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project.py
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project.py
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# Copyright (C) 2019 Intel Corporation
#
# SPDX-License-Identifier: MIT
from collections import OrderedDict, defaultdict
from functools import reduce
import git
from glob import glob
import importlib
import inspect
import logging as log
import os
import os.path as osp
import shutil
import sys
from datumaro.components.config import Config, DEFAULT_FORMAT
from datumaro.components.config_model import (Model, Source,
PROJECT_DEFAULT_CONFIG, PROJECT_SCHEMA)
from datumaro.components.extractor import Extractor
from datumaro.components.launcher import ModelTransform
from datumaro.components.dataset_filter import \
XPathDatasetFilter, XPathAnnotationsFilter
def import_foreign_module(name, path, package=None):
module = None
default_path = sys.path.copy()
try:
sys.path = [ osp.abspath(path), ] + default_path
sys.modules.pop(name, None) # remove from cache
module = importlib.import_module(name, package=package)
sys.modules.pop(name) # remove from cache
except Exception:
raise
finally:
sys.path = default_path
return module
class Registry:
def __init__(self, config=None, item_type=None):
self.item_type = item_type
self.items = {}
if config is not None:
self.load(config)
def load(self, config):
pass
def register(self, name, value):
if self.item_type:
value = self.item_type(value)
self.items[name] = value
return value
def unregister(self, name):
return self.items.pop(name, None)
def get(self, key):
return self.items[key] # returns a class / ctor
class ModelRegistry(Registry):
def __init__(self, config=None):
super().__init__(config, item_type=Model)
def load(self, config):
# TODO: list default dir, insert values
if 'models' in config:
for name, model in config.models.items():
self.register(name, model)
class SourceRegistry(Registry):
def __init__(self, config=None):
super().__init__(config, item_type=Source)
def load(self, config):
# TODO: list default dir, insert values
if 'sources' in config:
for name, source in config.sources.items():
self.register(name, source)
class PluginRegistry(Registry):
def __init__(self, config=None, builtin=None, local=None):
super().__init__(config)
from datumaro.components.cli_plugin import CliPlugin
if builtin is not None:
for v in builtin:
k = CliPlugin._get_name(v)
self.register(k, v)
if local is not None:
for v in local:
k = CliPlugin._get_name(v)
self.register(k, v)
class GitWrapper:
def __init__(self, config=None):
self.repo = None
if config is not None and config.project_dir:
self.init(config.project_dir)
@staticmethod
def _git_dir(base_path):
return osp.join(base_path, '.git')
@classmethod
def spawn(cls, path):
spawn = not osp.isdir(cls._git_dir(path))
repo = git.Repo.init(path=path)
if spawn:
repo.config_writer().set_value("user", "name", "User") \
.set_value("user", "email", "user@nowhere.com") \
.release()
# gitpython does not support init, use git directly
repo.git.init()
repo.git.commit('-m', 'Initial commit', '--allow-empty')
return repo
def init(self, path):
self.repo = self.spawn(path)
return self.repo
def is_initialized(self):
return self.repo is not None
def create_submodule(self, name, dst_dir, **kwargs):
self.repo.create_submodule(name, dst_dir, **kwargs)
def has_submodule(self, name):
return name in [submodule.name for submodule in self.repo.submodules]
def remove_submodule(self, name, **kwargs):
return self.repo.submodule(name).remove(**kwargs)
def load_project_as_dataset(url):
# symbol forward declaration
raise NotImplementedError()
class Environment:
_builtin_plugins = None
PROJECT_EXTRACTOR_NAME = 'datumaro_project'
def __init__(self, config=None):
config = Config(config,
fallback=PROJECT_DEFAULT_CONFIG, schema=PROJECT_SCHEMA)
self.models = ModelRegistry(config)
self.sources = SourceRegistry(config)
self.git = GitWrapper(config)
env_dir = osp.join(config.project_dir, config.env_dir)
builtin = self._load_builtin_plugins()
custom = self._load_plugins2(osp.join(env_dir, config.plugins_dir))
select = lambda seq, t: [e for e in seq if issubclass(e, t)]
from datumaro.components.extractor import Transform
from datumaro.components.extractor import SourceExtractor
from datumaro.components.extractor import Importer
from datumaro.components.converter import Converter
from datumaro.components.launcher import Launcher
self.extractors = PluginRegistry(
builtin=select(builtin, SourceExtractor),
local=select(custom, SourceExtractor)
)
self.extractors.register(self.PROJECT_EXTRACTOR_NAME,
load_project_as_dataset)
self.importers = PluginRegistry(
builtin=select(builtin, Importer),
local=select(custom, Importer)
)
self.launchers = PluginRegistry(
builtin=select(builtin, Launcher),
