fiftyone.brain#
- fiftyone.brain.internal
- fiftyone.brain.internal.core
- fiftyone.brain.internal.core.duplicates
- fiftyone.brain.internal.core.elasticsearch
ElasticsearchSimilarityConfig
ElasticsearchSimilarityConfig.method
ElasticsearchSimilarityConfig.hosts
ElasticsearchSimilarityConfig.cloud_id
ElasticsearchSimilarityConfig.username
ElasticsearchSimilarityConfig.password
ElasticsearchSimilarityConfig.api_key
ElasticsearchSimilarityConfig.ca_certs
ElasticsearchSimilarityConfig.bearer_auth
ElasticsearchSimilarityConfig.ssl_assert_fingerprint
ElasticsearchSimilarityConfig.verify_certs
ElasticsearchSimilarityConfig.max_k
ElasticsearchSimilarityConfig.supports_least_similarity
ElasticsearchSimilarityConfig.supported_aggregations
ElasticsearchSimilarityConfig.load_credentials()
ElasticsearchSimilarityConfig.attributes()
ElasticsearchSimilarityConfig.base_config_cls()
ElasticsearchSimilarityConfig.build()
ElasticsearchSimilarityConfig.builder()
ElasticsearchSimilarityConfig.cls
ElasticsearchSimilarityConfig.copy()
ElasticsearchSimilarityConfig.custom_attributes()
ElasticsearchSimilarityConfig.default()
ElasticsearchSimilarityConfig.from_dict()
ElasticsearchSimilarityConfig.from_json()
ElasticsearchSimilarityConfig.from_kwargs()
ElasticsearchSimilarityConfig.from_str()
ElasticsearchSimilarityConfig.get_class_name()
ElasticsearchSimilarityConfig.load_default()
ElasticsearchSimilarityConfig.parse_array()
ElasticsearchSimilarityConfig.parse_bool()
ElasticsearchSimilarityConfig.parse_categorical()
ElasticsearchSimilarityConfig.parse_dict()
ElasticsearchSimilarityConfig.parse_int()
ElasticsearchSimilarityConfig.parse_mutually_exclusive_fields()
ElasticsearchSimilarityConfig.parse_number()
ElasticsearchSimilarityConfig.parse_object()
ElasticsearchSimilarityConfig.parse_object_array()
ElasticsearchSimilarityConfig.parse_object_dict()
ElasticsearchSimilarityConfig.parse_path()
ElasticsearchSimilarityConfig.parse_raw()
ElasticsearchSimilarityConfig.parse_string()
ElasticsearchSimilarityConfig.run_cls
ElasticsearchSimilarityConfig.serialize()
ElasticsearchSimilarityConfig.to_str()
ElasticsearchSimilarityConfig.type
ElasticsearchSimilarityConfig.validate_all_or_nothing_fields()
ElasticsearchSimilarityConfig.write_json()
ElasticsearchSimilarity
ElasticsearchSimilarity.ensure_requirements()
ElasticsearchSimilarity.ensure_usage_requirements()
ElasticsearchSimilarity.initialize()
ElasticsearchSimilarity.cleanup()
ElasticsearchSimilarity.delete_run()
ElasticsearchSimilarity.delete_runs()
ElasticsearchSimilarity.from_config()
ElasticsearchSimilarity.from_dict()
ElasticsearchSimilarity.from_json()
ElasticsearchSimilarity.from_kwargs()
ElasticsearchSimilarity.get_fields()
ElasticsearchSimilarity.get_run_info()
ElasticsearchSimilarity.has_cached_run_results()
ElasticsearchSimilarity.list_runs()
ElasticsearchSimilarity.load_run_results()
ElasticsearchSimilarity.load_run_view()
ElasticsearchSimilarity.parse()
ElasticsearchSimilarity.register_run()
ElasticsearchSimilarity.rename()
ElasticsearchSimilarity.run_info_cls()
ElasticsearchSimilarity.save_run_info()
ElasticsearchSimilarity.save_run_results()
ElasticsearchSimilarity.update_run_config()
ElasticsearchSimilarity.update_run_key()
ElasticsearchSimilarity.validate()
ElasticsearchSimilarity.validate_run()
ElasticsearchSimilarityIndex
ElasticsearchSimilarityIndex.total_index_size
ElasticsearchSimilarityIndex.client
ElasticsearchSimilarityIndex.add_to_index()
ElasticsearchSimilarityIndex.remove_from_index()
ElasticsearchSimilarityIndex.attributes()
ElasticsearchSimilarityIndex.backend
ElasticsearchSimilarityIndex.base_results_cls()
ElasticsearchSimilarityIndex.clear_view()
ElasticsearchSimilarityIndex.cls
ElasticsearchSimilarityIndex.compute_embeddings()
ElasticsearchSimilarityIndex.config
ElasticsearchSimilarityIndex.copy()
ElasticsearchSimilarityIndex.current_label_ids
ElasticsearchSimilarityIndex.current_sample_ids
ElasticsearchSimilarityIndex.custom_attributes()
ElasticsearchSimilarityIndex.from_dict()
ElasticsearchSimilarityIndex.from_json()
ElasticsearchSimilarityIndex.from_str()
ElasticsearchSimilarityIndex.get_class_name()
ElasticsearchSimilarityIndex.get_embeddings()
ElasticsearchSimilarityIndex.get_model()
ElasticsearchSimilarityIndex.has_view
ElasticsearchSimilarityIndex.index_size
ElasticsearchSimilarityIndex.is_external
ElasticsearchSimilarityIndex.key
ElasticsearchSimilarityIndex.label_ids
ElasticsearchSimilarityIndex.missing_size
ElasticsearchSimilarityIndex.reload()
ElasticsearchSimilarityIndex.sample_ids
ElasticsearchSimilarityIndex.samples
ElasticsearchSimilarityIndex.save()
ElasticsearchSimilarityIndex.save_config()
ElasticsearchSimilarityIndex.serialize()
ElasticsearchSimilarityIndex.sort_by_similarity()
ElasticsearchSimilarityIndex.to_str()
ElasticsearchSimilarityIndex.use_view()
ElasticsearchSimilarityIndex.values()
ElasticsearchSimilarityIndex.view
ElasticsearchSimilarityIndex.write_json()
ElasticsearchSimilarityIndex.cleanup()
- fiftyone.brain.internal.core.hardness
compute_hardness()
HardnessConfig
HardnessConfig.type
HardnessConfig.method
HardnessConfig.attributes()
HardnessConfig.base_config_cls()
HardnessConfig.build()
HardnessConfig.builder()
HardnessConfig.cls
HardnessConfig.copy()
HardnessConfig.custom_attributes()
HardnessConfig.default()
HardnessConfig.from_dict()
HardnessConfig.from_json()
HardnessConfig.from_kwargs()
HardnessConfig.from_str()
HardnessConfig.get_class_name()
HardnessConfig.load_credentials()
HardnessConfig.load_default()
HardnessConfig.parse_array()
HardnessConfig.parse_bool()
HardnessConfig.parse_categorical()
HardnessConfig.parse_dict()
HardnessConfig.parse_int()
HardnessConfig.parse_mutually_exclusive_fields()
HardnessConfig.parse_number()
HardnessConfig.parse_object()
HardnessConfig.parse_object_array()
HardnessConfig.parse_object_dict()
HardnessConfig.parse_path()
HardnessConfig.parse_raw()
HardnessConfig.parse_string()
HardnessConfig.run_cls
HardnessConfig.serialize()
HardnessConfig.to_str()
HardnessConfig.validate_all_or_nothing_fields()
HardnessConfig.write_json()
Hardness
Hardness.ensure_requirements()
Hardness.register_samples()
Hardness.process_image()
Hardness.get_fields()
Hardness.cleanup()
Hardness.delete_run()
Hardness.delete_runs()
Hardness.ensure_usage_requirements()
Hardness.from_config()
Hardness.from_dict()
Hardness.from_json()
Hardness.from_kwargs()
Hardness.get_run_info()
Hardness.has_cached_run_results()
Hardness.list_runs()
Hardness.load_run_results()
Hardness.load_run_view()
Hardness.parse()
Hardness.register_run()
Hardness.rename()
Hardness.run_info_cls()
Hardness.save_run_info()
Hardness.save_run_results()
Hardness.update_run_config()
Hardness.update_run_key()
Hardness.validate()
Hardness.validate_run()
- fiftyone.brain.internal.core.lancedb
LanceDBSimilarityConfig
LanceDBSimilarityConfig.method
LanceDBSimilarityConfig.uri
LanceDBSimilarityConfig.max_k
LanceDBSimilarityConfig.supports_least_similarity
LanceDBSimilarityConfig.supported_aggregations
LanceDBSimilarityConfig.load_credentials()
LanceDBSimilarityConfig.attributes()
LanceDBSimilarityConfig.base_config_cls()
LanceDBSimilarityConfig.build()
LanceDBSimilarityConfig.builder()
LanceDBSimilarityConfig.cls
LanceDBSimilarityConfig.copy()
LanceDBSimilarityConfig.custom_attributes()
LanceDBSimilarityConfig.default()
LanceDBSimilarityConfig.from_dict()
LanceDBSimilarityConfig.from_json()
LanceDBSimilarityConfig.from_kwargs()
LanceDBSimilarityConfig.from_str()
LanceDBSimilarityConfig.get_class_name()
LanceDBSimilarityConfig.load_default()
LanceDBSimilarityConfig.parse_array()
LanceDBSimilarityConfig.parse_bool()
LanceDBSimilarityConfig.parse_categorical()
LanceDBSimilarityConfig.parse_dict()
LanceDBSimilarityConfig.parse_int()
LanceDBSimilarityConfig.parse_mutually_exclusive_fields()
LanceDBSimilarityConfig.parse_number()
LanceDBSimilarityConfig.parse_object()
LanceDBSimilarityConfig.parse_object_array()
LanceDBSimilarityConfig.parse_object_dict()
LanceDBSimilarityConfig.parse_path()
LanceDBSimilarityConfig.parse_raw()
LanceDBSimilarityConfig.parse_string()
LanceDBSimilarityConfig.run_cls
LanceDBSimilarityConfig.serialize()
LanceDBSimilarityConfig.to_str()
LanceDBSimilarityConfig.type
LanceDBSimilarityConfig.validate_all_or_nothing_fields()
LanceDBSimilarityConfig.write_json()
LanceDBSimilarity
LanceDBSimilarity.ensure_requirements()
LanceDBSimilarity.ensure_usage_requirements()
LanceDBSimilarity.initialize()
LanceDBSimilarity.cleanup()
LanceDBSimilarity.delete_run()
LanceDBSimilarity.delete_runs()
LanceDBSimilarity.from_config()
LanceDBSimilarity.from_dict()
LanceDBSimilarity.from_json()
LanceDBSimilarity.from_kwargs()
LanceDBSimilarity.get_fields()
LanceDBSimilarity.get_run_info()
LanceDBSimilarity.has_cached_run_results()
LanceDBSimilarity.list_runs()
LanceDBSimilarity.load_run_results()
LanceDBSimilarity.load_run_view()
LanceDBSimilarity.parse()
LanceDBSimilarity.register_run()
LanceDBSimilarity.rename()
LanceDBSimilarity.run_info_cls()
LanceDBSimilarity.save_run_info()
LanceDBSimilarity.save_run_results()
LanceDBSimilarity.update_run_config()
LanceDBSimilarity.update_run_key()
LanceDBSimilarity.validate()
LanceDBSimilarity.validate_run()
LanceDBSimilarityIndex
LanceDBSimilarityIndex.table
LanceDBSimilarityIndex.total_index_size
LanceDBSimilarityIndex.add_to_index()
LanceDBSimilarityIndex.remove_from_index()
LanceDBSimilarityIndex.get_embeddings()
LanceDBSimilarityIndex.cleanup()
LanceDBSimilarityIndex.attributes()
LanceDBSimilarityIndex.backend
LanceDBSimilarityIndex.base_results_cls()
LanceDBSimilarityIndex.clear_view()
LanceDBSimilarityIndex.cls
LanceDBSimilarityIndex.compute_embeddings()
LanceDBSimilarityIndex.config
LanceDBSimilarityIndex.copy()
LanceDBSimilarityIndex.current_label_ids
LanceDBSimilarityIndex.current_sample_ids
LanceDBSimilarityIndex.custom_attributes()
LanceDBSimilarityIndex.from_dict()
LanceDBSimilarityIndex.from_json()
LanceDBSimilarityIndex.from_str()
LanceDBSimilarityIndex.get_class_name()
LanceDBSimilarityIndex.get_model()
LanceDBSimilarityIndex.has_view
LanceDBSimilarityIndex.index_size
LanceDBSimilarityIndex.is_external
LanceDBSimilarityIndex.key
LanceDBSimilarityIndex.label_ids
LanceDBSimilarityIndex.missing_size
LanceDBSimilarityIndex.reload()
LanceDBSimilarityIndex.sample_ids
LanceDBSimilarityIndex.samples
LanceDBSimilarityIndex.save()
LanceDBSimilarityIndex.save_config()
LanceDBSimilarityIndex.serialize()
LanceDBSimilarityIndex.sort_by_similarity()
LanceDBSimilarityIndex.to_str()
LanceDBSimilarityIndex.use_view()
LanceDBSimilarityIndex.values()
LanceDBSimilarityIndex.view
LanceDBSimilarityIndex.write_json()
- fiftyone.brain.internal.core.leaky_splits
compute_leaky_splits()
LeakySplitsConfig
LeakySplitsConfig.type
LeakySplitsConfig.method
LeakySplitsConfig.attributes()
LeakySplitsConfig.base_config_cls()
LeakySplitsConfig.build()
LeakySplitsConfig.builder()
LeakySplitsConfig.cls
LeakySplitsConfig.copy()
LeakySplitsConfig.custom_attributes()
LeakySplitsConfig.default()
LeakySplitsConfig.from_dict()
LeakySplitsConfig.from_json()
LeakySplitsConfig.from_kwargs()
LeakySplitsConfig.from_str()
LeakySplitsConfig.get_class_name()
LeakySplitsConfig.load_credentials()
LeakySplitsConfig.load_default()
LeakySplitsConfig.parse_array()
LeakySplitsConfig.parse_bool()
LeakySplitsConfig.parse_categorical()
LeakySplitsConfig.parse_dict()
LeakySplitsConfig.parse_int()
LeakySplitsConfig.parse_mutually_exclusive_fields()
LeakySplitsConfig.parse_number()
LeakySplitsConfig.parse_object()
LeakySplitsConfig.parse_object_array()
LeakySplitsConfig.parse_object_dict()
LeakySplitsConfig.parse_path()
LeakySplitsConfig.parse_raw()
LeakySplitsConfig.parse_string()
