def download_local_nfs_image(request, project_id, dataset_id, candidate_id,
frame):
username = request.user
user_id = AccountManager.get_id_by_username(username)
if not Permission.hasPermission(user_id, 'get_annotationwork', project_id):
raise PermissionDenied
dataset_manager = DatasetManager()
dataset_dir = dataset_manager.get_dataset_file_path(user_id, dataset_id)
original_manager = OriginalManager()
candidate = original_manager.get_dataset_candidate(candidate_id)
analyzed_info = json.loads(candidate['analyzed_info'])
msg_type = analyzed_info['msg_type']
if msg_type == 'sensor_msgs/Image':
extension = '.jpg'
elif msg_type == 'sensor_msgs/PointCloud2':
extension = '.pcd'
file_path = dataset_dir + candidate_id + '_' + str(frame).zfill(
6) + extension
image = open(file_path, "rb").read()
if msg_type == 'sensor_msgs/Image':
return HttpResponse(image, content_type="image/jpeg")
return HttpResponse(image, content_type="application/octet-stream")
def __get_raw_data_config(original_id, candidates):
records = {}
for candidate_id in candidates:
original_manager = OriginalManager()
candidate = original_manager.get_dataset_candidate(candidate_id)
analyzed_info = json.loads(candidate['analyzed_info'])
records[analyzed_info['topic_name']] = candidate_id
raw_data_config = {
'original_id': original_id,
'candidates': candidates,
'records': records,
}
return raw_data_config
def analyze(cls, user_id, project_id, original_id):
project = ProjectManager().get_project(project_id, user_id)
label_type = project['label_type']
original = OriginalManager().get_original(project_id, original_id, status='uploaded')
storage = StorageSerializer().get_storage(project_id, original['storage_id'])
storage_config = copy.deepcopy(storage['storage_config'])
original_path = StorageSerializer.get_original_path(
storage['storage_type'], storage['storage_config'], original['name'])
storage_config.update({'path': original_path})
automan_config = cls.__get_automan_config(user_id)
automan_config.update({'path': '/projects/' + project_id + '/originals/' + str(original_id) + '/', 'label_type': label_type})
job_config = {
'storage_type': storage['storage_type'],
'storage_config': storage_config,
'automan_config': automan_config
}
job_config_json = json.dumps(job_config)
new_job = Job(
job_type='analyzer',
user_id=user_id,
project_id=project_id,
job_config=job_config_json)
new_job.save()
if original['file_type'] == 'rosbag':
job = RosbagAnalyzer(**job_config)
job.create(cls.__generate_job_name(new_job.id, 'analyzer'))
res = job.run()
return res
else:
raise ValidationError()
def extract(cls, user_id, project_id, original_id, candidates):
original = OriginalManager().get_original(project_id, original_id, status='analyzed')
storage = StorageSerializer().get_storage(project_id, original['storage_id'])
storage_config = copy.deepcopy(storage['storage_config'])
original_path = StorageSerializer.get_original_path(
storage['storage_type'], storage['storage_config'], original['name'])
storage_config.update({'path': original_path})
output_dir = StorageSerializer.get_dataset_output_dir(
storage['storage_type'], storage['storage_config'], original['name'], candidates)
storage_config.update({'output_dir': output_dir})
automan_config = cls.__get_automan_config(user_id)
automan_config.update({'path': '/projects/' + project_id + '/datasets/'})
raw_data_config = cls.__get_raw_data_config(project_id, original_id, candidates)
job_config = {
'storage_type': storage['storage_type'],
'storage_config': storage_config,
'automan_config': automan_config,
'raw_data_config': raw_data_config
}
job_config_json = json.dumps(job_config)
new_job = Job(
job_type='extractor',
user_id=user_id,
project_id=project_id,
job_config=job_config_json)
new_job.save()
if original['file_type'] == 'rosbag':
job = RosbagExtractor(**job_config)
job.create(cls.__generate_job_name(new_job.id, 'extractor'))
res = job.run()
return res
else:
raise ValidationError()
def archive(cls, user_id, project_id, dataset_id, original_id, annotation_id):
