename_column:
file_names = csv_data[filename_column - 1]
else:
if verbose:
print("Warning, filename column not provided, images will be aligned with the csv data in order of the image filenames.")
# process each image
for idx, image in tqdm(enumerate(process_file_list), desc="Inserting csv data in image EXIF"):
# get image entry index
image_index = get_image_index(image, file_names) if file_names else idx
if image_index == None:
print("Warning, no entry found in csv file for image " + image)
continue
# get required data
timestamp, lat, lon, heading, altitude = parse_csv_geotag_data(
csv_data, image_index, column_indexes, convert_gps_time, convert_utc_time, time_format)
# get meta data
meta = parse_csv_meta_data(
csv_data, image_index, meta_columns, meta_types, meta_names)
# insert in image EXIF
exif_edit = ExifEdit(image)
if timestamp:
exif_edit.add_date_time_original(timestamp)
if lat and lon:
exif_edit.add_lat_lon(lat, lon)
if heading:
exif_edit.add_direction(heading)
if altitude:
exif_edit.add_altitude(altitude)
if meta:
exif_edit.add_image_history(meta["MAPMetaTags"])
filename = image
filename_keep_original = processing.processed_images_rootpath(image)
if os.path.isfile(filename_keep_original):
os.remove(filename_keep_original)
if keep_original:
if not os.path.isdir(os.path.dirname(filename_keep_original)):
os.makedirs(os.path.dirname(filename_keep_original))
filename = filename_keep_original
try:
exif_edit.write(filename=filename)
except:
print("Error, image EXIF could not be written back for image " + image)
return None
def post_process(import_path,
split_import_path=None,
video_import_path=None,
summarize=False,
move_all_images=False,
move_duplicates=False,
move_uploaded=False,
move_sequences=False,
save_as_json=False,
list_file_status=False,
push_images=False,
skip_subfolders=False,
verbose=False,
save_local_mapping=False):
# return if nothing specified
if not any([
summarize, move_all_images, list_file_status, push_images,
move_duplicates, move_uploaded, save_local_mapping, move_sequences
]):
print("No post processing action specified.")
return
# sanity check if video file is passed
if video_import_path and not os.path.isdir(
video_import_path) and not os.path.isfile(video_import_path):
print("Error, video path " + video_import_path +
" does not exist, exiting...")
sys.exit(1)
if move_all_images:
move_sequences = True
move_duplicates = True
move_uploaded = True
# in case of video processing, adjust the import path
if video_import_path:
# set sampling path
video_sampling_path = "mapillary_sampled_video_frames"
video_dirname = video_import_path if os.path.isdir(
video_import_path) else os.path.dirname(video_import_path)
import_path = os.path.join(
os.path.abspath(import_path),
video_sampling_path) if import_path else os.path.join(
os.path.abspath(video_dirname), video_sampling_path)
# basic check for all
if not import_path or not os.path.isdir(import_path):
print("Error, import directory " + import_path +
" does not exist, exiting...")
sys.exit(1)
if save_local_mapping:
local_mapping = save_local_mapping(import_path)
with open(local_mapping_filepath, "w") as csvfile:
csvwriter = csv.writer(csvfile, delimiter=",")
for row in local_mapping:
csvwriter.writerow(row)
if push_images:
to_be_pushed_files = uploader.get_success_only_manual_upload_file_list(
import_path, skip_subfolders)
params = {}
for image in tqdm(to_be_pushed_files, desc="Pushing images"):
log_root = uploader.log_rootpath(image)
upload_params_path = os.path.join(log_root,
"upload_params_process.json")
if os.path.isfile(upload_params_path):
with open(upload_params_path, "rb") as jf:
params[image] = json.load(
jf, object_hook=uploader.ascii_encode_dict)
# get the s3 locations of the sequences
finalize_params = uploader.process_upload_finalization(
to_be_pushed_files, params)
uploader.finalize_upload(finalize_params)
# flag finalization for each file
uploader.flag_finalization(to_be_pushed_files)
if any([summarize, list_file_status, move_uploaded]):
# upload logs
uploaded_files = uploader.get_success_upload_file_list(
import_path, skip_subfolders)
uploaded_files_count = len(uploaded_files)
failed_upload_files = uploader.get_failed_upload_file_list(
import_path, skip_subfolders)
failed_upload_files_count = len(failed_upload_files)
to_be_finalized_files = uploader.get_finalize_file_list(import_path)
to_be_finalized_files_count = len(to_be_finalized_files)
to_be_uploaded_files = uploader.get_upload_file_list(
import_path, skip_subfolders)
to_be_uploaded_files_count = len(to_be_uploaded_files)
if any([summarize, move_sequences]):
total_files = uploader.get_total_file_list(import_path)
