similarity
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
파일 탐색기
최종 버전 다운로드 (.zip)- nightly-publish.yml
- python-publish.yml
- test.yml
- EfficientNetSim.md
- ResNet18Sim.md
- ResNet50Sim.md
- Augmenter.md
- BarlowAugmenter.md
- ContrastiveAugmenter.md
- SimCLRAugmenter.md
- Callback.md
- ClassificationMatch.md
- ClassificationMetric.md
- EvalCallback.md
- Evaluator.md
- FloatTensor.md
- IntTensor.md
- make_classification_metric.md
- MemoryEvaluator.md
- Path.md
- SimilarityModel.md
- SplitValidationLoss.md
- Tensor.md
- unpack_lookup_distances.md
- unpack_lookup_labels.md
- unpack_results.md
- BinaryAccuracy.md
- F1Score.md
- FalsePositiveRate.md
- NegativePredictiveValue.md
- Precision.md
- Recall.md
- ABC.md
- CosineDistance.md
- Distance.md
- distance_canonicalizer.md
- EuclideanDistance.md
- InnerProductSimilarity.md
- ManhattanDistance.md
- SNRDistance.md
- SquaredEuclideanDistance.md
- CalibrationResults.md
- defaultdict.md
- deque.md
- Indexer.md
- Lookup.md
- make_classification_matcher.md
- MemoryStore.md
- NMSLibSearch.md
- PandasDataFrame.md
- RetrievalMetric.md
- Search.md
- Store.md
- tabulate.md
- time.md
- tqdm.md
- ActivationStdLoggingLayer.md
- GeneralizedMeanPooling.md
- GeneralizedMeanPooling1D.md
- GeneralizedMeanPooling2D.md
- MetricEmbedding.md
- Barlow.md
- CircleLoss.md
- MetricLoss.md
- MultiSimilarityLoss.md
- PNLoss.md
- SimCLRLoss.md
- SimSiamLoss.md
- SoftNearestNeighborLoss.md
- TripletLoss.md
- VicReg.md
- MatchMajorityVote.md
- MatchNearest.md
- ContrastiveModel.md
- BNDCG.md
- MapAtK.md
- PrecisionAtK.md
- RecallAtK.md
- MultiShotMemorySampler.md
- select_examples.md
- SingleShotMemorySampler.md
- TFDatasetMultiShotMemorySampler.md
- TFRecordDatasetSampler.md
- avg_neg.md
- avg_pos.md
- batch_class_ratio.md
- dist_gap.md
- DistanceGapMetric.md
- DistanceMetric.md
- max_neg.md
- max_pos.md
- min_neg.md
- min_pos.md
- sum_neg.md
- sum_pos.md
- BoolTensor.md
- is_tensor_or_variable.md
- tf_cap_memory.md
- confusion_matrix.md
- projector.md
- visualize_views.md
- viz_neigbors_imgs.md
- _api_cache.json
- _redirects.yaml
- _toc.yaml
- all_symbols.md
- api_report.pb
- architectures.md
- augmenters.md
- callbacks.md
- classification_metrics.md
- distances.md
- evaluators.md
- indexer.md
- layers.md
- losses.md
- matchers.md
- models.md
- retrieval_metrics.md
- samplers.md
- search.md
- stores.md
- training_metrics.md
- utils.md
- visualization.md
- README.md
- contrastive_batch.png
- contrastive_loss_functions.png
- contrastive_model_terms.png
- self_supervised_overview.png
- similar-cats-and-dogs.jpg
- similarity-learning-overview.png
- tfsim_overview.png
- __init__.py
- dataset.py
- tfds.py
- types.py
- utils.py
- __init__.py
- architectures.py
- augmentations.py
- experiments.py
- losses.py
- metrics.py
- optimizers.py
- utils.py
- all_losses_basic.json
- hyperparameter_all.json
- train_all.json
- train_single.json
- create_datasets.py
- hyper_parameter_search.py
- README.md
- requirements.txt
- train.py
- indexing_search_and_store.ipynb
- multimodal_example.ipynb
- README.md
- sampler_io_cookbook.ipynb
- supervised_hello_world.ipynb
- unsupervised_hello_world.ipynb
- visualization.ipynb
- gen_api_doc.py
- increment_version.py
- README.md
- __init__.py
- __init__.py
- efficientnet.py
- resnet18.py
- resnet50.py
- utils.py
- __init__.py
- blur.py
- color_jitter.py
- cropping.py
- flip.py
- random_apply.py
- solarize.py
- __init__.py
- augmenter.py
- barlow.py
- contrastive.py
- simclr.py
- __init__.py
- binary_accuracy.py
- classification_metric.py
- f1_score.py
- false_positive_rate.py
- negative_predictive_value.py
