update docs

docs/index.rst

@@ -1,9 +1,9 @@
-.. detectron2 documentation master file, created by
+.. fastreid documentation master file, created by
    sphinx-quickstart on Sat Sep 21 13:46:45 2019.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to detectron2's documentation!
+Welcome to fastreid's documentation!
 ======================================
 
 .. toctree::

docs/modules/export.rst

@@ -1,9 +0,0 @@
-fastreid.export
-=========================
-
-Related tutorial: :doc:`../tutorials/deployment`.
-
-.. automodule:: fastreid.export
-    :members:
-    :undoc-members:
-    :show-inheritance:

docs/requirements.txt

@@ -1,20 +1,20 @@
-termcolor
-numpy
-tqdm
-docutils==0.16
-# https://github.com/sphinx-doc/sphinx/commit/7acd3ada3f38076af7b2b5c9f3b60bb9c2587a3d
-git+git://github.com/sphinx-doc/sphinx.git@7acd3ada3f38076af7b2b5c9f3b60bb9c2587a3d
-recommonmark==0.6.0
-sphinx_rtd_theme
 matplotlib
-termcolor
+scipy
-yacs
-tabulate
-cloudpickle
 Pillow
-future
+numpy
-requests
+prettytable
-six
+easydict
-git+git://github.com/facebookresearch/fvcore.git
+scikit-learn
-https://download.pytorch.org/whl/cpu/torch-1.5.0%2Bcpu-cp37-cp37m-linux_x86_64.whl
+pyyaml
-https://download.pytorch.org/whl/cpu/torchvision-0.6.0%2Bcpu-cp37-cp37m-linux_x86_64.whl
+yacs
+termcolor
+tabulate
+tensorboard
+opencv-python
+pyyaml
+yacs
+termcolor
+scikit-learn
+tabulate
+gdown
+faiss-gpu

fastreid/data/datasets/caviara.py

@@ -5,16 +5,12 @@
 """
 
 import os
-from scipy.io import loadmat
 from glob import glob
 
 from fastreid.data.datasets import DATASET_REGISTRY
 from fastreid.data.datasets.bases import ImageDataset
-import pdb
-import random
-import numpy as np
 
-__all__ = ['CAVIARa',]
+__all__ = ['CAVIARa', ]
 
 
 @DATASET_REGISTRY.register()

fastreid/data/datasets/cuhk03.py

@@ -100,7 +100,7 @@ class CUHK03(ImageDataset):
 
         import h5py
         from imageio import imwrite
-        from scipy.io import loadmat
+        from scipy import io
 
         PathManager.mkdirs(self.imgs_detected_dir)
         PathManager.mkdirs(self.imgs_labeled_dir)
@@ -236,7 +236,7 @@ class CUHK03(ImageDataset):
 
         print('Creating new split for detected images (767/700) ...')
         train_info, query_info, gallery_info = _extract_new_split(
-            loadmat(self.split_new_det_mat_path),
+            io.loadmat(self.split_new_det_mat_path),
             self.imgs_detected_dir
         )
         split = [{
@@ -256,7 +256,7 @@ class CUHK03(ImageDataset):
 
         print('Creating new split for labeled images (767/700) ...')
         train_info, query_info, gallery_info = _extract_new_split(
-            loadmat(self.split_new_lab_mat_path),
+            io.loadmat(self.split_new_lab_mat_path),
             self.imgs_labeled_dir
         )
         split = [{

fastreid/data/datasets/sysu_mm.py

@@ -5,12 +5,10 @@
 """
 
 import os
-from scipy.io import loadmat
 from glob import glob
 
 from fastreid.data.datasets import DATASET_REGISTRY
 from fastreid.data.datasets.bases import ImageDataset
-import pdb
 
 __all__ = ['SYSU_mm', ]
 
@@ -37,7 +35,7 @@ class SYSU_mm(ImageDataset):
         data = []
 
         file_path_list = ['cam1', 'cam2', 'cam4', 'cam5']
-        
+
         for file_path in file_path_list:
             camid = self.dataset_name + "_" + file_path
             pid_list = os.listdir(os.path.join(train_path, file_path))
@@ -47,4 +45,3 @@ class SYSU_mm(ImageDataset):
                 for img_path in img_list:
                     data.append([img_path, pid, camid])
         return data
-

fastreid/data/datasets/thermalworld.py

@@ -5,16 +5,12 @@
 """
 
 import os
-from scipy.io import loadmat
 from glob import glob
 
 from fastreid.data.datasets import DATASET_REGISTRY
 from fastreid.data.datasets.bases import ImageDataset
-import pdb
-import random
-import numpy as np
 