LeakySplitsConfig.run_cls
LeakySplitsConfig.serialize()
LeakySplitsConfig.to_str()
LeakySplitsConfig.validate_all_or_nothing_fields()
LeakySplitsConfig.write_json()
LeakySplits
LeakySplits.initialize()
LeakySplits.get_fields()
LeakySplits.cleanup()
LeakySplits.delete_run()
LeakySplits.delete_runs()
LeakySplits.ensure_requirements()
LeakySplits.ensure_usage_requirements()
LeakySplits.from_config()
LeakySplits.from_dict()
LeakySplits.from_json()
LeakySplits.from_kwargs()
LeakySplits.get_run_info()
LeakySplits.has_cached_run_results()
LeakySplits.list_runs()
LeakySplits.load_run_results()
LeakySplits.load_run_view()
LeakySplits.parse()
LeakySplits.register_run()
LeakySplits.rename()
LeakySplits.run_info_cls()
LeakySplits.save_run_info()
LeakySplits.save_run_results()
LeakySplits.update_run_config()
LeakySplits.update_run_key()
LeakySplits.validate()
LeakySplits.validate_run()
LeakySplitsIndex
LeakySplitsIndex.split_views
LeakySplitsIndex.thresh
LeakySplitsIndex.leak_ids
LeakySplitsIndex.find_leaks()
LeakySplitsIndex.leaks_view()
LeakySplitsIndex.leaks_for_sample()
LeakySplitsIndex.no_leaks_view()
LeakySplitsIndex.tag_leaks()
LeakySplitsIndex.attributes()
LeakySplitsIndex.backend
LeakySplitsIndex.base_results_cls()
LeakySplitsIndex.cls
LeakySplitsIndex.config
LeakySplitsIndex.copy()
LeakySplitsIndex.custom_attributes()
LeakySplitsIndex.from_dict()
LeakySplitsIndex.from_json()
LeakySplitsIndex.from_str()
LeakySplitsIndex.get_class_name()
LeakySplitsIndex.key
LeakySplitsIndex.samples
LeakySplitsIndex.save()
LeakySplitsIndex.save_config()
LeakySplitsIndex.serialize()
LeakySplitsIndex.to_str()
LeakySplitsIndex.write_json()
- fiftyone.brain.internal.core.milvus
MilvusSimilarityConfig
MilvusSimilarityConfig.method
MilvusSimilarityConfig.uri
MilvusSimilarityConfig.user
MilvusSimilarityConfig.password
MilvusSimilarityConfig.secure
MilvusSimilarityConfig.token
MilvusSimilarityConfig.db_name
MilvusSimilarityConfig.client_key_path
MilvusSimilarityConfig.client_pem_path
MilvusSimilarityConfig.ca_pem_path
MilvusSimilarityConfig.server_pem_path
MilvusSimilarityConfig.server_name
MilvusSimilarityConfig.max_k
MilvusSimilarityConfig.supports_least_similarity
MilvusSimilarityConfig.supported_aggregations
MilvusSimilarityConfig.index_params
MilvusSimilarityConfig.search_params
MilvusSimilarityConfig.load_credentials()
MilvusSimilarityConfig.attributes()
MilvusSimilarityConfig.base_config_cls()
MilvusSimilarityConfig.build()
MilvusSimilarityConfig.builder()
MilvusSimilarityConfig.cls
MilvusSimilarityConfig.copy()
MilvusSimilarityConfig.custom_attributes()
MilvusSimilarityConfig.default()
MilvusSimilarityConfig.from_dict()
MilvusSimilarityConfig.from_json()
MilvusSimilarityConfig.from_kwargs()
MilvusSimilarityConfig.from_str()
MilvusSimilarityConfig.get_class_name()
MilvusSimilarityConfig.load_default()
MilvusSimilarityConfig.parse_array()
MilvusSimilarityConfig.parse_bool()
MilvusSimilarityConfig.parse_categorical()
MilvusSimilarityConfig.parse_dict()
MilvusSimilarityConfig.parse_int()
MilvusSimilarityConfig.parse_mutually_exclusive_fields()
MilvusSimilarityConfig.parse_number()
MilvusSimilarityConfig.parse_object()
MilvusSimilarityConfig.parse_object_array()
MilvusSimilarityConfig.parse_object_dict()
MilvusSimilarityConfig.parse_path()
MilvusSimilarityConfig.parse_raw()
MilvusSimilarityConfig.parse_string()
MilvusSimilarityConfig.run_cls
MilvusSimilarityConfig.serialize()
MilvusSimilarityConfig.to_str()
MilvusSimilarityConfig.type
MilvusSimilarityConfig.validate_all_or_nothing_fields()
MilvusSimilarityConfig.write_json()
MilvusSimilarity
MilvusSimilarity.ensure_requirements()
MilvusSimilarity.ensure_usage_requirements()
MilvusSimilarity.initialize()
MilvusSimilarity.cleanup()
MilvusSimilarity.delete_run()
MilvusSimilarity.delete_runs()
MilvusSimilarity.from_config()
MilvusSimilarity.from_dict()
MilvusSimilarity.from_json()
MilvusSimilarity.from_kwargs()
MilvusSimilarity.get_fields()
MilvusSimilarity.get_run_info()
MilvusSimilarity.has_cached_run_results()
MilvusSimilarity.list_runs()
MilvusSimilarity.load_run_results()
MilvusSimilarity.load_run_view()
MilvusSimilarity.parse()
MilvusSimilarity.register_run()
MilvusSimilarity.rename()
MilvusSimilarity.run_info_cls()
MilvusSimilarity.save_run_info()
MilvusSimilarity.save_run_results()
MilvusSimilarity.update_run_config()
MilvusSimilarity.update_run_key()
MilvusSimilarity.validate()
MilvusSimilarity.validate_run()
MilvusSimilarityIndex
MilvusSimilarityIndex.collection
MilvusSimilarityIndex.total_index_size
MilvusSimilarityIndex.add_to_index()
MilvusSimilarityIndex.attributes()
MilvusSimilarityIndex.backend
MilvusSimilarityIndex.base_results_cls()
MilvusSimilarityIndex.clear_view()
MilvusSimilarityIndex.cls
MilvusSimilarityIndex.compute_embeddings()
MilvusSimilarityIndex.config
MilvusSimilarityIndex.copy()
MilvusSimilarityIndex.current_label_ids
MilvusSimilarityIndex.current_sample_ids
MilvusSimilarityIndex.custom_attributes()
MilvusSimilarityIndex.from_dict()
MilvusSimilarityIndex.from_json()
MilvusSimilarityIndex.from_str()
MilvusSimilarityIndex.get_class_name()
MilvusSimilarityIndex.get_model()
MilvusSimilarityIndex.has_view
MilvusSimilarityIndex.index_size
MilvusSimilarityIndex.is_external
MilvusSimilarityIndex.key
MilvusSimilarityIndex.label_ids
MilvusSimilarityIndex.missing_size
MilvusSimilarityIndex.reload()
MilvusSimilarityIndex.sample_ids
MilvusSimilarityIndex.samples
MilvusSimilarityIndex.save()
MilvusSimilarityIndex.save_config()
MilvusSimilarityIndex.serialize()
MilvusSimilarityIndex.sort_by_similarity()
MilvusSimilarityIndex.to_str()
MilvusSimilarityIndex.use_view()
MilvusSimilarityIndex.values()
MilvusSimilarityIndex.view
MilvusSimilarityIndex.write_json()
MilvusSimilarityIndex.remove_from_index()
MilvusSimilarityIndex.get_embeddings()
MilvusSimilarityIndex.cleanup()
- fiftyone.brain.internal.core.mistakenness
compute_mistakenness()
MistakennessMethodConfig
MistakennessMethodConfig.type
MistakennessMethodConfig.attributes()
MistakennessMethodConfig.base_config_cls()
MistakennessMethodConfig.build()
MistakennessMethodConfig.builder()
MistakennessMethodConfig.cls
MistakennessMethodConfig.copy()
MistakennessMethodConfig.custom_attributes()
MistakennessMethodConfig.default()
MistakennessMethodConfig.from_dict()
MistakennessMethodConfig.from_json()
MistakennessMethodConfig.from_kwargs()
MistakennessMethodConfig.from_str()
MistakennessMethodConfig.get_class_name()
MistakennessMethodConfig.load_credentials()
MistakennessMethodConfig.load_default()
MistakennessMethodConfig.method
MistakennessMethodConfig.parse_array()
MistakennessMethodConfig.parse_bool()
MistakennessMethodConfig.parse_categorical()
MistakennessMethodConfig.parse_dict()
MistakennessMethodConfig.parse_int()
MistakennessMethodConfig.parse_mutually_exclusive_fields()
MistakennessMethodConfig.parse_number()
MistakennessMethodConfig.parse_object()
MistakennessMethodConfig.parse_object_array()
MistakennessMethodConfig.parse_object_dict()
MistakennessMethodConfig.parse_path()
MistakennessMethodConfig.parse_raw()
MistakennessMethodConfig.parse_string()
MistakennessMethodConfig.run_cls
MistakennessMethodConfig.serialize()
MistakennessMethodConfig.to_str()
MistakennessMethodConfig.validate_all_or_nothing_fields()
MistakennessMethodConfig.write_json()
MistakennessMethod
MistakennessMethod.ensure_requirements()
MistakennessMethod.register_samples()
MistakennessMethod.cleanup()
MistakennessMethod.delete_run()
MistakennessMethod.delete_runs()
MistakennessMethod.ensure_usage_requirements()
MistakennessMethod.from_config()
MistakennessMethod.from_dict()
MistakennessMethod.from_json()
MistakennessMethod.from_kwargs()
MistakennessMethod.get_fields()
MistakennessMethod.get_run_info()
MistakennessMethod.has_cached_run_results()
MistakennessMethod.list_runs()
MistakennessMethod.load_run_results()
MistakennessMethod.load_run_view()
MistakennessMethod.parse()
MistakennessMethod.register_run()
MistakennessMethod.rename()
MistakennessMethod.run_info_cls()
MistakennessMethod.save_run_info()
MistakennessMethod.save_run_results()
MistakennessMethod.update_run_config()
MistakennessMethod.update_run_key()
MistakennessMethod.validate()
MistakennessMethod.validate_run()
ClassificationMistakennessConfig
ClassificationMistakennessConfig.method
ClassificationMistakennessConfig.attributes()
ClassificationMistakennessConfig.base_config_cls()
ClassificationMistakennessConfig.build()
ClassificationMistakennessConfig.builder()
ClassificationMistakennessConfig.cls
ClassificationMistakennessConfig.copy()
ClassificationMistakennessConfig.custom_attributes()
ClassificationMistakennessConfig.default()
ClassificationMistakennessConfig.from_dict()
ClassificationMistakennessConfig.from_json()
ClassificationMistakennessConfig.from_kwargs()
ClassificationMistakennessConfig.from_str()
ClassificationMistakennessConfig.get_class_name()
ClassificationMistakennessConfig.load_credentials()
ClassificationMistakennessConfig.load_default()
ClassificationMistakennessConfig.parse_array()
ClassificationMistakennessConfig.parse_bool()
ClassificationMistakennessConfig.parse_categorical()
ClassificationMistakennessConfig.parse_dict()
ClassificationMistakennessConfig.parse_int()
ClassificationMistakennessConfig.parse_mutually_exclusive_fields()
ClassificationMistakennessConfig.parse_number()
ClassificationMistakennessConfig.parse_object()
ClassificationMistakennessConfig.parse_object_array()
ClassificationMistakennessConfig.parse_object_dict()
ClassificationMistakennessConfig.parse_path()
ClassificationMistakennessConfig.parse_raw()
ClassificationMistakennessConfig.parse_string()
ClassificationMistakennessConfig.run_cls
ClassificationMistakennessConfig.serialize()
ClassificationMistakennessConfig.to_str()
ClassificationMistakennessConfig.type
ClassificationMistakennessConfig.validate_all_or_nothing_fields()
ClassificationMistakennessConfig.write_json()
ClassificationMistakenness
ClassificationMistakenness.process_image()
ClassificationMistakenness.get_fields()
ClassificationMistakenness.cleanup()
ClassificationMistakenness.delete_run()
ClassificationMistakenness.delete_runs()
ClassificationMistakenness.ensure_requirements()
ClassificationMistakenness.ensure_usage_requirements()
ClassificationMistakenness.from_config()
ClassificationMistakenness.from_dict()
ClassificationMistakenness.from_json()
ClassificationMistakenness.from_kwargs()
ClassificationMistakenness.get_run_info()
ClassificationMistakenness.has_cached_run_results()
ClassificationMistakenness.list_runs()
ClassificationMistakenness.load_run_results()
ClassificationMistakenness.load_run_view()
ClassificationMistakenness.parse()
ClassificationMistakenness.register_run()
ClassificationMistakenness.register_samples()
ClassificationMistakenness.rename()
ClassificationMistakenness.run_info_cls()
ClassificationMistakenness.save_run_info()
ClassificationMistakenness.save_run_results()
ClassificationMistakenness.update_run_config()
ClassificationMistakenness.update_run_key()
ClassificationMistakenness.validate()
ClassificationMistakenness.validate_run()
DetectionMistakennessConfig
DetectionMistakennessConfig.method
DetectionMistakennessConfig.attributes()
DetectionMistakennessConfig.base_config_cls()
DetectionMistakennessConfig.build()
DetectionMistakennessConfig.builder()
DetectionMistakennessConfig.cls
DetectionMistakennessConfig.copy()
DetectionMistakennessConfig.custom_attributes()
DetectionMistakennessConfig.default()
DetectionMistakennessConfig.from_dict()
DetectionMistakennessConfig.from_json()
DetectionMistakennessConfig.from_kwargs()
DetectionMistakennessConfig.from_str()
DetectionMistakennessConfig.get_class_name()
