| 282 | layers_to_extract_from_coll = [layers_to_extract_from] |
| 283 | |
| 284 | def get_patchcore(input_shape, sampler, device): |
| 285 | loaded_patchcores = [] |
| 286 | for backbone_name, layers_to_extract_from in zip( |
| 287 | backbone_names, layers_to_extract_from_coll |
| 288 | ): |
| 289 | backbone_seed = None |
| 290 | if ".seed-" in backbone_name: |
| 291 | backbone_name, backbone_seed = backbone_name.split(".seed-")[0], int( |
| 292 | backbone_name.split("-")[-1] |
| 293 | ) |
| 294 | backbone = patchcore.backbones.load(backbone_name) |
| 295 | backbone.name, backbone.seed = backbone_name, backbone_seed |
| 296 | |
| 297 | nn_method = patchcore.common.FaissNN(faiss_on_gpu, faiss_num_workers) |
| 298 | |
| 299 | patchcore_instance = patchcore.patchcore.PatchCore(device) |
| 300 | patchcore_instance.load( |
| 301 | backbone=backbone, |
| 302 | layers_to_extract_from=layers_to_extract_from, |
| 303 | device=device, |
| 304 | input_shape=input_shape, |
| 305 | pretrain_embed_dimension=pretrain_embed_dimension, |
| 306 | target_embed_dimension=target_embed_dimension, |
| 307 | patchsize=patchsize, |
| 308 | featuresampler=sampler, |
| 309 | anomaly_scorer_num_nn=anomaly_scorer_num_nn, |
| 310 | nn_method=nn_method, |
| 311 | ) |
| 312 | loaded_patchcores.append(patchcore_instance) |
| 313 | return loaded_patchcores |
| 314 | |
| 315 | return ("get_patchcore", get_patchcore) |
| 316 | |