-__all__ = ['Thermalworld',]
+__all__ = ['Thermalworld', ]
 
 
 @DATASET_REGISTRY.register()
@@ -40,7 +36,7 @@ class Thermalworld(ImageDataset):
         pid_list = os.listdir(train_path)
         for pid_dir in pid_list:
             pid = self.dataset_name + "_" + pid_dir
-            img_list = glob(os.path.join(train_path, pid_dir,  "*.jpg"))
+            img_list = glob(os.path.join(train_path, pid_dir, "*.jpg"))
             for img_path in img_list:
                 camid = self.dataset_name + "_cam0"
                 data.append([img_path, pid, camid])

fastreid/engine/defaults.py

@@ -11,7 +11,6 @@ since they are meant to represent the "common default behavior" people need in t
 import argparse
 import logging
 import os
-import math
 import sys
 from collections import OrderedDict
 
@@ -247,7 +246,6 @@ class DefaultTrainer(TrainerBase):
             **self.scheduler,
         )
 
-
         self.start_epoch = 0
         self.max_epoch = cfg.SOLVER.MAX_EPOCH
         self.max_iter = self.max_epoch * self.iters_per_epoch
@@ -323,6 +321,7 @@ class DefaultTrainer(TrainerBase):
             cfg.SOLVER.FREEZE_ITERS,
             cfg.SOLVER.FREEZE_FC_ITERS,
         ))
+
         # Do PreciseBN before checkpointer, because it updates the model and need to
         # be saved by checkpointer.
         # This is not always the best: if checkpointing has a different frequency,

fastreid/engine/hooks.py

@@ -10,8 +10,8 @@ import time
 from collections import Counter
 
 import torch
-from torch import nn
 from apex.parallel import DistributedDataParallel
+from torch import nn
 
 from fastreid.evaluation.testing import flatten_results_dict
 from fastreid.solver import optim

fastreid/engine/train_loop.py

@@ -12,7 +12,6 @@ from typing import Dict
 import numpy as np
 import torch
 from apex import amp
-from apex.parallel import DistributedDataParallel
 
 import fastreid.utils.comm as comm
 from fastreid.utils.events import EventStorage, get_event_storage

fastreid/evaluation/__init__.py

@@ -1,8 +1,7 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
 from .evaluator import DatasetEvaluator, inference_context, inference_on_dataset
 from .rank import evaluate_rank
-from .roc import evaluate_roc
 from .reid_evaluation import ReidEvaluator
+from .roc import evaluate_roc
 from .testing import print_csv_format, verify_results
 
 __all__ = [k for k in globals().keys() if not k.startswith("_")]

fastreid/evaluation/rank_cylib/rank_cy.pyx

@@ -5,7 +5,6 @@ import cython
 import numpy as np
 cimport numpy as np
 from collections import defaultdict
-import faiss
 
 
 """

fastreid/modeling/__init__.py

@@ -20,4 +20,4 @@ from .meta_arch import (
     META_ARCH_REGISTRY,
 )
 
-__all__ = [k for k in globals().keys() if k not in k.startswith("_")]
+__all__ = [k for k in globals().keys() if not k.startswith("_")]

fastreid/modeling/losses/__init__.py

@@ -9,4 +9,4 @@ from .cross_entroy_loss import cross_entropy_loss, log_accuracy
 from .focal_loss import focal_loss
 from .triplet_loss import triplet_loss
 
-__all__ = [k for k in globals().keys() if k not in k.startswith("_")]
+__all__ = [k for k in globals().keys() if not k.startswith("_")]

fastreid/utils/logger.py

@@ -5,9 +5,11 @@ import os
 import sys
 import time
 from collections import Counter
-from .file_io import PathManager
+
 from termcolor import colored
 
+from .file_io import PathManager
+
 
 class _ColorfulFormatter(logging.Formatter):
     def __init__(self, *args, **kwargs):

requirements.txt

@@ -1,20 +0,0 @@
-matplotlib
-scipy
-Pillow
-numpy
-prettytable
-easydict
-scikit-learn
-pyyaml
-yacs
-termcolor
-tabulate
-tensorboard
-opencv-python
-pyyaml
-yacs
-termcolor
-scikit-learn
-tabulate
-gdown
-faiss-gpu