local=select(custom, Launcher)
)
self.converters = PluginRegistry(
builtin=select(builtin, Converter),
local=select(custom, Converter)
)
self.transforms = PluginRegistry(
builtin=select(builtin, Transform),
local=select(custom, Transform)
)
@staticmethod
def _find_plugins(plugins_dir):
plugins = []
if not osp.exists(plugins_dir):
return plugins
for plugin_name in os.listdir(plugins_dir):
p = osp.join(plugins_dir, plugin_name)
if osp.isfile(p) and p.endswith('.py'):
plugins.append((plugins_dir, plugin_name, None))
elif osp.isdir(p):
plugins += [(plugins_dir,
osp.splitext(plugin_name)[0] + '.' + osp.basename(p),
osp.splitext(plugin_name)[0]
)
for p in glob(osp.join(p, '*.py'))]
return plugins
@classmethod
def _import_module(cls, module_dir, module_name, types, package=None):
module = import_foreign_module(osp.splitext(module_name)[0], module_dir,
package=package)
exports = []
if hasattr(module, 'exports'):
exports = module.exports
else:
for symbol in dir(module):
if symbol.startswith('_'):
continue
exports.append(getattr(module, symbol))
exports = [s for s in exports
if inspect.isclass(s) and issubclass(s, types) and not s in types]
return exports
@classmethod
def _load_plugins(cls, plugins_dir, types):
types = tuple(types)
plugins = cls._find_plugins(plugins_dir)
all_exports = []
for module_dir, module_name, package in plugins:
try:
exports = cls._import_module(module_dir, module_name, types,
package)
except Exception as e:
module_search_error = ImportError
try:
module_search_error = ModuleNotFoundError # python 3.6+
except NameError:
pass
message = ["Failed to import module '%s': %s", module_name, e]
if isinstance(e, module_search_error):
log.debug(*message)
else:
log.warning(*message)
continue
log.debug("Imported the following symbols from %s: %s" % \
(
module_name,
', '.join(s.__name__ for s in exports)
)
)
all_exports.extend(exports)
return all_exports
@classmethod
def _load_builtin_plugins(cls):
if not cls._builtin_plugins:
plugins_dir = osp.join(
__file__[: __file__.rfind(osp.join('datumaro', 'components'))],
osp.join('datumaro', 'plugins')
)
assert osp.isdir(plugins_dir), plugins_dir
cls._builtin_plugins = cls._load_plugins2(plugins_dir)
return cls._builtin_plugins
@classmethod
def _load_plugins2(cls, plugins_dir):
from datumaro.components.extractor import Transform
from datumaro.components.extractor import SourceExtractor
from datumaro.components.extractor import Importer
from datumaro.components.converter import Converter
from datumaro.components.launcher import Launcher
types = [SourceExtractor, Converter, Importer, Launcher, Transform]
return cls._load_plugins(plugins_dir, types)
def make_extractor(self, name, *args, **kwargs):
return self.extractors.get(name)(*args, **kwargs)
def make_importer(self, name, *args, **kwargs):
return self.importers.get(name)(*args, **kwargs)
def make_launcher(self, name, *args, **kwargs):
return self.launchers.get(name)(*args, **kwargs)
def make_converter(self, name, *args, **kwargs):
return self.converters.get(name)(*args, **kwargs)
def register_model(self, name, model):
self.models.register(name, model)
def unregister_model(self, name):
self.models.unregister(name)
class Subset(Extractor):
def __init__(self, parent):
self._parent = parent
self.items = OrderedDict()
def __iter__(self):
for item in self.items.values():
yield item
def __len__(self):
return len(self.items)
def categories(self):
return self._parent.categories()
class Dataset(Extractor):
@classmethod
def from_extractors(cls, *sources):
# merge categories
# TODO: implement properly with merging and annotations remapping
categories = {}
for source in sources:
categories.update(source.categories())
for source in sources:
for cat_type, source_cat in source.categories().items():
if not categories[cat_type] == source_cat:
raise NotImplementedError(
"Merging different categories is not implemented yet")
dataset = Dataset(categories=categories)
# merge items
subsets = defaultdict(lambda: Subset(dataset))
for source in sources:
for item in source:
existing_item = subsets[item.subset].items.get(item.id)
if existing_item is not None:
path = existing_item.path
if item.path != path:
path = None
item = cls._merge_items(existing_item, item, path=path)
subsets[item.subset].items[item.id] = item
dataset._subsets = dict(subsets)
return dataset
def __init__(self, categories=None):
super().__init__()
self._subsets = {}
if not categories:
categories = {}
self._categories = categories
def __iter__(self):
for subset in self._subsets.values():
for item in subset:
yield item
def __len__(self):
if self._length is None:
self._length = reduce(lambda s, x: s + len(x),
self._subsets.values(), 0)
return self._length
def get_subset(self, name):
return self._subsets[name]
def subsets(self):