DetectionMistakennessConfig.load_credentials()
DetectionMistakennessConfig.load_default()
DetectionMistakennessConfig.parse_array()
DetectionMistakennessConfig.parse_bool()
DetectionMistakennessConfig.parse_categorical()
DetectionMistakennessConfig.parse_dict()
DetectionMistakennessConfig.parse_int()
DetectionMistakennessConfig.parse_mutually_exclusive_fields()
DetectionMistakennessConfig.parse_number()
DetectionMistakennessConfig.parse_object()
DetectionMistakennessConfig.parse_object_array()
DetectionMistakennessConfig.parse_object_dict()
DetectionMistakennessConfig.parse_path()
DetectionMistakennessConfig.parse_raw()
DetectionMistakennessConfig.parse_string()
DetectionMistakennessConfig.run_cls
DetectionMistakennessConfig.serialize()
DetectionMistakennessConfig.to_str()
DetectionMistakennessConfig.type
DetectionMistakennessConfig.validate_all_or_nothing_fields()
DetectionMistakennessConfig.write_json()
DetectionMistakenness
DetectionMistakenness.process_image()
DetectionMistakenness.get_fields()
DetectionMistakenness.cleanup()
DetectionMistakenness.delete_run()
DetectionMistakenness.delete_runs()
DetectionMistakenness.ensure_requirements()
DetectionMistakenness.ensure_usage_requirements()
DetectionMistakenness.from_config()
DetectionMistakenness.from_dict()
DetectionMistakenness.from_json()
DetectionMistakenness.from_kwargs()
DetectionMistakenness.get_run_info()
DetectionMistakenness.has_cached_run_results()
DetectionMistakenness.list_runs()
DetectionMistakenness.load_run_results()
DetectionMistakenness.load_run_view()
DetectionMistakenness.parse()
DetectionMistakenness.register_run()
DetectionMistakenness.register_samples()
DetectionMistakenness.rename()
DetectionMistakenness.run_info_cls()
DetectionMistakenness.save_run_info()
DetectionMistakenness.save_run_results()
DetectionMistakenness.update_run_config()
DetectionMistakenness.update_run_key()
DetectionMistakenness.validate()
DetectionMistakenness.validate_run()
- fiftyone.brain.internal.core.mongodb
MongoDBSimilarityConfig
MongoDBSimilarityConfig.method
MongoDBSimilarityConfig.max_k
MongoDBSimilarityConfig.supports_least_similarity
MongoDBSimilarityConfig.supported_aggregations
MongoDBSimilarityConfig.attributes()
MongoDBSimilarityConfig.base_config_cls()
MongoDBSimilarityConfig.build()
MongoDBSimilarityConfig.builder()
MongoDBSimilarityConfig.cls
MongoDBSimilarityConfig.copy()
MongoDBSimilarityConfig.custom_attributes()
MongoDBSimilarityConfig.default()
MongoDBSimilarityConfig.from_dict()
MongoDBSimilarityConfig.from_json()
MongoDBSimilarityConfig.from_kwargs()
MongoDBSimilarityConfig.from_str()
MongoDBSimilarityConfig.get_class_name()
MongoDBSimilarityConfig.load_credentials()
MongoDBSimilarityConfig.load_default()
MongoDBSimilarityConfig.parse_array()
MongoDBSimilarityConfig.parse_bool()
MongoDBSimilarityConfig.parse_categorical()
MongoDBSimilarityConfig.parse_dict()
MongoDBSimilarityConfig.parse_int()
MongoDBSimilarityConfig.parse_mutually_exclusive_fields()
MongoDBSimilarityConfig.parse_number()
MongoDBSimilarityConfig.parse_object()
MongoDBSimilarityConfig.parse_object_array()
MongoDBSimilarityConfig.parse_object_dict()
MongoDBSimilarityConfig.parse_path()
MongoDBSimilarityConfig.parse_raw()
MongoDBSimilarityConfig.parse_string()
MongoDBSimilarityConfig.run_cls
MongoDBSimilarityConfig.serialize()
MongoDBSimilarityConfig.to_str()
MongoDBSimilarityConfig.type
MongoDBSimilarityConfig.validate_all_or_nothing_fields()
MongoDBSimilarityConfig.write_json()
MongoDBSimilarity
MongoDBSimilarity.ensure_requirements()
MongoDBSimilarity.ensure_usage_requirements()
MongoDBSimilarity.initialize()
MongoDBSimilarity.cleanup()
MongoDBSimilarity.delete_run()
MongoDBSimilarity.delete_runs()
MongoDBSimilarity.from_config()
MongoDBSimilarity.from_dict()
MongoDBSimilarity.from_json()
MongoDBSimilarity.from_kwargs()
MongoDBSimilarity.get_fields()
MongoDBSimilarity.get_run_info()
MongoDBSimilarity.has_cached_run_results()
MongoDBSimilarity.list_runs()
MongoDBSimilarity.load_run_results()
MongoDBSimilarity.load_run_view()
MongoDBSimilarity.parse()
MongoDBSimilarity.register_run()
MongoDBSimilarity.rename()
MongoDBSimilarity.run_info_cls()
MongoDBSimilarity.save_run_info()
MongoDBSimilarity.save_run_results()
MongoDBSimilarity.update_run_config()
MongoDBSimilarity.update_run_key()
MongoDBSimilarity.validate()
MongoDBSimilarity.validate_run()
MongoDBSimilarityIndex
MongoDBSimilarityIndex.is_external
MongoDBSimilarityIndex.total_index_size
MongoDBSimilarityIndex.ready
MongoDBSimilarityIndex.add_to_index()
MongoDBSimilarityIndex.remove_from_index()
MongoDBSimilarityIndex.get_embeddings()
MongoDBSimilarityIndex.reload()
MongoDBSimilarityIndex.cleanup()
MongoDBSimilarityIndex.attributes()
MongoDBSimilarityIndex.backend
MongoDBSimilarityIndex.base_results_cls()
MongoDBSimilarityIndex.clear_view()
MongoDBSimilarityIndex.cls
MongoDBSimilarityIndex.compute_embeddings()
MongoDBSimilarityIndex.config
MongoDBSimilarityIndex.copy()
MongoDBSimilarityIndex.current_label_ids
MongoDBSimilarityIndex.current_sample_ids
MongoDBSimilarityIndex.custom_attributes()
MongoDBSimilarityIndex.from_dict()
MongoDBSimilarityIndex.from_json()
MongoDBSimilarityIndex.from_str()
MongoDBSimilarityIndex.get_class_name()
MongoDBSimilarityIndex.get_model()
MongoDBSimilarityIndex.has_view
MongoDBSimilarityIndex.index_size
MongoDBSimilarityIndex.key
MongoDBSimilarityIndex.label_ids
MongoDBSimilarityIndex.missing_size
MongoDBSimilarityIndex.sample_ids
MongoDBSimilarityIndex.samples
MongoDBSimilarityIndex.save()
MongoDBSimilarityIndex.save_config()
MongoDBSimilarityIndex.serialize()
MongoDBSimilarityIndex.sort_by_similarity()
MongoDBSimilarityIndex.to_str()
MongoDBSimilarityIndex.use_view()
MongoDBSimilarityIndex.values()
MongoDBSimilarityIndex.view
MongoDBSimilarityIndex.write_json()
- fiftyone.brain.internal.core.mosaic
MosaicSimilarityConfig
MosaicSimilarityConfig.method
MosaicSimilarityConfig.workspace_url
MosaicSimilarityConfig.service_principal_client_id
MosaicSimilarityConfig.service_principal_client_secret
MosaicSimilarityConfig.personal_access_token
MosaicSimilarityConfig.max_k
MosaicSimilarityConfig.supports_least_similarity
MosaicSimilarityConfig.supported_aggregations
MosaicSimilarityConfig.load_credentials()
MosaicSimilarityConfig.attributes()
MosaicSimilarityConfig.base_config_cls()
MosaicSimilarityConfig.build()
MosaicSimilarityConfig.builder()
MosaicSimilarityConfig.cls
MosaicSimilarityConfig.copy()
MosaicSimilarityConfig.custom_attributes()
MosaicSimilarityConfig.default()
MosaicSimilarityConfig.from_dict()
MosaicSimilarityConfig.from_json()
MosaicSimilarityConfig.from_kwargs()
MosaicSimilarityConfig.from_str()
MosaicSimilarityConfig.get_class_name()
MosaicSimilarityConfig.load_default()
MosaicSimilarityConfig.parse_array()
MosaicSimilarityConfig.parse_bool()
MosaicSimilarityConfig.parse_categorical()
MosaicSimilarityConfig.parse_dict()
MosaicSimilarityConfig.parse_int()
MosaicSimilarityConfig.parse_mutually_exclusive_fields()
MosaicSimilarityConfig.parse_number()
MosaicSimilarityConfig.parse_object()
MosaicSimilarityConfig.parse_object_array()
MosaicSimilarityConfig.parse_object_dict()
MosaicSimilarityConfig.parse_path()
MosaicSimilarityConfig.parse_raw()
MosaicSimilarityConfig.parse_string()
MosaicSimilarityConfig.run_cls
MosaicSimilarityConfig.serialize()
MosaicSimilarityConfig.to_str()
MosaicSimilarityConfig.type
MosaicSimilarityConfig.validate_all_or_nothing_fields()
MosaicSimilarityConfig.write_json()
MosaicSimilarity
MosaicSimilarity.ensure_requirements()
MosaicSimilarity.ensure_usage_requirements()
MosaicSimilarity.initialize()
MosaicSimilarity.cleanup()
MosaicSimilarity.delete_run()
MosaicSimilarity.delete_runs()
MosaicSimilarity.from_config()
MosaicSimilarity.from_dict()
MosaicSimilarity.from_json()
MosaicSimilarity.from_kwargs()
MosaicSimilarity.get_fields()
MosaicSimilarity.get_run_info()
MosaicSimilarity.has_cached_run_results()
MosaicSimilarity.list_runs()
MosaicSimilarity.load_run_results()
MosaicSimilarity.load_run_view()
MosaicSimilarity.parse()
MosaicSimilarity.register_run()
MosaicSimilarity.rename()
MosaicSimilarity.run_info_cls()
MosaicSimilarity.save_run_info()
MosaicSimilarity.save_run_results()
MosaicSimilarity.update_run_config()
MosaicSimilarity.update_run_key()
MosaicSimilarity.validate()
MosaicSimilarity.validate_run()
MosaicSimilarityIndex
MosaicSimilarityIndex.client
MosaicSimilarityIndex.total_index_size
MosaicSimilarityIndex.add_to_index()
MosaicSimilarityIndex.remove_from_index()
MosaicSimilarityIndex.get_embeddings()
MosaicSimilarityIndex.cleanup()
MosaicSimilarityIndex.attributes()
MosaicSimilarityIndex.backend
MosaicSimilarityIndex.base_results_cls()
MosaicSimilarityIndex.clear_view()
MosaicSimilarityIndex.cls
MosaicSimilarityIndex.compute_embeddings()
MosaicSimilarityIndex.config
MosaicSimilarityIndex.copy()
MosaicSimilarityIndex.current_label_ids
MosaicSimilarityIndex.current_sample_ids
MosaicSimilarityIndex.custom_attributes()
MosaicSimilarityIndex.from_dict()
MosaicSimilarityIndex.from_json()
MosaicSimilarityIndex.from_str()
MosaicSimilarityIndex.get_class_name()
MosaicSimilarityIndex.get_model()
MosaicSimilarityIndex.has_view
MosaicSimilarityIndex.index_size
MosaicSimilarityIndex.is_external
MosaicSimilarityIndex.key
MosaicSimilarityIndex.label_ids
MosaicSimilarityIndex.missing_size
MosaicSimilarityIndex.reload()
MosaicSimilarityIndex.sample_ids
MosaicSimilarityIndex.samples
MosaicSimilarityIndex.save()
MosaicSimilarityIndex.save_config()
MosaicSimilarityIndex.serialize()
MosaicSimilarityIndex.sort_by_similarity()
MosaicSimilarityIndex.to_str()
MosaicSimilarityIndex.use_view()
MosaicSimilarityIndex.values()
MosaicSimilarityIndex.view
MosaicSimilarityIndex.write_json()
- fiftyone.brain.internal.core.pgvector
PgVectorSimilarityConfig
PgVectorSimilarityConfig.method
PgVectorSimilarityConfig.connection_string
PgVectorSimilarityConfig.max_k
PgVectorSimilarityConfig.supports_least_similarity
PgVectorSimilarityConfig.supported_aggregations
PgVectorSimilarityConfig.load_credentials()
PgVectorSimilarityConfig.attributes()
PgVectorSimilarityConfig.base_config_cls()
PgVectorSimilarityConfig.build()
PgVectorSimilarityConfig.builder()
PgVectorSimilarityConfig.cls
PgVectorSimilarityConfig.copy()
PgVectorSimilarityConfig.custom_attributes()
PgVectorSimilarityConfig.default()
PgVectorSimilarityConfig.from_dict()
PgVectorSimilarityConfig.from_json()
PgVectorSimilarityConfig.from_kwargs()
PgVectorSimilarityConfig.from_str()
PgVectorSimilarityConfig.get_class_name()
PgVectorSimilarityConfig.load_default()
PgVectorSimilarityConfig.parse_array()
PgVectorSimilarityConfig.parse_bool()
PgVectorSimilarityConfig.parse_categorical()
PgVectorSimilarityConfig.parse_dict()
PgVectorSimilarityConfig.parse_int()
PgVectorSimilarityConfig.parse_mutually_exclusive_fields()
PgVectorSimilarityConfig.parse_number()
PgVectorSimilarityConfig.parse_object()
PgVectorSimilarityConfig.parse_object_array()
PgVectorSimilarityConfig.parse_object_dict()
PgVectorSimilarityConfig.parse_path()
PgVectorSimilarityConfig.parse_raw()
PgVectorSimilarityConfig.parse_string()
PgVectorSimilarityConfig.run_cls
PgVectorSimilarityConfig.serialize()
PgVectorSimilarityConfig.to_str()
PgVectorSimilarityConfig.type
PgVectorSimilarityConfig.validate_all_or_nothing_fields()
PgVectorSimilarityConfig.write_json()
PgVectorSimilarity
PgVectorSimilarity.ensure_requirements()
PgVectorSimilarity.ensure_usage_requirements()
PgVectorSimilarity.initialize()
PgVectorSimilarity.cleanup()
PgVectorSimilarity.delete_run()
PgVectorSimilarity.delete_runs()
PgVectorSimilarity.from_config()
PgVectorSimilarity.from_dict()
PgVectorSimilarity.from_json()
