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https://github.com/JDAI-CV/fast-reid.git
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update docs
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.. detectron2 documentation master file, created by
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.. fastreid documentation master file, created by
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sphinx-quickstart on Sat Sep 21 13:46:45 2019.
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sphinx-quickstart on Sat Sep 21 13:46:45 2019.
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You can adapt this file completely to your liking, but it should at least
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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contain the root `toctree` directive.
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Welcome to detectron2's documentation!
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Welcome to fastreid's documentation!
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======================================
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======================================
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.. toctree::
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.. toctree::
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fastreid.export
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=========================
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Related tutorial: :doc:`../tutorials/deployment`.
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.. automodule:: fastreid.export
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:members:
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:undoc-members:
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:show-inheritance:
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@ -1,20 +1,20 @@
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termcolor
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numpy
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tqdm
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docutils==0.16
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# https://github.com/sphinx-doc/sphinx/commit/7acd3ada3f38076af7b2b5c9f3b60bb9c2587a3d
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git+git://github.com/sphinx-doc/sphinx.git@7acd3ada3f38076af7b2b5c9f3b60bb9c2587a3d
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recommonmark==0.6.0
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sphinx_rtd_theme
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matplotlib
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matplotlib
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termcolor
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scipy
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yacs
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tabulate
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cloudpickle
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Pillow
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Pillow
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future
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numpy
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requests
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prettytable
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six
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easydict
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git+git://github.com/facebookresearch/fvcore.git
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scikit-learn
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https://download.pytorch.org/whl/cpu/torch-1.5.0%2Bcpu-cp37-cp37m-linux_x86_64.whl
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pyyaml
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https://download.pytorch.org/whl/cpu/torchvision-0.6.0%2Bcpu-cp37-cp37m-linux_x86_64.whl
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yacs
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termcolor
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tabulate
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tensorboard
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opencv-python
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pyyaml
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yacs
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termcolor
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scikit-learn
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tabulate
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gdown
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faiss-gpu
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"""
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"""
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import os
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import os
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from scipy.io import loadmat
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from glob import glob
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from glob import glob
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from fastreid.data.datasets import DATASET_REGISTRY
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from fastreid.data.datasets import DATASET_REGISTRY
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from fastreid.data.datasets.bases import ImageDataset
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from fastreid.data.datasets.bases import ImageDataset
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import pdb
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import random
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import numpy as np
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__all__ = ['CAVIARa', ]
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__all__ = ['CAVIARa', ]
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@ -100,7 +100,7 @@ class CUHK03(ImageDataset):
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import h5py
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import h5py
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from imageio import imwrite
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from imageio import imwrite
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from scipy.io import loadmat
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from scipy import io
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PathManager.mkdirs(self.imgs_detected_dir)
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PathManager.mkdirs(self.imgs_detected_dir)
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PathManager.mkdirs(self.imgs_labeled_dir)
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PathManager.mkdirs(self.imgs_labeled_dir)
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@ -236,7 +236,7 @@ class CUHK03(ImageDataset):
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print('Creating new split for detected images (767/700) ...')
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print('Creating new split for detected images (767/700) ...')
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train_info, query_info, gallery_info = _extract_new_split(
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train_info, query_info, gallery_info = _extract_new_split(
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loadmat(self.split_new_det_mat_path),
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io.loadmat(self.split_new_det_mat_path),
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self.imgs_detected_dir
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self.imgs_detected_dir
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)
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)
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split = [{
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split = [{
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@ -256,7 +256,7 @@ class CUHK03(ImageDataset):
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print('Creating new split for labeled images (767/700) ...')
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print('Creating new split for labeled images (767/700) ...')