- precision.py
- recall.py
- utils.py
- __init__.py
- cosine.py
- distance.py
- euclidean.py
- inner_product.py
- manhattan.py
- snr.py
- __init__.py
- evaluator.py
- memory_evaluator.py
- __init__.py
- barlow.py
- circle_loss.py
- lifted_structure_loss.py
- metric_loss.py
- multinegrank_loss.py
- multisim_loss.py
- pn_loss.py
- simclr.py
- simsiam.py
- softnn_loss.py
- triplet_loss.py
- utils.py
- vicreg.py
- xbm_loss.py
- __init__.py
- classification_match.py
- match_majority_vote.py
- match_nearest.py
- utils.py
- __init__.py
- contrastive_model.py
- similarity_model.py
- __init__.py
- bndcg.py
- map_at_k.py
- precision_at_k.py
- recall_at_k.py
- retrieval_metric.py
- utils.py
- __init__.py
- file_samplers.py
- memory_samplers.py
- samplers.py
- tfdata_sampler.py
- tfdataset_samplers.py
- tfrecords_samplers.py
- utils.py
- __init__.py
- faiss.py
- linear.py
- nmslib.py
- search.py
- __init__.py
- cached.py
- memory.py
- redis.py
- store.py
- __init__.py
- distance_metrics.py
- utils.py
- __init__.py
- confusion_matrix_viz.py
- neighbors_viz.py
- projector.py
- vizualize_views.py
- __init__.py
- algebra.py
- base_indexer.py
- callbacks.py
- indexer.py
- layers.py
- schedules.py
- types.py
- utils.py
- __init__.py
- test_efficientnet.py
- test_resnet18.py
- test_resnet50.py
- test_blur.py
- test_color_jitter.py
- test_crop.py
- test_flip.py
- test_solarize.py
- test_augmenters.py
- __init__.py
- test_classification_metrics.py
- generate_calibration_data.py
- mnist_fashion_embeddings.npz
- __init__.py
- test_memory_evaluator.py
- test_basic_flow.py
- test_multihead.py
- test_readme_minimal.py
- __init__.py
- test_lifted_structure_loss.py
- test_pn_loss.py
- test_softnn_loss.py
- test_triplet_loss.py
- test_xbm_loss.py
- utils.py
- __init__.py
- test_classification_match.py
- test_majority_vote.py
- test_match_nearest.py
- __init__.py
- test_contrastive_model.py
- test_similarity_model.py
- __init__.py
- test_bndcg.py
- test_map_at_k.py
- test_precision_at_k.py
- test_recall_at_k.py
- test_retrieval_metric.py
- __init__.py
- test_file_samplers.py
- test_memory_samplers.py
- test_tfdata_sampler.py
- test_tfdataset_samplers.py
- test_tfrecord_samplers.py
- __init__.py
- test_faiss.py
- test_linear.py
- test_nmslib.py
- __init__.py
- test_cached.py
- test_memory.py
- test_redis.py
- __init__.py
- test_distance_metrics.py
- __init__.py
- test_confusion_matrix.py
- test_neighbors_viz.py
- __init__.py
- conftest.py
- test_algebra.py
- test_callbacks.py
- test_distances.py
- test_indexer.py
- test_layers.py
- test_schedules.py
- test_types.py
- test_utils.py
- .coveragerc
- .flake8
- .git-blame-ignore-revs
- .gitattributes
- .gitignore
- .pre-commit-config.yaml
- CONTRIBUTING.md
- LICENSE
- mypy.ini
- pyproject.toml
- pytest.ini
- README.md
- releases.md
- setup.py
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/tensorflow/similarity
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd similarity
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. 공식 설치 스크립트
쉬움 추천사전 준비물
- Python 3 pip 명령어를 쓰려면 Python이 필요합니다.
pip install --upgrade-strategy=only-if-needed tensorflow_similarity[tensorflow]
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
설치 후 새 터미널을 열고, 프로그램의 버전 확인 명령(예: --version)으로 정상 설치됐는지 확인하세요.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
3. Python
쉬움사전 준비물
pip install --upgrade-strategy=only-if-needed tensorflow_similarity[tensorflow]
PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.
에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
// repository documentation
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