PgVectorSimilarity.from_kwargs()
PgVectorSimilarity.get_fields()
PgVectorSimilarity.get_run_info()
PgVectorSimilarity.has_cached_run_results()
PgVectorSimilarity.list_runs()
PgVectorSimilarity.load_run_results()
PgVectorSimilarity.load_run_view()
PgVectorSimilarity.parse()
PgVectorSimilarity.register_run()
PgVectorSimilarity.rename()
PgVectorSimilarity.run_info_cls()
PgVectorSimilarity.save_run_info()
PgVectorSimilarity.save_run_results()
PgVectorSimilarity.update_run_config()
PgVectorSimilarity.update_run_key()
PgVectorSimilarity.validate()
PgVectorSimilarity.validate_run()
PgVectorSimilarityIndex
PgVectorSimilarityIndex.total_index_size
PgVectorSimilarityIndex.create_hnsw_index()
PgVectorSimilarityIndex.add_to_index()
PgVectorSimilarityIndex.remove_from_index()
PgVectorSimilarityIndex.close_connections()
PgVectorSimilarityIndex.get_embeddings_by_id()
PgVectorSimilarityIndex.get_embeddings()
PgVectorSimilarityIndex.cleanup()
PgVectorSimilarityIndex.attributes()
PgVectorSimilarityIndex.backend
PgVectorSimilarityIndex.base_results_cls()
PgVectorSimilarityIndex.clear_view()
PgVectorSimilarityIndex.cls
PgVectorSimilarityIndex.compute_embeddings()
PgVectorSimilarityIndex.config
PgVectorSimilarityIndex.copy()
PgVectorSimilarityIndex.current_label_ids
PgVectorSimilarityIndex.current_sample_ids
PgVectorSimilarityIndex.custom_attributes()
PgVectorSimilarityIndex.from_dict()
PgVectorSimilarityIndex.from_json()
PgVectorSimilarityIndex.from_str()
PgVectorSimilarityIndex.get_class_name()
PgVectorSimilarityIndex.get_model()
PgVectorSimilarityIndex.has_view
PgVectorSimilarityIndex.index_size
PgVectorSimilarityIndex.is_external
PgVectorSimilarityIndex.key
PgVectorSimilarityIndex.label_ids
PgVectorSimilarityIndex.missing_size
PgVectorSimilarityIndex.reload()
PgVectorSimilarityIndex.sample_ids
PgVectorSimilarityIndex.samples
PgVectorSimilarityIndex.save()
PgVectorSimilarityIndex.save_config()
PgVectorSimilarityIndex.serialize()
PgVectorSimilarityIndex.sort_by_similarity()
PgVectorSimilarityIndex.to_str()
PgVectorSimilarityIndex.use_view()
PgVectorSimilarityIndex.values()
PgVectorSimilarityIndex.view
PgVectorSimilarityIndex.write_json()
- fiftyone.brain.internal.core.pinecone
PineconeSimilarityConfig
PineconeSimilarityConfig.method
PineconeSimilarityConfig.api_key
PineconeSimilarityConfig.cloud
PineconeSimilarityConfig.region
PineconeSimilarityConfig.environment
PineconeSimilarityConfig.max_k
PineconeSimilarityConfig.supports_least_similarity
PineconeSimilarityConfig.supported_aggregations
PineconeSimilarityConfig.load_credentials()
PineconeSimilarityConfig.attributes()
PineconeSimilarityConfig.base_config_cls()
PineconeSimilarityConfig.build()
PineconeSimilarityConfig.builder()
PineconeSimilarityConfig.cls
PineconeSimilarityConfig.copy()
PineconeSimilarityConfig.custom_attributes()
PineconeSimilarityConfig.default()
PineconeSimilarityConfig.from_dict()
PineconeSimilarityConfig.from_json()
PineconeSimilarityConfig.from_kwargs()
PineconeSimilarityConfig.from_str()
PineconeSimilarityConfig.get_class_name()
PineconeSimilarityConfig.load_default()
PineconeSimilarityConfig.parse_array()
PineconeSimilarityConfig.parse_bool()
PineconeSimilarityConfig.parse_categorical()
PineconeSimilarityConfig.parse_dict()
PineconeSimilarityConfig.parse_int()
PineconeSimilarityConfig.parse_mutually_exclusive_fields()
PineconeSimilarityConfig.parse_number()
PineconeSimilarityConfig.parse_object()
PineconeSimilarityConfig.parse_object_array()
PineconeSimilarityConfig.parse_object_dict()
PineconeSimilarityConfig.parse_path()
PineconeSimilarityConfig.parse_raw()
PineconeSimilarityConfig.parse_string()
PineconeSimilarityConfig.run_cls
PineconeSimilarityConfig.serialize()
PineconeSimilarityConfig.to_str()
PineconeSimilarityConfig.type
PineconeSimilarityConfig.validate_all_or_nothing_fields()
PineconeSimilarityConfig.write_json()
PineconeSimilarity
PineconeSimilarity.ensure_requirements()
PineconeSimilarity.ensure_usage_requirements()
PineconeSimilarity.initialize()
PineconeSimilarity.cleanup()
PineconeSimilarity.delete_run()
PineconeSimilarity.delete_runs()
PineconeSimilarity.from_config()
PineconeSimilarity.from_dict()
PineconeSimilarity.from_json()
PineconeSimilarity.from_kwargs()
PineconeSimilarity.get_fields()
PineconeSimilarity.get_run_info()
PineconeSimilarity.has_cached_run_results()
PineconeSimilarity.list_runs()
PineconeSimilarity.load_run_results()
PineconeSimilarity.load_run_view()
PineconeSimilarity.parse()
PineconeSimilarity.register_run()
PineconeSimilarity.rename()
PineconeSimilarity.run_info_cls()
PineconeSimilarity.save_run_info()
PineconeSimilarity.save_run_results()
PineconeSimilarity.update_run_config()
PineconeSimilarity.update_run_key()
PineconeSimilarity.validate()
PineconeSimilarity.validate_run()
PineconeSimilarityIndex
PineconeSimilarityIndex.index
PineconeSimilarityIndex.total_index_size
PineconeSimilarityIndex.ready
PineconeSimilarityIndex.add_to_index()
PineconeSimilarityIndex.remove_from_index()
PineconeSimilarityIndex.get_embeddings()
PineconeSimilarityIndex.cleanup()
PineconeSimilarityIndex.attributes()
PineconeSimilarityIndex.backend
PineconeSimilarityIndex.base_results_cls()
PineconeSimilarityIndex.clear_view()
PineconeSimilarityIndex.cls
PineconeSimilarityIndex.compute_embeddings()
PineconeSimilarityIndex.config
PineconeSimilarityIndex.copy()
PineconeSimilarityIndex.current_label_ids
PineconeSimilarityIndex.current_sample_ids
PineconeSimilarityIndex.custom_attributes()
PineconeSimilarityIndex.from_dict()
PineconeSimilarityIndex.from_json()
PineconeSimilarityIndex.from_str()
PineconeSimilarityIndex.get_class_name()
PineconeSimilarityIndex.get_model()
PineconeSimilarityIndex.has_view
PineconeSimilarityIndex.index_size
PineconeSimilarityIndex.is_external
PineconeSimilarityIndex.key
PineconeSimilarityIndex.label_ids
PineconeSimilarityIndex.missing_size
PineconeSimilarityIndex.reload()
PineconeSimilarityIndex.sample_ids
PineconeSimilarityIndex.samples
PineconeSimilarityIndex.save()
PineconeSimilarityIndex.save_config()
PineconeSimilarityIndex.serialize()
PineconeSimilarityIndex.sort_by_similarity()
PineconeSimilarityIndex.to_str()
PineconeSimilarityIndex.use_view()
PineconeSimilarityIndex.values()
PineconeSimilarityIndex.view
PineconeSimilarityIndex.write_json()
- fiftyone.brain.internal.core.qdrant
- fiftyone.brain.internal.core.redis
RedisSimilarityConfig
RedisSimilarityConfig.method
RedisSimilarityConfig.host
RedisSimilarityConfig.port
RedisSimilarityConfig.db
RedisSimilarityConfig.username
RedisSimilarityConfig.password
RedisSimilarityConfig.max_k
RedisSimilarityConfig.supports_least_similarity
RedisSimilarityConfig.supported_aggregations
RedisSimilarityConfig.load_credentials()
RedisSimilarityConfig.attributes()
RedisSimilarityConfig.base_config_cls()
RedisSimilarityConfig.build()
RedisSimilarityConfig.builder()
RedisSimilarityConfig.cls
RedisSimilarityConfig.copy()
RedisSimilarityConfig.custom_attributes()
RedisSimilarityConfig.default()
RedisSimilarityConfig.from_dict()
RedisSimilarityConfig.from_json()
RedisSimilarityConfig.from_kwargs()
RedisSimilarityConfig.from_str()
RedisSimilarityConfig.get_class_name()
RedisSimilarityConfig.load_default()
RedisSimilarityConfig.parse_array()
RedisSimilarityConfig.parse_bool()
RedisSimilarityConfig.parse_categorical()
RedisSimilarityConfig.parse_dict()
RedisSimilarityConfig.parse_int()
RedisSimilarityConfig.parse_mutually_exclusive_fields()
RedisSimilarityConfig.parse_number()
RedisSimilarityConfig.parse_object()
RedisSimilarityConfig.parse_object_array()
RedisSimilarityConfig.parse_object_dict()
RedisSimilarityConfig.parse_path()
RedisSimilarityConfig.parse_raw()
RedisSimilarityConfig.parse_string()
RedisSimilarityConfig.run_cls
RedisSimilarityConfig.serialize()
RedisSimilarityConfig.to_str()
RedisSimilarityConfig.type
RedisSimilarityConfig.validate_all_or_nothing_fields()
RedisSimilarityConfig.write_json()
RedisSimilarity
RedisSimilarity.ensure_requirements()
RedisSimilarity.ensure_usage_requirements()
RedisSimilarity.initialize()
RedisSimilarity.cleanup()
RedisSimilarity.delete_run()
RedisSimilarity.delete_runs()
RedisSimilarity.from_config()
RedisSimilarity.from_dict()
RedisSimilarity.from_json()
RedisSimilarity.from_kwargs()
RedisSimilarity.get_fields()
RedisSimilarity.get_run_info()
RedisSimilarity.has_cached_run_results()
RedisSimilarity.list_runs()
RedisSimilarity.load_run_results()
RedisSimilarity.load_run_view()
RedisSimilarity.parse()
RedisSimilarity.register_run()
RedisSimilarity.rename()
RedisSimilarity.run_info_cls()
RedisSimilarity.save_run_info()
RedisSimilarity.save_run_results()
RedisSimilarity.update_run_config()
RedisSimilarity.update_run_key()
RedisSimilarity.validate()
RedisSimilarity.validate_run()
RedisSimilarityIndex
RedisSimilarityIndex.client
RedisSimilarityIndex.total_index_size
RedisSimilarityIndex.add_to_index()
RedisSimilarityIndex.remove_from_index()
RedisSimilarityIndex.get_embeddings()
RedisSimilarityIndex.cleanup()
RedisSimilarityIndex.attributes()
RedisSimilarityIndex.backend
RedisSimilarityIndex.base_results_cls()
RedisSimilarityIndex.clear_view()
RedisSimilarityIndex.cls
RedisSimilarityIndex.compute_embeddings()
RedisSimilarityIndex.config
RedisSimilarityIndex.copy()
RedisSimilarityIndex.current_label_ids
RedisSimilarityIndex.current_sample_ids
RedisSimilarityIndex.custom_attributes()
RedisSimilarityIndex.from_dict()
RedisSimilarityIndex.from_json()
RedisSimilarityIndex.from_str()
RedisSimilarityIndex.get_class_name()
RedisSimilarityIndex.get_model()
RedisSimilarityIndex.has_view
RedisSimilarityIndex.index_size
RedisSimilarityIndex.is_external
RedisSimilarityIndex.key
RedisSimilarityIndex.label_ids
RedisSimilarityIndex.missing_size
RedisSimilarityIndex.reload()
RedisSimilarityIndex.sample_ids
RedisSimilarityIndex.samples
RedisSimilarityIndex.save()
RedisSimilarityIndex.save_config()
RedisSimilarityIndex.serialize()
RedisSimilarityIndex.sort_by_similarity()
RedisSimilarityIndex.to_str()
RedisSimilarityIndex.use_view()
RedisSimilarityIndex.values()
RedisSimilarityIndex.view
RedisSimilarityIndex.write_json()
- fiftyone.brain.internal.core.representativeness
compute_representativeness()
RepresentativenessConfig
RepresentativenessConfig.type
RepresentativenessConfig.method
RepresentativenessConfig.attributes()
RepresentativenessConfig.base_config_cls()
RepresentativenessConfig.build()
RepresentativenessConfig.builder()
RepresentativenessConfig.cls
RepresentativenessConfig.copy()
RepresentativenessConfig.custom_attributes()
RepresentativenessConfig.default()
RepresentativenessConfig.from_dict()
RepresentativenessConfig.from_json()
RepresentativenessConfig.from_kwargs()
RepresentativenessConfig.from_str()
RepresentativenessConfig.get_class_name()
RepresentativenessConfig.load_credentials()
RepresentativenessConfig.load_default()
RepresentativenessConfig.parse_array()
RepresentativenessConfig.parse_bool()
RepresentativenessConfig.parse_categorical()
RepresentativenessConfig.parse_dict()
RepresentativenessConfig.parse_int()
RepresentativenessConfig.parse_mutually_exclusive_fields()
RepresentativenessConfig.parse_number()
RepresentativenessConfig.parse_object()
RepresentativenessConfig.parse_object_array()
RepresentativenessConfig.parse_object_dict()
RepresentativenessConfig.parse_path()
RepresentativenessConfig.parse_raw()
RepresentativenessConfig.parse_string()
RepresentativenessConfig.run_cls
RepresentativenessConfig.serialize()
RepresentativenessConfig.to_str()
RepresentativenessConfig.validate_all_or_nothing_fields()
RepresentativenessConfig.write_json()
Representativeness
Representativeness.ensure_requirements()
Representativeness.get_fields()