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train_info, query_info, gallery_info = _extract_new_split(
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train_info, query_info, gallery_info = _extract_new_split(
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loadmat(self.split_new_lab_mat_path),
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io.loadmat(self.split_new_lab_mat_path),
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self.imgs_labeled_dir
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self.imgs_labeled_dir
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)
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)
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split = [{
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split = [{
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"""
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"""
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import os
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import os
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from scipy.io import loadmat
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from glob import glob
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from glob import glob
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from fastreid.data.datasets import DATASET_REGISTRY
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from fastreid.data.datasets import DATASET_REGISTRY
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from fastreid.data.datasets.bases import ImageDataset
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from fastreid.data.datasets.bases import ImageDataset
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import pdb
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__all__ = ['SYSU_mm', ]
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__all__ = ['SYSU_mm', ]
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@ -47,4 +45,3 @@ class SYSU_mm(ImageDataset):
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for img_path in img_list:
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for img_path in img_list:
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data.append([img_path, pid, camid])
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data.append([img_path, pid, camid])
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return data
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return data
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"""
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"""
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import os
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import os
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from scipy.io import loadmat
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from glob import glob
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from glob import glob
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from fastreid.data.datasets import DATASET_REGISTRY
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from fastreid.data.datasets import DATASET_REGISTRY
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from fastreid.data.datasets.bases import ImageDataset
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from fastreid.data.datasets.bases import ImageDataset
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import pdb
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import random
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import numpy as np
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__all__ = ['Thermalworld', ]
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__all__ = ['Thermalworld', ]
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import argparse
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import argparse
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import logging
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import logging
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import os
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import os
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import math
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import sys
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import sys
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from collections import OrderedDict
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from collections import OrderedDict
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@ -247,7 +246,6 @@ class DefaultTrainer(TrainerBase):
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**self.scheduler,
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**self.scheduler,
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)
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)
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self.start_epoch = 0
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self.start_epoch = 0
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self.max_epoch = cfg.SOLVER.MAX_EPOCH
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self.max_epoch = cfg.SOLVER.MAX_EPOCH
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self.max_iter = self.max_epoch * self.iters_per_epoch
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self.max_iter = self.max_epoch * self.iters_per_epoch
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cfg.SOLVER.FREEZE_ITERS,
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cfg.SOLVER.FREEZE_ITERS,
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cfg.SOLVER.FREEZE_FC_ITERS,
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cfg.SOLVER.FREEZE_FC_ITERS,
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))
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))
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# Do PreciseBN before checkpointer, because it updates the model and need to
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# Do PreciseBN before checkpointer, because it updates the model and need to
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# be saved by checkpointer.
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# be saved by checkpointer.
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# This is not always the best: if checkpointing has a different frequency,
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# This is not always the best: if checkpointing has a different frequency,
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from collections import Counter
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from collections import Counter
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import torch
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import torch
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from torch import nn
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from apex.parallel import DistributedDataParallel
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from apex.parallel import DistributedDataParallel
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from torch import nn
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from fastreid.evaluation.testing import flatten_results_dict
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from fastreid.evaluation.testing import flatten_results_dict
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from fastreid.solver import optim
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from fastreid.solver import optim
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import numpy as np
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import numpy as np
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import torch
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import torch
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from apex import amp
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from apex import amp
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from apex.parallel import DistributedDataParallel
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import fastreid.utils.comm as comm
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import fastreid.utils.comm as comm
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from fastreid.utils.events import EventStorage, get_event_storage
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from fastreid.utils.events import EventStorage, get_event_storage
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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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from .evaluator import DatasetEvaluator, inference_context, inference_on_dataset
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from .evaluator import DatasetEvaluator, inference_context, inference_on_dataset
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from .rank import evaluate_rank
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from .rank import evaluate_rank
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from .roc import evaluate_roc
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from .reid_evaluation import ReidEvaluator
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from .reid_evaluation import ReidEvaluator
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from .roc import evaluate_roc
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from .testing import print_csv_format, verify_results
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from .testing import print_csv_format, verify_results
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__all__ = [k for k in globals().keys() if not k.startswith("_")]
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__all__ = [k for k in globals().keys() if not k.startswith("_")]
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@ -5,7 +5,6 @@ import cython
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import numpy as np
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import numpy as np
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cimport numpy as np
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cimport numpy as np
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from collections import defaultdict
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from collections import defaultdict
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import faiss
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"""
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"""
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META_ARCH_REGISTRY,
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META_ARCH_REGISTRY,
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)
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)
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__all__ = [k for k in globals().keys() if k not in k.startswith("_")]
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__all__ = [k for k in globals().keys() if not k.startswith("_")]
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from .focal_loss import focal_loss
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from .focal_loss import focal_loss
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from .triplet_loss import triplet_loss
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from .triplet_loss import triplet_loss
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__all__ = [k for k in globals().keys() if k not in k.startswith("_")]
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__all__ = [k for k in globals().keys() if not k.startswith("_")]
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import sys
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import sys
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import time
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import time
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from collections import Counter
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from collections import Counter
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from .file_io import PathManager
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from termcolor import colored
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from termcolor import colored
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from .file_io import PathManager
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class _ColorfulFormatter(logging.Formatter):
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class _ColorfulFormatter(logging.Formatter):
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def __init__(self, *args, **kwargs):
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def __init__(self, *args, **kwargs):
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@ -1,20 +0,0 @@
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matplotlib
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scipy
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Pillow
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numpy
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prettytable
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easydict
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scikit-learn
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pyyaml
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yacs
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termcolor
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tabulate
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tensorboard
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opencv-python
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pyyaml
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yacs
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termcolor
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scikit-learn
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tabulate
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gdown
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faiss-gpu
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