original = OriginalManager().get_original(project_id, original_id, status='analyzed')
storage = StorageSerializer().get_storage(project_id, original['storage_id'])
storage_config = copy.deepcopy(storage['storage_config'])
automan_config = cls.__get_automan_config(user_id)
automan_config.update({'path': '/projects/' + str(project_id) + '/annotations/' + str(annotation_id) + '/'})
archive_config = cls.__get_archive_info(user_id, project_id, dataset_id, annotation_id, original_id)
job_config = {
'storage_type': storage['storage_type'],
'storage_config': storage_config,
'automan_config': automan_config,
'archive_config': archive_config,
}
job_config_json = json.dumps(job_config)
new_job = Job(
job_type='archiver',
user_id=user_id,
project_id=project_id,
job_config=job_config_json)
new_job.save()
job = AnnotationArchiver(**job_config)
job.create(cls.__generate_job_name(new_job.id, 'archiver'))
res = job.run()
return res
def get_frame(request, project_id, dataset_id, candidate_id, frame):
username = request.user
user_id = AccountManager.get_id_by_username(username)
if not Permission.hasPermission(user_id, 'get_annotationwork', project_id):
raise PermissionDenied
dataset = DatasetManager().get_dataset(user_id, dataset_id)
original = OriginalManager().get_original(project_id,
dataset['original_id'])
storage = StorageSerializer().get_storage(project_id,
original['storage_id'])
if storage['storage_type'] == 'LOCAL_NFS':
image_link = request.build_absolute_uri(request.path) + 'image/'
elif storage['storage_type'] == 'AWS_S3':
ext = __get_extension(candidate_id)
key = (dataset['file_path'] + candidate_id + '_' +
str(frame).zfill(6) + ext)
image_link = AwsS3Client().get_s3_down_url(
storage['storage_config']['bucket'], key)
else:
raise UnknownStorageTypeError
frame = DatasetFrameManager.get_dataset_frame(project_id, dataset_id,
frame,
storage['storage_type'])
content = {'image_link': image_link, 'frame': frame['frame']}
return HttpResponse(status=200,
content=json.dumps(content),
content_type='application/json')
def annotation(request, project_id, annotation_id):
username = request.user
user_id = AccountManager.get_id_by_username(username)
annotation_manager = AnnotationManager()
if request.method == 'GET':
if not Permission.hasPermission(user_id, 'get_annotationwork',
project_id):
raise PermissionDenied
contents = annotation_manager.get_annotation(annotation_id)
return HttpResponse(content=json.dumps(contents),
status=200,
content_type='application/json')
elif request.method == 'POST':
file_path = request.data.get('file_path')
file_name = request.data.get('file_name')
annotation_manager.set_archive(annotation_id, file_path, file_name)
return HttpResponse(status=201,
content=json.dumps({}),
content_type='application/json')
else:
if not Permission.hasPermission(user_id, 'delete_annotationwork',
project_id):
raise PermissionDenied
dataset_id = annotation_manager.get_annotation(
annotation_id)['dataset_id']
original_id = DatasetManager().get_dataset(user_id,
dataset_id)['original_id']
storage_id = OriginalManager().get_original(project_id,
original_id)['storage_id']
storage = StorageSerializer().get_storage(project_id, storage_id)
annotation_manager.delete_annotation(annotation_id, storage)
return HttpResponse(status=204)
def destroy(self, request, project_id, dataset_id):
username = request.user
dataset_manager = DatasetManager()
user_id = AccountManager.get_id_by_username(username)
if not Permission.hasPermission(user_id, 'delete_dataset', project_id):
raise PermissionDenied
original_id = DatasetManager().get_dataset(user_id,
dataset_id)['original_id']
storage_id = OriginalManager().get_original(project_id,
original_id)['storage_id']
storage = StorageSerializer().get_storage(project_id, storage_id)
dataset_manager.delete_dataset(user_id, dataset_id, storage)
return HttpResponse(status=204)
def extract(cls, user_id, project_id, original_id, candidates, name):
original = OriginalManager().get_original(project_id,