Representativeness.cleanup()
Representativeness.delete_run()
Representativeness.delete_runs()
Representativeness.ensure_usage_requirements()
Representativeness.from_config()
Representativeness.from_dict()
Representativeness.from_json()
Representativeness.from_kwargs()
Representativeness.get_run_info()
Representativeness.has_cached_run_results()
Representativeness.list_runs()
Representativeness.load_run_results()
Representativeness.load_run_view()
Representativeness.parse()
Representativeness.register_run()
Representativeness.rename()
Representativeness.run_info_cls()
Representativeness.save_run_info()
Representativeness.save_run_results()
Representativeness.update_run_config()
Representativeness.update_run_key()
Representativeness.validate()
Representativeness.validate_run()
- fiftyone.brain.internal.core.sklearn
SklearnSimilarityConfig
SklearnSimilarityConfig.method
SklearnSimilarityConfig.max_k
SklearnSimilarityConfig.supports_least_similarity
SklearnSimilarityConfig.supported_aggregations
SklearnSimilarityConfig.attributes()
SklearnSimilarityConfig.base_config_cls()
SklearnSimilarityConfig.build()
SklearnSimilarityConfig.builder()
SklearnSimilarityConfig.cls
SklearnSimilarityConfig.copy()
SklearnSimilarityConfig.custom_attributes()
SklearnSimilarityConfig.default()
SklearnSimilarityConfig.from_dict()
SklearnSimilarityConfig.from_json()
SklearnSimilarityConfig.from_kwargs()
SklearnSimilarityConfig.from_str()
SklearnSimilarityConfig.get_class_name()
SklearnSimilarityConfig.load_credentials()
SklearnSimilarityConfig.load_default()
SklearnSimilarityConfig.parse_array()
SklearnSimilarityConfig.parse_bool()
SklearnSimilarityConfig.parse_categorical()
SklearnSimilarityConfig.parse_dict()
SklearnSimilarityConfig.parse_int()
SklearnSimilarityConfig.parse_mutually_exclusive_fields()
SklearnSimilarityConfig.parse_number()
SklearnSimilarityConfig.parse_object()
SklearnSimilarityConfig.parse_object_array()
SklearnSimilarityConfig.parse_object_dict()
SklearnSimilarityConfig.parse_path()
SklearnSimilarityConfig.parse_raw()
SklearnSimilarityConfig.parse_string()
SklearnSimilarityConfig.run_cls
SklearnSimilarityConfig.serialize()
SklearnSimilarityConfig.to_str()
SklearnSimilarityConfig.type
SklearnSimilarityConfig.validate_all_or_nothing_fields()
SklearnSimilarityConfig.write_json()
SklearnSimilarity
SklearnSimilarity.initialize()
SklearnSimilarity.cleanup()
SklearnSimilarity.delete_run()
SklearnSimilarity.delete_runs()
SklearnSimilarity.ensure_requirements()
SklearnSimilarity.ensure_usage_requirements()
SklearnSimilarity.from_config()
SklearnSimilarity.from_dict()
SklearnSimilarity.from_json()
SklearnSimilarity.from_kwargs()
SklearnSimilarity.get_fields()
SklearnSimilarity.get_run_info()
SklearnSimilarity.has_cached_run_results()
SklearnSimilarity.list_runs()
SklearnSimilarity.load_run_results()
SklearnSimilarity.load_run_view()
SklearnSimilarity.parse()
SklearnSimilarity.register_run()
SklearnSimilarity.rename()
SklearnSimilarity.run_info_cls()
SklearnSimilarity.save_run_info()
SklearnSimilarity.save_run_results()
SklearnSimilarity.update_run_config()
SklearnSimilarity.update_run_key()
SklearnSimilarity.validate()
SklearnSimilarity.validate_run()
SklearnSimilarityIndex
SklearnSimilarityIndex.is_external
SklearnSimilarityIndex.embeddings
SklearnSimilarityIndex.sample_ids
SklearnSimilarityIndex.label_ids
SklearnSimilarityIndex.total_index_size
SklearnSimilarityIndex.add_to_index()
SklearnSimilarityIndex.remove_from_index()
SklearnSimilarityIndex.use_view()
SklearnSimilarityIndex.get_embeddings()
SklearnSimilarityIndex.reload()
SklearnSimilarityIndex.cleanup()
SklearnSimilarityIndex.attributes()
SklearnSimilarityIndex.backend
SklearnSimilarityIndex.base_results_cls()
SklearnSimilarityIndex.clear_view()
SklearnSimilarityIndex.cls
SklearnSimilarityIndex.compute_embeddings()
SklearnSimilarityIndex.config
SklearnSimilarityIndex.copy()
SklearnSimilarityIndex.current_label_ids
SklearnSimilarityIndex.current_sample_ids
SklearnSimilarityIndex.custom_attributes()
SklearnSimilarityIndex.duplicate_ids
SklearnSimilarityIndex.duplicates_view()
SklearnSimilarityIndex.find_duplicates()
SklearnSimilarityIndex.find_unique()
SklearnSimilarityIndex.from_dict()
SklearnSimilarityIndex.from_json()
SklearnSimilarityIndex.from_str()
SklearnSimilarityIndex.get_class_name()
SklearnSimilarityIndex.get_model()
SklearnSimilarityIndex.has_view
SklearnSimilarityIndex.index_size
SklearnSimilarityIndex.key
SklearnSimilarityIndex.missing_size
SklearnSimilarityIndex.neighbors_map
SklearnSimilarityIndex.plot_distances()
SklearnSimilarityIndex.samples
SklearnSimilarityIndex.save()
SklearnSimilarityIndex.save_config()
SklearnSimilarityIndex.serialize()
SklearnSimilarityIndex.sort_by_similarity()
SklearnSimilarityIndex.thresh
SklearnSimilarityIndex.to_str()
SklearnSimilarityIndex.unique_ids
SklearnSimilarityIndex.unique_view()
SklearnSimilarityIndex.values()
SklearnSimilarityIndex.view
SklearnSimilarityIndex.visualize_duplicates()
SklearnSimilarityIndex.visualize_unique()
SklearnSimilarityIndex.write_json()
NeighborsHelper
- fiftyone.brain.internal.core.uniqueness
compute_uniqueness()
UniquenessConfig
UniquenessConfig.type
UniquenessConfig.method
UniquenessConfig.attributes()
UniquenessConfig.base_config_cls()
UniquenessConfig.build()
UniquenessConfig.builder()
UniquenessConfig.cls
UniquenessConfig.copy()
UniquenessConfig.custom_attributes()
UniquenessConfig.default()
UniquenessConfig.from_dict()
UniquenessConfig.from_json()
UniquenessConfig.from_kwargs()
UniquenessConfig.from_str()
UniquenessConfig.get_class_name()
UniquenessConfig.load_credentials()
UniquenessConfig.load_default()
UniquenessConfig.parse_array()
UniquenessConfig.parse_bool()
UniquenessConfig.parse_categorical()
UniquenessConfig.parse_dict()
UniquenessConfig.parse_int()
UniquenessConfig.parse_mutually_exclusive_fields()
UniquenessConfig.parse_number()
UniquenessConfig.parse_object()
UniquenessConfig.parse_object_array()
UniquenessConfig.parse_object_dict()
UniquenessConfig.parse_path()
UniquenessConfig.parse_raw()
UniquenessConfig.parse_string()
UniquenessConfig.run_cls
UniquenessConfig.serialize()
UniquenessConfig.to_str()
UniquenessConfig.validate_all_or_nothing_fields()
UniquenessConfig.write_json()
Uniqueness
Uniqueness.ensure_requirements()
Uniqueness.get_fields()
Uniqueness.cleanup()
Uniqueness.delete_run()
Uniqueness.delete_runs()
Uniqueness.ensure_usage_requirements()
Uniqueness.from_config()
Uniqueness.from_dict()
Uniqueness.from_json()
Uniqueness.from_kwargs()
Uniqueness.get_run_info()
Uniqueness.has_cached_run_results()
Uniqueness.list_runs()
Uniqueness.load_run_results()
Uniqueness.load_run_view()
Uniqueness.parse()
Uniqueness.register_run()
Uniqueness.rename()
Uniqueness.run_info_cls()
Uniqueness.save_run_info()
Uniqueness.save_run_results()
Uniqueness.update_run_config()
Uniqueness.update_run_key()
Uniqueness.validate()
Uniqueness.validate_run()
- fiftyone.brain.internal.core.utils
- fiftyone.brain.internal.core.visualization
- Module contents
- Module contents
- fiftyone.brain.internal.core
- fiftyone.brain.config
BrainConfig
BrainConfig.attributes()
BrainConfig.copy()
BrainConfig.custom_attributes()
BrainConfig.from_dict()
BrainConfig.from_json()
BrainConfig.from_str()
BrainConfig.get_class_name()
BrainConfig.parse_bool()
BrainConfig.parse_dict()
BrainConfig.parse_int()
BrainConfig.parse_number()
BrainConfig.parse_path()
BrainConfig.parse_path_array()
BrainConfig.parse_string()
BrainConfig.parse_string_array()
BrainConfig.serialize()
BrainConfig.to_str()
BrainConfig.write_json()
locate_brain_config()
load_brain_config()
- fiftyone.brain.similarity
compute_similarity()
SimilarityConfig
SimilarityConfig.type
SimilarityConfig.method
SimilarityConfig.max_k
SimilarityConfig.supports_least_similarity
SimilarityConfig.supported_aggregations
SimilarityConfig.load_credentials()
SimilarityConfig.attributes()
SimilarityConfig.base_config_cls()
SimilarityConfig.build()
SimilarityConfig.builder()
SimilarityConfig.cls
SimilarityConfig.copy()
SimilarityConfig.custom_attributes()
SimilarityConfig.default()
SimilarityConfig.from_dict()
SimilarityConfig.from_json()
SimilarityConfig.from_kwargs()
SimilarityConfig.from_str()
SimilarityConfig.get_class_name()
SimilarityConfig.load_default()
SimilarityConfig.parse_array()
SimilarityConfig.parse_bool()
SimilarityConfig.parse_categorical()
SimilarityConfig.parse_dict()
SimilarityConfig.parse_int()
SimilarityConfig.parse_mutually_exclusive_fields()
SimilarityConfig.parse_number()
SimilarityConfig.parse_object()
SimilarityConfig.parse_object_array()
SimilarityConfig.parse_object_dict()
SimilarityConfig.parse_path()
SimilarityConfig.parse_raw()
SimilarityConfig.parse_string()
SimilarityConfig.run_cls
SimilarityConfig.serialize()
SimilarityConfig.to_str()
SimilarityConfig.validate_all_or_nothing_fields()
SimilarityConfig.write_json()
Similarity
Similarity.initialize()
Similarity.get_fields()
Similarity.cleanup()
Similarity.delete_run()
Similarity.delete_runs()
Similarity.ensure_requirements()
Similarity.ensure_usage_requirements()
Similarity.from_config()
Similarity.from_dict()
Similarity.from_json()
Similarity.from_kwargs()
Similarity.get_run_info()
Similarity.has_cached_run_results()
Similarity.list_runs()
Similarity.load_run_results()
Similarity.load_run_view()
Similarity.parse()
Similarity.register_run()
Similarity.rename()
Similarity.run_info_cls()
Similarity.save_run_info()
Similarity.save_run_results()
Similarity.update_run_config()
Similarity.update_run_key()
Similarity.validate()
Similarity.validate_run()
SimilarityIndex
SimilarityIndex.config
SimilarityIndex.is_external
SimilarityIndex.sample_ids
SimilarityIndex.label_ids
SimilarityIndex.total_index_size
SimilarityIndex.has_view
SimilarityIndex.view
SimilarityIndex.current_sample_ids
SimilarityIndex.current_label_ids
SimilarityIndex.index_size
SimilarityIndex.missing_size
SimilarityIndex.add_to_index()
SimilarityIndex.remove_from_index()
SimilarityIndex.get_embeddings()
SimilarityIndex.use_view()
SimilarityIndex.clear_view()
SimilarityIndex.reload()
SimilarityIndex.cleanup()
SimilarityIndex.values()
SimilarityIndex.sort_by_similarity()
SimilarityIndex.get_model()
SimilarityIndex.compute_embeddings()
SimilarityIndex.attributes()
SimilarityIndex.backend
SimilarityIndex.base_results_cls()
SimilarityIndex.cls
SimilarityIndex.copy()
SimilarityIndex.custom_attributes()
SimilarityIndex.from_dict()
SimilarityIndex.from_json()
SimilarityIndex.from_str()
SimilarityIndex.get_class_name()
SimilarityIndex.key
SimilarityIndex.samples
SimilarityIndex.save()
SimilarityIndex.save_config()
SimilarityIndex.serialize()
SimilarityIndex.to_str()
SimilarityIndex.write_json()
DuplicatesMixin
DuplicatesMixin.thresh
DuplicatesMixin.unique_ids
DuplicatesMixin.duplicate_ids
DuplicatesMixin.neighbors_map
DuplicatesMixin.find_duplicates()
DuplicatesMixin.find_unique()
DuplicatesMixin.plot_distances()
DuplicatesMixin.duplicates_view()
DuplicatesMixin.unique_view()
DuplicatesMixin.visualize_duplicates()
DuplicatesMixin.visualize_unique()
- fiftyone.brain.visualization
compute_visualization()
values()
visualize()
VisualizationResults
VisualizationResults.config
VisualizationResults.index_size
VisualizationResults.total_index_size
VisualizationResults.missing_size
VisualizationResults.current_points
VisualizationResults.current_sample_ids
VisualizationResults.current_label_ids
VisualizationResults.view
VisualizationResults.has_spatial_index
VisualizationResults.use_view()
VisualizationResults.clear_view()
VisualizationResults.values()
VisualizationResults.visualize()
VisualizationResults.index_points()
VisualizationResults.remove_index()