return list(self._subsets)
def categories(self):
return self._categories
def get(self, item_id, subset=None, path=None):
if path:
raise KeyError("Requested dataset item path is not found")
item_id = str(item_id)
subset = subset or ''
subset = self._subsets[subset]
return subset.items[item_id]
def put(self, item, item_id=None, subset=None, path=None):
if path:
raise KeyError("Requested dataset item path is not found")
if item_id is None:
item_id = item.id
if subset is None:
subset = item.subset
item = item.wrap(path=None, annotations=item.annotations)
if item.subset not in self._subsets:
self._subsets[item.subset] = Subset(self)
self._subsets[subset].items[item_id] = item
self._length = None
return item
def extract(self, filter_expr, filter_annotations=False, remove_empty=False):
if filter_annotations:
return self.transform(XPathAnnotationsFilter, filter_expr,
remove_empty)
else:
return self.transform(XPathDatasetFilter, filter_expr)
def update(self, items):
for item in items:
self.put(item)
return self
def define_categories(self, categories):
assert not self._categories
self._categories = categories
@staticmethod
def _lazy_image(item):
# NOTE: avoid https://docs.python.org/3/faq/programming.html#why-do-lambdas-defined-in-a-loop-with-different-values-all-return-the-same-result
return lambda: item.image
@classmethod
def _merge_items(cls, existing_item, current_item, path=None):
return existing_item.wrap(path=path,
image=cls._merge_images(existing_item, current_item),
annotations=cls._merge_anno(
existing_item.annotations, current_item.annotations))
@staticmethod
def _merge_images(existing_item, current_item):
image = None
if existing_item.has_image and current_item.has_image:
if existing_item.image.has_data:
image = existing_item.image
else:
image = current_item.image
if existing_item.image.path != current_item.image.path:
if not existing_item.image.path:
image._path = current_item.image.path
if all([existing_item.image._size, current_item.image._size]):
assert existing_item.image._size == current_item.image._size, "Image info differs for item '%s'" % existing_item.id
elif existing_item.image._size:
image._size = existing_item.image._size
else:
image._size = current_item.image._size
elif existing_item.has_image:
image = existing_item.image
else:
image = current_item.image
return image
@staticmethod
def _merge_anno(a, b):
from itertools import chain
merged = []
for item in chain(a, b):
found = False
for elem in merged:
if elem == item:
found = True
break
if not found:
merged.append(item)
return merged
class ProjectDataset(Dataset):
def __init__(self, project):
super().__init__()
self._project = project
config = self.config
env = self.env
sources = {}
for s_name, source in config.sources.items():
s_format = source.format
if not s_format:
s_format = env.PROJECT_EXTRACTOR_NAME
options = {}
options.update(source.options)
url = source.url
if not source.url:
url = osp.join(config.project_dir, config.sources_dir, s_name)
sources[s_name] = env.make_extractor(s_format,
url, **options)
self._sources = sources
own_source = None
own_source_dir = osp.join(config.project_dir, config.dataset_dir)
if config.project_dir and osp.isdir(own_source_dir):
log.disable(log.INFO)
own_source = env.make_importer(DEFAULT_FORMAT)(own_source_dir) \
.make_dataset()
log.disable(log.NOTSET)
# merge categories
# TODO: implement properly with merging and annotations remapping
categories = {}
for source in self._sources.values():
categories.update(source.categories())
for source in self._sources.values():
for cat_type, source_cat in source.categories().items():
if not categories[cat_type] == source_cat:
raise NotImplementedError(
"Merging different categories is not implemented yet")
if own_source is not None and (not categories or len(own_source) != 0):
categories.update(own_source.categories())
self._categories = categories
# merge items
subsets = defaultdict(lambda: Subset(self))
for source_name, source in self._sources.items():
log.debug("Loading '%s' source contents..." % source_name)
for item in source:
existing_item = subsets[item.subset].items.get(item.id)
if existing_item is not None:
path = existing_item.path
if item.path != path:
path = None # NOTE: move to our own dataset
item = self._merge_items(existing_item, item, path=path)
else:
s_config = config.sources[source_name]
if s_config and \
s_config.format != env.PROJECT_EXTRACTOR_NAME:
# NOTE: consider imported sources as our own dataset
path = None
else:
path = item.path
if path is None:
path = []
path = [source_name] + path
item = item.wrap(path=path, annotations=item.annotations)
subsets[item.subset].items[item.id] = item
# override with our items, fallback to existing images
if own_source is not None:
log.debug("Loading own dataset...")