original_id,
status='analyzed')
storage_manager = StorageManager(project_id, original['storage_id'])
storage_config = copy.deepcopy(
storage_manager.storage['storage_config'])
original_path = storage_manager.get_original_filepath(original['name'])
output_dir = storage_manager.get_dataset_dirname(
original['name'], candidates)
print('output_dirname: ' + output_dir)
storage_config.update({
'path': original_path,
'output_dir': output_dir,
'storage_id': original['storage_id']
})
automan_config = cls.__get_automan_config(user_id)
automan_config.update({
'path':
'/projects/' + project_id + '/datasets/',
'presigned':
'/projects/' + project_id + '/storages/upload/'
})
raw_data_config = cls.__get_raw_data_config(project_id, original_id,
candidates, name)
job_config = {
'storage_type': storage_manager.storage['storage_type'],
'storage_config': storage_config,
'automan_config': automan_config,
'raw_data_config': raw_data_config,
}
job_config_json = json.dumps(job_config)
new_job = Job(job_type='extractor',
user_id=user_id,
project_id=project_id,
job_config=job_config_json)
new_job.save()
if original['file_type'] == 'rosbag':
job = RosbagExtractor(**job_config)
job.create(cls.__generate_job_name(new_job.id, 'extractor'))
res = job.run(namespace=settings.JOB_NAMESPACE)
return res
else:
raise ValidationError()
def download_archived_link(request, project_id, annotation_id):
username = request.user
user_id = AccountManager.get_id_by_username(username)
annotation_manager = AnnotationManager()
dataset_id = annotation_manager.get_annotation(annotation_id)['dataset_id']
original_id = DatasetManager().get_dataset(user_id,
dataset_id)['original_id']
storage_id = OriginalManager().get_original(project_id,
original_id)['storage_id']
storage = StorageSerializer().get_storage(project_id, storage_id)
if storage['storage_type'] == 'LOCAL_NFS':
content = request.build_absolute_uri(request.path) + 'local/'
elif storage['storage_type'] == 'AWS_S3':
archive_path = annotation_manager.get_archive_path(annotation_id)
content = AwsS3Client().get_s3_down_url(
storage['storage_config']['bucket'], archive_path)
else:
raise UnknownStorageTypeError
return HttpResponse(status=200, content=content, content_type='text/plain')
def archive(cls, user_id, project_id, dataset_id, original_id,
annotation_id, include_image: bool):
original = OriginalManager().get_original(project_id,
original_id,
status='analyzed')
storage_manager = StorageManager(project_id, original['storage_id'])
storage_config = copy.deepcopy(
storage_manager.storage['storage_config'])
original_path = storage_manager.get_original_filepath(original['name'])
storage_config.update({
'path': original_path,
'storage_id': original['storage_id']
})
automan_config = cls.__get_automan_config(user_id)
automan_config.update({
'path':
'/projects/' + str(project_id) + '/annotations/' +
str(annotation_id) + '/',
'presigned':
'/projects/' + str(project_id) + '/storages/upload/'
})
archive_config = cls.__get_archive_info(
storage_manager.storage['storage_type'], user_id, project_id,
dataset_id, annotation_id, original_id, include_image)
job_config = {
'storage_type': storage_manager.storage['storage_type'],
'storage_config': storage_config,
'automan_config': automan_config,
'archive_config': archive_config,
}
job_config_json = json.dumps(job_config)
new_job = Job(job_type='archiver',
user_id=user_id,
project_id=project_id,
job_config=job_config_json)
new_job.save()
job = AnnotationArchiver(**job_config)
job.create(cls.__generate_job_name(new_job.id, 'archiver'))
res = job.run(namespace=settings.JOB_NAMESPACE)
return res
def test_get_originals(self):
original_manager = OriginalManager()
rosbags = original_manager.get_originals(PROJECT_ID)
self.assertEqual(len(rosbags), 2)
def __get_extension(candidate_id):
candidate = OriginalManager().get_dataset_candidate(candidate_id)
msg_type = json.loads(candidate['analyzed_info'])['msg_type']
if msg_type == 'sensor_msgs/PointCloud2':
return '.pcd'
return '.jpg'