VisualizationResults.attributes()
VisualizationResults.backend
VisualizationResults.base_results_cls()
VisualizationResults.cls
VisualizationResults.copy()
VisualizationResults.custom_attributes()
VisualizationResults.from_dict()
VisualizationResults.from_json()
VisualizationResults.from_str()
VisualizationResults.get_class_name()
VisualizationResults.key
VisualizationResults.samples
VisualizationResults.save()
VisualizationResults.save_config()
VisualizationResults.serialize()
VisualizationResults.to_str()
VisualizationResults.write_json()
VisualizationConfig
VisualizationConfig.type
VisualizationConfig.attributes()
VisualizationConfig.base_config_cls()
VisualizationConfig.build()
VisualizationConfig.builder()
VisualizationConfig.cls
VisualizationConfig.copy()
VisualizationConfig.custom_attributes()
VisualizationConfig.default()
VisualizationConfig.from_dict()
VisualizationConfig.from_json()
VisualizationConfig.from_kwargs()
VisualizationConfig.from_str()
VisualizationConfig.get_class_name()
VisualizationConfig.load_credentials()
VisualizationConfig.load_default()
VisualizationConfig.method
VisualizationConfig.parse_array()
VisualizationConfig.parse_bool()
VisualizationConfig.parse_categorical()
VisualizationConfig.parse_dict()
VisualizationConfig.parse_int()
VisualizationConfig.parse_mutually_exclusive_fields()
VisualizationConfig.parse_number()
VisualizationConfig.parse_object()
VisualizationConfig.parse_object_array()
VisualizationConfig.parse_object_dict()
VisualizationConfig.parse_path()
VisualizationConfig.parse_raw()
VisualizationConfig.parse_string()
VisualizationConfig.run_cls
VisualizationConfig.serialize()
VisualizationConfig.to_str()
VisualizationConfig.validate_all_or_nothing_fields()
VisualizationConfig.write_json()
Visualization
Visualization.fit()
Visualization.get_fields()
Visualization.rename()
Visualization.cleanup()
Visualization.delete_run()
Visualization.delete_runs()
Visualization.ensure_requirements()
Visualization.ensure_usage_requirements()
Visualization.from_config()
Visualization.from_dict()
Visualization.from_json()
Visualization.from_kwargs()
Visualization.get_run_info()
Visualization.has_cached_run_results()
Visualization.list_runs()
Visualization.load_run_results()
Visualization.load_run_view()
Visualization.parse()
Visualization.register_run()
Visualization.run_info_cls()
Visualization.save_run_info()
Visualization.save_run_results()
Visualization.update_run_config()
Visualization.update_run_key()
Visualization.validate()
Visualization.validate_run()
UMAPVisualizationConfig
UMAPVisualizationConfig.method
UMAPVisualizationConfig.attributes()
UMAPVisualizationConfig.base_config_cls()
UMAPVisualizationConfig.build()
UMAPVisualizationConfig.builder()
UMAPVisualizationConfig.cls
UMAPVisualizationConfig.copy()
UMAPVisualizationConfig.custom_attributes()
UMAPVisualizationConfig.default()
UMAPVisualizationConfig.from_dict()
UMAPVisualizationConfig.from_json()
UMAPVisualizationConfig.from_kwargs()
UMAPVisualizationConfig.from_str()
UMAPVisualizationConfig.get_class_name()
UMAPVisualizationConfig.load_credentials()
UMAPVisualizationConfig.load_default()
UMAPVisualizationConfig.parse_array()
UMAPVisualizationConfig.parse_bool()
UMAPVisualizationConfig.parse_categorical()
UMAPVisualizationConfig.parse_dict()
UMAPVisualizationConfig.parse_int()
UMAPVisualizationConfig.parse_mutually_exclusive_fields()
UMAPVisualizationConfig.parse_number()
UMAPVisualizationConfig.parse_object()
UMAPVisualizationConfig.parse_object_array()
UMAPVisualizationConfig.parse_object_dict()
UMAPVisualizationConfig.parse_path()
UMAPVisualizationConfig.parse_raw()
UMAPVisualizationConfig.parse_string()
UMAPVisualizationConfig.run_cls
UMAPVisualizationConfig.serialize()
UMAPVisualizationConfig.to_str()
UMAPVisualizationConfig.type
UMAPVisualizationConfig.validate_all_or_nothing_fields()
UMAPVisualizationConfig.write_json()
UMAPVisualization
UMAPVisualization.ensure_requirements()
UMAPVisualization.fit()
UMAPVisualization.cleanup()
UMAPVisualization.delete_run()
UMAPVisualization.delete_runs()
UMAPVisualization.ensure_usage_requirements()
UMAPVisualization.from_config()
UMAPVisualization.from_dict()
UMAPVisualization.from_json()
UMAPVisualization.from_kwargs()
UMAPVisualization.get_fields()
UMAPVisualization.get_run_info()
UMAPVisualization.has_cached_run_results()
UMAPVisualization.list_runs()
UMAPVisualization.load_run_results()
UMAPVisualization.load_run_view()
UMAPVisualization.parse()
UMAPVisualization.register_run()
UMAPVisualization.rename()
UMAPVisualization.run_info_cls()
UMAPVisualization.save_run_info()
UMAPVisualization.save_run_results()
UMAPVisualization.update_run_config()
UMAPVisualization.update_run_key()
UMAPVisualization.validate()
UMAPVisualization.validate_run()
TSNEVisualizationConfig
TSNEVisualizationConfig.method
TSNEVisualizationConfig.attributes()
TSNEVisualizationConfig.base_config_cls()
TSNEVisualizationConfig.build()
TSNEVisualizationConfig.builder()
TSNEVisualizationConfig.cls
TSNEVisualizationConfig.copy()
TSNEVisualizationConfig.custom_attributes()
TSNEVisualizationConfig.default()
TSNEVisualizationConfig.from_dict()
TSNEVisualizationConfig.from_json()
TSNEVisualizationConfig.from_kwargs()
TSNEVisualizationConfig.from_str()
TSNEVisualizationConfig.get_class_name()
TSNEVisualizationConfig.load_credentials()
TSNEVisualizationConfig.load_default()
TSNEVisualizationConfig.parse_array()
TSNEVisualizationConfig.parse_bool()
TSNEVisualizationConfig.parse_categorical()
TSNEVisualizationConfig.parse_dict()
TSNEVisualizationConfig.parse_int()
TSNEVisualizationConfig.parse_mutually_exclusive_fields()
TSNEVisualizationConfig.parse_number()
TSNEVisualizationConfig.parse_object()
TSNEVisualizationConfig.parse_object_array()
TSNEVisualizationConfig.parse_object_dict()
TSNEVisualizationConfig.parse_path()
TSNEVisualizationConfig.parse_raw()
TSNEVisualizationConfig.parse_string()
TSNEVisualizationConfig.run_cls
TSNEVisualizationConfig.serialize()
TSNEVisualizationConfig.to_str()
TSNEVisualizationConfig.type
TSNEVisualizationConfig.validate_all_or_nothing_fields()
TSNEVisualizationConfig.write_json()
TSNEVisualization
TSNEVisualization.fit()
TSNEVisualization.cleanup()
TSNEVisualization.delete_run()
TSNEVisualization.delete_runs()
TSNEVisualization.ensure_requirements()
TSNEVisualization.ensure_usage_requirements()
TSNEVisualization.from_config()
TSNEVisualization.from_dict()
TSNEVisualization.from_json()
TSNEVisualization.from_kwargs()
TSNEVisualization.get_fields()
TSNEVisualization.get_run_info()
TSNEVisualization.has_cached_run_results()
TSNEVisualization.list_runs()
TSNEVisualization.load_run_results()
TSNEVisualization.load_run_view()
TSNEVisualization.parse()
TSNEVisualization.register_run()
TSNEVisualization.rename()
TSNEVisualization.run_info_cls()
TSNEVisualization.save_run_info()
TSNEVisualization.save_run_results()
TSNEVisualization.update_run_config()
TSNEVisualization.update_run_key()
TSNEVisualization.validate()
TSNEVisualization.validate_run()
PCAVisualizationConfig
PCAVisualizationConfig.method
PCAVisualizationConfig.attributes()
PCAVisualizationConfig.base_config_cls()
PCAVisualizationConfig.build()
PCAVisualizationConfig.builder()
PCAVisualizationConfig.cls
PCAVisualizationConfig.copy()
PCAVisualizationConfig.custom_attributes()
PCAVisualizationConfig.default()
PCAVisualizationConfig.from_dict()
PCAVisualizationConfig.from_json()
PCAVisualizationConfig.from_kwargs()
PCAVisualizationConfig.from_str()
PCAVisualizationConfig.get_class_name()
PCAVisualizationConfig.load_credentials()
PCAVisualizationConfig.load_default()
PCAVisualizationConfig.parse_array()
PCAVisualizationConfig.parse_bool()
PCAVisualizationConfig.parse_categorical()
PCAVisualizationConfig.parse_dict()
PCAVisualizationConfig.parse_int()
PCAVisualizationConfig.parse_mutually_exclusive_fields()
PCAVisualizationConfig.parse_number()
PCAVisualizationConfig.parse_object()
PCAVisualizationConfig.parse_object_array()
PCAVisualizationConfig.parse_object_dict()
PCAVisualizationConfig.parse_path()
PCAVisualizationConfig.parse_raw()
PCAVisualizationConfig.parse_string()
PCAVisualizationConfig.run_cls
PCAVisualizationConfig.serialize()
PCAVisualizationConfig.to_str()
PCAVisualizationConfig.type
PCAVisualizationConfig.validate_all_or_nothing_fields()
PCAVisualizationConfig.write_json()
PCAVisualization
PCAVisualization.fit()
PCAVisualization.cleanup()
PCAVisualization.delete_run()
PCAVisualization.delete_runs()
PCAVisualization.ensure_requirements()
PCAVisualization.ensure_usage_requirements()
PCAVisualization.from_config()
PCAVisualization.from_dict()
PCAVisualization.from_json()
PCAVisualization.from_kwargs()
PCAVisualization.get_fields()
PCAVisualization.get_run_info()
PCAVisualization.has_cached_run_results()
PCAVisualization.list_runs()
PCAVisualization.load_run_results()
PCAVisualization.load_run_view()
PCAVisualization.parse()
PCAVisualization.register_run()
PCAVisualization.rename()
PCAVisualization.run_info_cls()
PCAVisualization.save_run_info()
PCAVisualization.save_run_results()
PCAVisualization.update_run_config()
PCAVisualization.update_run_key()
PCAVisualization.validate()
PCAVisualization.validate_run()
ManualVisualizationConfig
ManualVisualizationConfig.method
ManualVisualizationConfig.attributes()
ManualVisualizationConfig.base_config_cls()
ManualVisualizationConfig.build()
ManualVisualizationConfig.builder()
ManualVisualizationConfig.cls
ManualVisualizationConfig.copy()
ManualVisualizationConfig.custom_attributes()
ManualVisualizationConfig.default()
ManualVisualizationConfig.from_dict()
ManualVisualizationConfig.from_json()
ManualVisualizationConfig.from_kwargs()
ManualVisualizationConfig.from_str()
ManualVisualizationConfig.get_class_name()
ManualVisualizationConfig.load_credentials()
ManualVisualizationConfig.load_default()
ManualVisualizationConfig.parse_array()
ManualVisualizationConfig.parse_bool()
ManualVisualizationConfig.parse_categorical()
ManualVisualizationConfig.parse_dict()
ManualVisualizationConfig.parse_int()
ManualVisualizationConfig.parse_mutually_exclusive_fields()
ManualVisualizationConfig.parse_number()
ManualVisualizationConfig.parse_object()
ManualVisualizationConfig.parse_object_array()
ManualVisualizationConfig.parse_object_dict()
ManualVisualizationConfig.parse_path()
ManualVisualizationConfig.parse_raw()
ManualVisualizationConfig.parse_string()
ManualVisualizationConfig.run_cls
ManualVisualizationConfig.serialize()
ManualVisualizationConfig.to_str()
ManualVisualizationConfig.type
ManualVisualizationConfig.validate_all_or_nothing_fields()
ManualVisualizationConfig.write_json()
ManualVisualization
ManualVisualization.fit()
ManualVisualization.cleanup()
ManualVisualization.delete_run()
ManualVisualization.delete_runs()
ManualVisualization.ensure_requirements()
ManualVisualization.ensure_usage_requirements()
ManualVisualization.from_config()
ManualVisualization.from_dict()
ManualVisualization.from_json()
ManualVisualization.from_kwargs()
ManualVisualization.get_fields()
ManualVisualization.get_run_info()
ManualVisualization.has_cached_run_results()
ManualVisualization.list_runs()
ManualVisualization.load_run_results()
ManualVisualization.load_run_view()
ManualVisualization.parse()
ManualVisualization.register_run()
ManualVisualization.rename()
ManualVisualization.run_info_cls()
ManualVisualization.save_run_info()
ManualVisualization.save_run_results()
ManualVisualization.update_run_config()
ManualVisualization.update_run_key()
ManualVisualization.validate()
ManualVisualization.validate_run()
Module contents#
The brains behind FiftyOne: a powerful package for dataset curation, analysis, and visualization.