total_files_count = len(total_files)
if any([summarize, move_duplicates, list_file_status]):
duplicates_file_list = processing.get_duplicate_file_list(
import_path, skip_subfolders)
duplicates_file_list_count = len(duplicates_file_list)
if summarize:
summary_dict = {}
summary_dict["total images"] = total_files_count
summary_dict["upload summary"] = {
"successfully uploaded": uploaded_files_count,
"failed uploads": failed_upload_files_count,
"uploaded to be finalized": to_be_finalized_files_count
}
# process logs
summary_dict["process summary"] = {}
process_steps = [
"user_process", "import_meta_process", "geotag_process",
"sequence_process", "upload_params_process",
"mapillary_image_description"
]
process_status = ["success", "failed"]
for step in process_steps:
process_success = len(
processing.get_process_status_file_list(
import_path, step, "success", skip_subfolders))
process_failed = len(
processing.get_process_status_file_list(
import_path, step, "failed", skip_subfolders))
summary_dict["process summary"][step] = {
"failed": process_failed,
"success": process_success
}
summary_dict["process summary"][
"duplicates"] = duplicates_file_list_count
summary_dict["process summary"][
"processed_not_yet_uploaded"] = to_be_uploaded_files_count
print("Import summary for import path {} :".format(import_path))
print(json.dumps(summary_dict, indent=4))
ipc.send('summary', summary_dict)
if save_as_json:
try:
processing.save_json(
summary_dict,
os.path.join(import_path, "mapillary_import_summary.json"))
except Exception as e:
print(
"Could not save summary into json at {}, due to {}".format(
os.path.join(import_path,
"mapillary_import_summary.json"), e))
if list_file_status:
status_list_dict = {}
status_list_dict["successfully uploaded"] = uploaded_files
status_list_dict["failed uploads"] = failed_upload_files
status_list_dict["uploaded to be finalized"] = to_be_finalized_files
status_list_dict["duplicates"] = duplicates_file_list
status_list_dict["processed_not_yet_uploaded"] = to_be_uploaded_files
print("")
print("List of file status for import path {} :".format(import_path))
print(json.dumps(status_list_dict, indent=4))
if save_as_json:
try:
processing.save_json(
status_list_dict,
os.path.join(import_path,
"mapillary_import_image_status_list.json"))
except Exception as e:
print(
"Could not save image status list into json at {}, due to {}"
.format(
os.path.join(
import_path,
"mapillary_import_image_status_list.json"), e))
split_import_path = split_import_path if split_import_path else import_path
if any([move_sequences, move_duplicates, move_uploaded]):
if not os.path.isdir(split_import_path):
print("Split import path {} does not exist.".format(
split_import_path))
sys.exit(1)
destination_mapping = {}
if move_duplicates:
for image in duplicates_file_list:
destination_mapping[image] = {"basic": ["duplicates"]}
if move_uploaded:
for image in uploaded_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append("uploaded")
else:
destination_mapping[image] = {"basic": ["uploaded"]}
for image in failed_upload_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append("failed_upload")
else:
destination_mapping[image] = {"basic": ["failed_upload"]}
for image in to_be_finalized_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append(
"uploaded_not_finalized")
else:
destination_mapping[image] = {
"basic": ["uploaded_not_finalized"]
}
for image in to_be_uploaded_files:
if image in destination_mapping:
destination_mapping[image]["basic"].append("to_be_uploaded")
else:
destination_mapping[image] = {"basic": ["to_be_uploaded"]}
if move_sequences:
destination_mapping = map_images_to_sequences(destination_mapping,
total_files)
for image in destination_mapping:
basic_destination = destination_mapping[image][
"basic"] if "basic" in destination_mapping[image] else []
sequence_destination = destination_mapping[image][
"sequence"] if "sequence" in destination_mapping[image] else ""
image_destination_path = os.path.join(*(
[split_import_path] + basic_destination +
[os.path.dirname(image[len(os.path.abspath(import_path)) + 1:])] +
[sequence_destination,
os.path.basename(image)]))
if not os.path.isdir(os.path.dirname(image_destination_path)):
os.makedirs(os.path.dirname(image_destination_path))
os.rename(image, image_destination_path)
image_logs_dir = uploader.log_rootpath(image)
destination_logs_dir = uploader.log_rootpath(image_destination_path)
if not os.path.isdir(image_logs_dir):
continue
if not os.path.isdir(os.path.dirname(destination_logs_dir)):
os.makedirs(os.path.dirname(destination_logs_dir))
os.rename(image_logs_dir, destination_logs_dir)