for item in own_source:
existing_item = subsets[item.subset].items.get(item.id)
if existing_item is not None:
item = item.wrap(path=None,
image=self._merge_images(existing_item, item),
annotations=item.annotations)
subsets[item.subset].items[item.id] = item
# TODO: implement subset remapping when needed
subsets_filter = config.subsets
if len(subsets_filter) != 0:
subsets = { k: v for k, v in subsets.items() if k in subsets_filter}
self._subsets = dict(subsets)
self._length = None
def iterate_own(self):
return self.select(lambda item: not item.path)
def get(self, item_id, subset=None, path=None):
if path:
source = path[0]
rest_path = path[1:]
return self._sources[source].get(
item_id=item_id, subset=subset, path=rest_path)
return super().get(item_id, subset)
def put(self, item, item_id=None, subset=None, path=None):
if path is None:
path = item.path
if path:
source = path[0]
rest_path = path[1:]
# TODO: reverse remapping
self._sources[source].put(item,
item_id=item_id, subset=subset, path=rest_path)
if item_id is None:
item_id = item.id
if subset is None:
subset = item.subset
item = item.wrap(path=path, annotations=item.annotations)
if item.subset not in self._subsets:
self._subsets[item.subset] = Subset(self)
self._subsets[subset].items[item_id] = item
self._length = None
return item
def save(self, save_dir=None, merge=False, recursive=True,
save_images=False):
if save_dir is None:
assert self.config.project_dir
save_dir = self.config.project_dir
project = self._project
else:
merge = True
if merge:
project = Project(Config(self.config))
project.config.remove('sources')
save_dir = osp.abspath(save_dir)
dataset_save_dir = osp.join(save_dir, project.config.dataset_dir)
converter_kwargs = {
'save_images': save_images,
}
save_dir_existed = osp.exists(save_dir)
try:
os.makedirs(save_dir, exist_ok=True)
os.makedirs(dataset_save_dir, exist_ok=True)
if merge:
# merge and save the resulting dataset
self.env.converters.get(DEFAULT_FORMAT).convert(
self, dataset_save_dir, **converter_kwargs)
else:
if recursive:
# children items should already be updated
# so we just save them recursively
for source in self._sources.values():
if isinstance(source, ProjectDataset):
source.save(**converter_kwargs)
self.env.converters.get(DEFAULT_FORMAT).convert(
self.iterate_own(), dataset_save_dir, **converter_kwargs)
project.save(save_dir)
except BaseException:
if not save_dir_existed and osp.isdir(save_dir):
shutil.rmtree(save_dir, ignore_errors=True)
raise
@property
def env(self):
return self._project.env
@property
def config(self):
return self._project.config
@property
def sources(self):
return self._sources
def _save_branch_project(self, extractor, save_dir=None):
extractor = Dataset.from_extractors(extractor) # apply lazy transforms
# NOTE: probably this function should be in the ViewModel layer
save_dir = osp.abspath(save_dir)
if save_dir:
dst_project = Project()
else:
if not self.config.project_dir:
raise Exception("Either a save directory or a project "
"directory should be specified")
save_dir = self.config.project_dir
dst_project = Project(Config(self.config))
dst_project.config.remove('project_dir')
dst_project.config.remove('sources')
dst_project.config.project_name = osp.basename(save_dir)
dst_dataset = dst_project.make_dataset()
dst_dataset.define_categories(extractor.categories())
dst_dataset.update(extractor)
dst_dataset.save(save_dir=save_dir, merge=True)
def transform_project(self, method, save_dir=None, **method_kwargs):
# NOTE: probably this function should be in the ViewModel layer
if isinstance(method, str):
method = self.env.make_transform(method)
transformed = self.transform(method, **method_kwargs)
self._save_branch_project(transformed, save_dir=save_dir)
def apply_model(self, model, save_dir=None, batch_size=1):
# NOTE: probably this function should be in the ViewModel layer
if isinstance(model, str):
launcher = self._project.make_executable_model(model)
self.transform_project(ModelTransform, launcher=launcher,
save_dir=save_dir, batch_size=batch_size)
def export_project(self, save_dir, converter,