See voxel51/fiftyone for more information.
Functions:
|
Adds a hardness field to each sample scoring the difficulty that the specified label field observed in classifying the sample. |
|
Computes the mistakenness (likelihood of being incorrect) of the labels in |
|
Adds a uniqueness field to each sample scoring how unique it is with respect to the rest of the samples. |
|
Adds a representativeness field to each sample scoring how representative of nearby samples it is. |
|
Computes a low-dimensional representation of the samples' media or their patches that can be interactively visualized. |
|
Uses embeddings to index the samples or their patches so that you can query/sort by similarity. |
|
Detects potential duplicates in the given sample collection. |
|
Detects duplicate media in a sample collection. |
|
Computes potential leaks between splits of the given sample collection. |
- fiftyone.brain.compute_hardness(samples, label_field, hardness_field='hardness', progress=None)#
Adds a hardness field to each sample scoring the difficulty that the specified label field observed in classifying the sample.
Hardness is a measure computed based on model prediction output (through logits) that summarizes a measure of the uncertainty the model had with the sample. This makes hardness quantitative and can be used to detect things like hard samples, annotation errors during noisy training, and more.
All classifications must have their
logits
attributes populated in order to use this method.Note
Runs of this method can be referenced later via brain key
hardness_field
.- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
label_field β the
fiftyone.core.labels.Classification
orfiftyone.core.labels.Classifications
field to use from each samplehardness_field ("hardness") β the field name to use to store the hardness value for each sample
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead
- fiftyone.brain.compute_mistakenness(samples, pred_field, label_field, mistakenness_field='mistakenness', missing_field='possible_missing', spurious_field='possible_spurious', use_logits=False, copy_missing=False, progress=None)#
Computes the mistakenness (likelihood of being incorrect) of the labels in
label_field
based on the predcted labels inpred_field
.Mistakenness is measured based on either the
confidence
orlogits
of the predictions inpred_field
. This measure can be used to detect things like annotation errors and unusually hard samples.For classifications, a
mistakenness_field
field is populated on each sample that quantifies the likelihood that the label in thelabel_field
of that sample is incorrect.For objects (detections, polylines, keypoints, etc), the mistakenness of each object in
label_field
is computed, usingfiftyone.core.collections.SampleCollection.evaluate_detections()
to locate corresponding objects inpred_field
. Three types of mistakes are identified:(Mistakes) Objects in
label_field
with a match inpred_field
are assigned a mistakenness value in theirmistakenness_field
that captures the likelihood that the class label of the object inlabel_field
is a mistake. Amistakenness_field + "_loc"
field is also populated that captures the likelihood that the object inlabel_field
is a mistake due to its localization (bounding box).(Missing) Objects in
pred_field
with no matches inlabel_field
but which are likely to be correct will have theirmissing_field
attribute set to True. In addition, ifcopy_missing
is True, copies of these objects are added to the ground truthlabel_field
.(Spurious) Objects in
label_field
with no matches inpred_field
but which are likely to be incorrect will have theirspurious_field
attribute set to True.
In addition, for objects, the following sample-level fields are populated:
(Mistakes) The
mistakenness_field
of each sample is populated with the maximum mistakenness of the objects inlabel_field
(Missing) The
missing_field
of each sample is populated with the number of missing objects that were deemed missing fromlabel_field
.(Spurious) The
spurious_field
of each sample is populated with the number of objects inlabel_field
that were given deemed spurious.
Note
Runs of this method can be referenced later via brain key
mistakenness_field
.- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
pred_field β the name of the predicted label field to use from each sample. Can be of type
fiftyone.core.labels.Classification
,fiftyone.core.labels.Classifications
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polylines
,fiftyone.core.labels.Keypoints
, orfiftyone.core.labels.TemporalDetections
label_field β the name of the βground truthβ label field that you want to test for mistakes with respect to the predictions in
pred_field
. Must have the same type aspred_field
mistakenness_field ("mistakenness") β the field name to use to store the mistakenness value for each sample
missing_field ("possible_missing) β the field in which to store per-sample counts of potential missing objects
spurious_field ("possible_spurious) β the field in which to store per-sample counts of potential spurious objects
use_logits (False) β whether to use logits (True) or confidence (False) to compute mistakenness. Logits typically yield better results, when they are available
copy_missing (False) β whether to copy predicted objects that were deemed to be missing into
label_field
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead
- fiftyone.brain.compute_uniqueness(samples, uniqueness_field='uniqueness', roi_field=None, embeddings=None, similarity_index=None, model=None, model_kwargs=None, force_square=False, alpha=None, batch_size=None, num_workers=None, skip_failures=True, progress=None)#
Adds a uniqueness field to each sample scoring how unique it is with respect to the rest of the samples.
This function only uses the pixel data and can therefore process labeled or unlabeled samples.
If no
embeddings
,similarity_index
, ormodel
is provided, a default model is used to generate embeddings.Note
Runs of this method can be referenced later via brain key
uniqueness_field
.- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
uniqueness_field ("uniqueness") β the field name to use to store the uniqueness value for each sample
roi_field (None) β an optional
fiftyone.core.labels.Detection
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polyline
, orfiftyone.core.labels.Polylines
field defining a region of interest within each image to use to compute uniquenessembeddings (None) β
if no
model
is provided, this argument specifies pre-computed embeddings to use, which can be any of the following:a
num_samples x num_dims
array of embeddingsif
roi_field
is specified, a dict mapping sample IDs tonum_patches x num_dims
arrays of patch embeddingsthe name of a dataset field containing the embeddings to use
If a
model
is provided, this argument specifies the name of a field in which to store the computed embeddings. In either case, when working with patch embeddings, you can provide either the fully-qualified path to the patch embeddings or just the name of the label attribute inroi_field
similarity_index (None) β a
fiftyone.brain.similarity.SimilarityIndex
or the brain key of a similarity index to use to load pre-computed embeddingsmodel (None) β a
fiftyone.core.models.Model
or the name of a model from the FiftyOne Model Zoo to use to generate embeddings. The model must expose embeddings (model.has_embeddings = True
)model_kwargs (None) β a dictionary of optional keyword arguments to pass to the modelβs
Config
when a model name is providedforce_square (False) β whether to minimally manipulate the patch bounding boxes into squares prior to extraction. Only applicable when a
model
androi_field
are specifiedalpha (None) β an optional expansion/contraction to apply to the patches before extracting them, in
[-1, inf)
. If provided, the length and width of the box are expanded (or contracted, whenalpha < 0
) by(100 * alpha)%
. For example, setalpha = 0.1
to expand the boxes by 10%, and setalpha = -0.1
to contract the boxes by 10%. Only applicable when amodel
androi_field
are specifiedbatch_size (None) β a batch size to use when computing embeddings. Only applicable when a
model
is providednum_workers (None) β the number of workers to use when loading images. Only applicable when a Torch-based model is being used to compute embeddings
skip_failures (True) β whether to gracefully continue without raising an error if embeddings cannot be generated for a sample
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead
- fiftyone.brain.compute_representativeness(samples, representativeness_field='representativeness', method='cluster-center', roi_field=None, embeddings=None, similarity_index=None, model=None, model_kwargs=None, force_square=False, alpha=None, batch_size=None, num_workers=None, skip_failures=True, progress=None)#
Adds a representativeness field to each sample scoring how representative of nearby samples it is.
This function only uses the pixel data and can therefore process labeled or unlabeled samples.
If no
embeddings
,similarity_index
, ormodel
is provided, a default model is used to generate embeddings.Note
Runs of this method can be referenced later via brain key
representativeness_field
.- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
representativeness_field ("representativeness") β the field name to use to store the representativeness value for each sample
method ("cluster-center") β the name of the method to use to compute the representativeness. The supported values are
["cluster-center", 'cluster-center-downweight']
."cluster-center"` will make a sample's representativeness proportional to it's proximity to cluster centers, while ``"cluster-center-downweight"
will ensure more diversity in representative samplesroi_field (None) β an optional
fiftyone.core.labels.Detection
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polyline
, orfiftyone.core.labels.Polylines
field defining a region of interest within each image to use to compute representativenessembeddings (None) β
if no
model
is provided, this argument specifies pre-computed embeddings to use, which can be any of the following:a
num_samples x num_dims
array of embeddingsif
roi_field
is specified, a dict mapping sample IDs tonum_patches x num_dims
arrays of patch embeddingsthe name of a dataset field containing the embeddings to use
If a
model
is provided, this argument specifies the name of a field in which to store the computed embeddings. In either case, when working with patch embeddings, you can provide either the fully-qualified path to the patch embeddings or just the name of the label attribute inroi_field
similarity_index (None) β a
fiftyone.brain.similarity.SimilarityIndex
or the brain key of a similarity index to use to load pre-computed embeddingsmodel (None) β
a
fiftyone.core.models.Model
or the name of a model from the FiftyOne Model Zoo to use to generate embeddings. The model must expose embeddings (model.has_embeddings = True
)model_kwargs (None) β a dictionary of optional keyword arguments to pass to the modelβs
Config
when a model name is providedforce_square (False) β whether to minimally manipulate the patch bounding boxes into squares prior to extraction. Only applicable when a
model
androi_field
are specifiedalpha (None) β an optional expansion/contraction to apply to the patches before extracting them, in
[-1, inf)
. If provided, the length and width of the box are expanded (or contracted, whenalpha < 0
) by(100 * alpha)%
. For example, setalpha = 0.1
to expand the boxes by 10%, and setalpha = -0.1
to contract the boxes by 10%. Only applicable when amodel
androi_field
are specifiedbatch_size (None) β a batch size to use when computing embeddings. Only applicable when a
model
is providednum_workers (None) β the number of workers to use when loading images. Only applicable when a Torch-based model is being used to compute embeddings
skip_failures (True) β whether to gracefully continue without raising an error if embeddings cannot be generated for a sample
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead
- fiftyone.brain.compute_visualization(samples, patches_field=None, embeddings=None, points=None, create_index=False, points_field=None, brain_key=None, num_dims=2, method=None, similarity_index=None, model=None, model_kwargs=None, force_square=False, alpha=None, batch_size=None, num_workers=None, skip_failures=True, progress=None, **kwargs)#
Computes a low-dimensional representation of the samplesβ media or their patches that can be interactively visualized.