filter_expr=None, filter_annotations=False, remove_empty=False):
# NOTE: probably this function should be in the ViewModel layer
dataset = self
if filter_expr:
dataset = dataset.extract(filter_expr,
filter_annotations=filter_annotations,
remove_empty=remove_empty)
save_dir = osp.abspath(save_dir)
save_dir_existed = osp.exists(save_dir)
try:
os.makedirs(save_dir, exist_ok=True)
converter(dataset, save_dir)
except BaseException:
if not save_dir_existed:
shutil.rmtree(save_dir)
raise
def extract_project(self, filter_expr, filter_annotations=False,
save_dir=None, remove_empty=False):
# NOTE: probably this function should be in the ViewModel layer
filtered = self
if filter_expr:
filtered = self.extract(filter_expr,
filter_annotations=filter_annotations,
remove_empty=remove_empty)
self._save_branch_project(filtered, save_dir=save_dir)
class Project:
@classmethod
def load(cls, path):
path = osp.abspath(path)
config_path = osp.join(path, PROJECT_DEFAULT_CONFIG.env_dir,
PROJECT_DEFAULT_CONFIG.project_filename)
config = Config.parse(config_path)
config.project_dir = path
config.project_filename = osp.basename(config_path)
return Project(config)
def save(self, save_dir=None):
config = self.config
if save_dir is None:
assert config.project_dir
project_dir = config.project_dir
else:
project_dir = save_dir
env_dir = osp.join(project_dir, config.env_dir)
save_dir = osp.abspath(env_dir)
project_dir_existed = osp.exists(project_dir)
env_dir_existed = osp.exists(env_dir)
try:
os.makedirs(save_dir, exist_ok=True)
config_path = osp.join(save_dir, config.project_filename)
config.dump(config_path)
except BaseException:
if not env_dir_existed:
shutil.rmtree(save_dir, ignore_errors=True)
if not project_dir_existed:
shutil.rmtree(project_dir, ignore_errors=True)
raise
@staticmethod
def generate(save_dir, config=None):
config = Config(config)
config.project_dir = save_dir
project = Project(config)
project.save(save_dir)
return project
@staticmethod
def import_from(path, dataset_format, env=None, **kwargs):
if env is None:
env = Environment()
importer = env.make_importer(dataset_format)
return importer(path, **kwargs)
def __init__(self, config=None):
self.config = Config(config,
fallback=PROJECT_DEFAULT_CONFIG, schema=PROJECT_SCHEMA)
self.env = Environment(self.config)
def make_dataset(self):
return ProjectDataset(self)
def add_source(self, name, value=None):
if value is None or isinstance(value, (dict, Config)):
value = Source(value)
self.config.sources[name] = value
self.env.sources.register(name, value)
def remove_source(self, name):
self.config.sources.remove(name)
self.env.sources.unregister(name)
def get_source(self, name):
try:
return self.config.sources[name]
except KeyError:
raise KeyError("Source '%s' is not found" % name)
def get_subsets(self):
return self.config.subsets
def set_subsets(self, value):
if not value:
self.config.remove('subsets')
else:
self.config.subsets = value
def add_model(self, name, value=None):
if value is None or isinstance(value, (dict, Config)):
value = Model(value)
self.env.register_model(name, value)
self.config.models[name] = value
def get_model(self, name):
try:
return self.env.models.get(name)
except KeyError:
raise KeyError("Model '%s' is not found" % name)
def remove_model(self, name):
self.config.models.remove(name)
self.env.unregister_model(name)
def make_executable_model(self, name):
model = self.get_model(name)
return self.env.make_launcher(model.launcher,
**model.options, model_dir=self.local_model_dir(name))
def make_source_project(self, name):
source = self.get_source(name)
config = Config(self.config)
config.remove('sources')
config.remove('subsets')
project = Project(config)
project.add_source(name, source)
return project
def local_model_dir(self, model_name):
return osp.join(
self.config.env_dir, self.config.models_dir, model_name)
def local_source_dir(self, source_name):
return osp.join(self.config.sources_dir, source_name)
# pylint: disable=function-redefined
def load_project_as_dataset(url):
# implement the function declared above
return Project.load(url).make_dataset()
# pylint: enable=function-redefined