The representation can be visualized by calling the
visualize()
method of the returnedfiftyone.brain.visualization.VisualizationResults
object.If no
embeddings
,similarity_index
, ormodel
is provided, a default model is used to generate embeddings.You can use the
method
parameter to select the dimensionality reduction method to use, and you can optionally customize the method by passing additional parameters for the methodβsfiftyone.brain.visualization.VisualizationConfig
class askwargs
.The builtin
method
values and their associated config classes are:"umap"
:fiftyone.brain.visualization.UMAPVisualizationConfig
"tsne"
:fiftyone.brain.visualization.TSNEVisualizationConfig
"manual"
:fiftyone.brain.visualization.ManualVisualizationConfig
You can pass
create_index=True
to create a spatial index of the computed points on your datasetβs samples. This is highly recommended for large datasets as it enables efficient querying when lassoing points in embeddings plots. By default, spatial indexes are created in a field with namepoints_field=brain_key
, but you can customize this by manually providing apoints_field
.You can also provide a
points_field
withcreate_index=False
to store the points on your dataset without explicitly creating a database index. This will allow lasso callbacks to leverage point data rather than relying on ID selection, but without the added benefit of a database index to further optimize performance.- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
patches_field (None) β a sample field defining the image patches in each sample that have been/will be embedded. Must be of type
fiftyone.core.labels.Detection
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polyline
, orfiftyone.core.labels.Polylines
embeddings (None) β
if no
model
is provided, this argument specifies pre-computed embeddings to use, which can be any of the following:a dict mapping sample IDs to embedding vectors
a
num_samples x num_embedding_dims
array of embeddings corresponding to the samples insamples
if
patches_field
is specified, a dict mapping label IDs to to embedding vectorsif
patches_field
is specified, a dict mapping sample IDs tonum_patches x num_embedding_dims
arrays of patch embeddingsthe name of a dataset field containing the embeddings to use
If a
model
is provided, this argument specifies the name of a field in which to store the computed embeddings. In either case, when working with patch embeddings, you can provide either the fully-qualified path to the patch embeddings or just the name of the label attribute inpatches_field
points (None) β
a pre-computed low-dimensional representation to use. If provided, no embeddings will be used/computed. Can be any of the following:
a dict mapping sample IDs to points vectors
a
num_samples x num_dims
array of points corresponding to the samples insamples
if
patches_field
is specified, a dict mapping label IDs to points vectorsif
patches_field
is specified, anum_patches x num_dims
array of points whose rows correspond to the flattened list of patches whose IDs are shown below:# The list of patch IDs that the rows of `points` must match _, id_field = samples._get_label_field_path(patches_field, "id") patch_ids = samples.values(id_field, unwind=True)
create_index (False) β whether to create a spatial index for the computed points on your dataset
points_field (None) β an optional field name in which to store the spatial index. When
create_index=True
, this defaults topoints_field=brain_key
. When working with patches, you can provide either the fully-qualified path to the points field or just the name of the label attribute inpatches_field
brain_key (None) β a brain key under which to store the results of this method
num_dims (2) β the dimension of the visualization space
method (None) β the dimensionality reduction method to use. The supported values are
fiftyone.brain.brain_config.visualization_methods.keys()
and the default isfiftyone.brain.brain_config.default_visualization_method
similarity_index (None) β a
fiftyone.brain.similarity.SimilarityIndex
or the brain key of a similarity index to use to load pre-computed embeddingsmodel (None) β
a
fiftyone.core.models.Model
or the name of a model from the FiftyOne Model Zoo to use to generate embeddings. The model must expose embeddings (model.has_embeddings = True
)model_kwargs (None) β a dictionary of optional keyword arguments to pass to the modelβs
Config
when a model name is providedforce_square (False) β whether to minimally manipulate the patch bounding boxes into squares prior to extraction. Only applicable when a
model
andpatches_field
are specifiedalpha (None) β an optional expansion/contraction to apply to the patches before extracting them, in
[-1, inf)
. If provided, the length and width of the box are expanded (or contracted, whenalpha < 0
) by(100 * alpha)%
. For example, setalpha = 0.1
to expand the boxes by 10%, and setalpha = -0.1
to contract the boxes by 10%. Only applicable when amodel
andpatches_field
are specifiedbatch_size (None) β an optional batch size to use when computing embeddings. Only applicable when a
model
is providednum_workers (None) β the number of workers to use when loading images. Only applicable when a Torch-based model is being used to compute embeddings
skip_failures (True) β whether to gracefully continue without raising an error if embeddings cannot be generated for a sample
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead**kwargs β optional keyword arguments for the constructor of the
fiftyone.brain.visualization.VisualizationConfig
being used
- Returns:
- fiftyone.brain.compute_similarity(samples, patches_field=None, roi_field=None, embeddings=None, brain_key=None, model=None, model_kwargs=None, force_square=False, alpha=None, batch_size=None, num_workers=None, skip_failures=True, progress=None, backend=None, **kwargs)#
Uses embeddings to index the samples or their patches so that you can query/sort by similarity.
Calling this method only creates the index. You can then call the methods exposed on the retuned
fiftyone.brain.similarity.SimilarityIndex
object to perform the following operations:sort_by_similarity()
: Sort the samples in the collection by similarity to a specific example or example(s)
All indexes support querying by image similarity by passing sample IDs to
sort_by_similarity()
. In addition, if you pass the name of a model from the FiftyOne Model Zoo likemodel="clip-vit-base32-torch"
that can embed prompts to this method, then you can query the index by text similarity as well.In addition, if the backend supports it, you can call the following duplicate detection methods:
find_duplicates()
: Query the index to find all examples with near-duplicates in the collectionfind_unique()
: Query the index to select a subset of examples of a specified size that are maximally unique with respect to each other
If no
embeddings
ormodel
is provided, a default model is used to generate embeddings.- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
patches_field (None) β a sample field defining the image patches in each sample that have been/will be embedded. Must be of type
fiftyone.core.labels.Detection
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polyline
, orfiftyone.core.labels.Polylines
roi_field (None) β an optional
fiftyone.core.labels.Detection
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polyline
, orfiftyone.core.labels.Polylines
field defining a region of interest within each image to use to compute embeddingsembeddings (None) β
embeddings to feed the index. This argumentβs behavior depends on whether a
model
is provided, as described below.If no
model
is provided, this argument specifies pre-computed embeddings to use:a
num_samples x num_dims
array of embeddingsif
patches_field
/roi_field
is specified, a dict mapping sample IDs tonum_patches x num_dims
arrays of patch embeddingsthe name of a dataset field from which to load embeddings
None
: use the default model to compute embeddingsFalse
: do not compute embeddings right now
If a
model
is provided, this argument specifies where to store the modelβs embeddings:the name of a field in which to store the computed embeddings
False
: do not compute embeddings right now
In either case, when working with patch embeddings, you can provide either the fully-qualified path to the patch embeddings or just the name of the label attribute in
patches_field
/roi_field
brain_key (None) β a brain key under which to store the results of this method
model (None) β
a
fiftyone.core.models.Model
or the name of a model from the FiftyOne Model Zoo to use, or that was already used, to generate embeddings. The model must expose embeddings (model.has_embeddings = True
)model_kwargs (None) β a dictionary of optional keyword arguments to pass to the modelβs
Config
when a model name is providedforce_square (False) β whether to minimally manipulate the patch bounding boxes into squares prior to extraction. Only applicable when a
model
andpatches_field
/roi_field
are specifiedalpha (None) β an optional expansion/contraction to apply to the patches before extracting them, in
[-1, inf)
. If provided, the length and width of the box are expanded (or contracted, whenalpha < 0
) by(100 * alpha)%
. For example, setalpha = 0.1
to expand the boxes by 10%, and setalpha = -0.1
to contract the boxes by 10%. Only applicable when amodel
andpatches_field
/roi_field
are specifiedbatch_size (None) β an optional batch size to use when computing embeddings. Only applicable when a
model
is providednum_workers (None) β the number of workers to use when loading images. Only applicable when a Torch-based model is being used to compute embeddings
skip_failures (True) β whether to gracefully continue without raising an error if embeddings cannot be generated for a sample
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke insteadbackend (None) β the similarity backend to use. The supported values are
fiftyone.brain.brain_config.similarity_backends.keys()
and the default isfiftyone.brain.brain_config.default_similarity_backend
**kwargs β keyword arguments for the
fiftyone.brian.SimilarityConfig
subclass of the backend being used
- Returns:
- fiftyone.brain.compute_near_duplicates(samples, threshold=0.2, roi_field=None, embeddings=None, similarity_index=None, model=None, model_kwargs=None, force_square=False, alpha=None, batch_size=None, num_workers=None, skip_failures=True, progress=None)#
Detects potential duplicates in the given sample collection.
Calling this method only initializes the index. You can then call the methods exposed on the returned object to perform the following operations:
duplicate_ids
: A list of duplicate IDsneighbors_map
: A dictionary mapping IDs to lists of(dup_id, dist)
tuplesduplicates_view()
: Returns a view of all duplicates in the input collection
- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
threshold (0.2) β the similarity distance threshold to use when detecting duplicates. Values in
[0.1, 0.25]
work well for the default setuproi_field (None) β an optional
fiftyone.core.labels.Detection
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polyline
, orfiftyone.core.labels.Polylines
field defining a region of interest within each image to use to compute embeddingsembeddings (None) β
if no
model
is provided, this argument specifies pre-computed embeddings to use, which can be any of the following:a
num_samples x num_dims
array of embeddingsif
roi_field
is specified, a dict mapping sample IDs tonum_patches x num_dims
arrays of patch embeddingsthe name of a dataset field containing the embeddings to use
If a
model
is provided, this argument specifies the name of a field in which to store the computed embeddings. In either case, when working with patch embeddings, you can provide either the fully-qualified path to the patch embeddings or just the name of the label attribute inroi_field
similarity_index (None) β a
fiftyone.brain.similarity.SimilarityIndex
or the brain key of a similarity index to use to load pre-computed embeddingsmodel (None) β
a
fiftyone.core.models.Model
or the name of a model from the FiftyOne Model Zoo to use to generate embeddings. The model must expose embeddings (model.has_embeddings = True
)model_kwargs (None) β a dictionary of optional keyword arguments to pass to the modelβs
Config
when a model name is providedforce_square (False) β whether to minimally manipulate the patch bounding boxes into squares prior to extraction. Only applicable when a
model
androi_field
are specifiedalpha (None) β an optional expansion/contraction to apply to the patches before extracting them, in
[-1, inf)
. If provided, the length and width of the box are expanded (or contracted, whenalpha < 0
) by(100 * alpha)%
. For example, setalpha = 0.1
to expand the boxes by 10%, and setalpha = -0.1
to contract the boxes by 10%. Only applicable when amodel
androi_field
are specifiedbatch_size (None) β a batch size to use when computing embeddings. Only applicable when a
model
is providednum_workers (None) β the number of workers to use when loading images. Only applicable when a Torch-based model is being used to compute embeddings
skip_failures (True) β whether to gracefully continue without raising an error if embeddings cannot be generated for a sample
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead
- Returns:
- fiftyone.brain.compute_exact_duplicates(samples, num_workers=None, skip_failures=True, progress=None)#
Detects duplicate media in a sample collection.
This method detects exact duplicates with the same filehash. Use
compute_near_duplicates()
to detect near-duplicates.If duplicates are found, the first instance in
samples
will be the key in the returned dictionary, while the subsequent duplicates will be the values in the corresponding list.- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
num_workers (None) β an optional number of processes to use
skip_failures (True) β whether to gracefully ignore samples whose filehash cannot be computed
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead
- Returns:
a dictionary mapping IDs of samples with exact duplicates to lists of IDs of the duplicates for the corresponding sample
- fiftyone.brain.compute_leaky_splits(samples, splits, threshold=0.2, roi_field=None, embeddings=None, similarity_index=None, model=None, model_kwargs=None, force_square=False, alpha=None, batch_size=None, num_workers=None, skip_failures=True, progress=None)#
Computes potential leaks between splits of the given sample collection.
Calling this method only initializes the index. You can then call the methods exposed on the returned object to perform the following operations:
leaks_view()
: Returns a view of all leaks in the input collectionno_leaks_view()
: Returns the subset of the input collection without any leaksleaks_for_sample()
: Returns a view with leaks corresponding to the given sampletag_leaks()
: Tags leaks in the dataset as leaks
- Parameters:
samples β a
fiftyone.core.collections.SampleCollection
splits β
the dataset splits, specified in one of the following ways:
a list of tag strings
the name of a string/list field that encodes the split memberships
a dict mapping split names to
fiftyone.core.view.DatasetView
instances
threshold (0.2) β the similarity distance threshold to use when detecting leaks. Values in
[0.1, 0.25]
work well for the default setuproi_field (None) β an optional
fiftyone.core.labels.Detection
,fiftyone.core.labels.Detections
,fiftyone.core.labels.Polyline
, orfiftyone.core.labels.Polylines
field defining a region of interest within each image to use to compute leaksembeddings (None) β
if no
model
is provided, this argument specifies pre-computed embeddings to use, which can be any of the following:a
num_samples x num_dims
array of embeddingsif
roi_field
is specified, a dict mapping sample IDs tonum_patches x num_dims
arrays of patch embeddingsthe name of a dataset field containing the embeddings to use
If a
model
is provided, this argument specifies the name of a field in which to store the computed embeddings. In either case, when working with patch embeddings, you can provide either the fully-qualified path to the patch embeddings or just the name of the label attribute inroi_field
similarity_index (None) β a
fiftyone.brain.similarity.SimilarityIndex
or the brain key of a similarity index to use to load pre-computed embeddingsmodel (None) β
a
fiftyone.core.models.Model
or the name of a model from the FiftyOne Model Zoo to use to generate embeddings. The model must expose embeddings (model.has_embeddings = True
)model_kwargs (None) β a dictionary of optional keyword arguments to pass to the modelβs
Config
when a model name is providedforce_square (False) β whether to minimally manipulate the patch bounding boxes into squares prior to extraction. Only applicable when a
model
androi_field
are specifiedalpha (None) β an optional expansion/contraction to apply to the patches before extracting them, in
[-1, inf)
. If provided, the length and width of the box are expanded (or contracted, whenalpha < 0
) by(100 * alpha)%
. For example, setalpha = 0.1
to expand the boxes by 10%, and setalpha = -0.1
to contract the boxes by 10%. Only applicable when amodel
androi_field
are specifiedbatch_size (None) β a batch size to use when computing embeddings. Only applicable when a
model
is providednum_workers (None) β the number of workers to use when loading images. Only applicable when a Torch-based model is being used to compute embeddings
skip_failures (True) β whether to gracefully continue without raising an error if embeddings cannot be generated for a sample
progress (None) β whether to render a progress bar (True/False), use the default value
fiftyone.config.show_progress_bars
(None), or a progress callback function to invoke instead
- Returns:
a
fiftyone.brain.internal.core.leaky_splits.LeakySplitsIndex