update docs

README.md

@@ -28,7 +28,7 @@ The designed architecture follows this guide [PyTorch-Project-Template](https://
 
 See [GETTING_STARTED.md](https://github.com/JDAI-CV/fast-reid/blob/master/GETTING_STARTED.md).
 
-Learn more at out [documentation](). And see [projects/](https://github.com/JDAI-CV/fast-reid/tree/master/projects) for some projects that are build on top of fastreid.
+Learn more at out [documentation](https://fast-reid.readthedocs.io/). And see [projects/](https://github.com/JDAI-CV/fast-reid/tree/master/projects) for some projects that are build on top of fastreid.
 
 ## Model Zoo and Baselines
 

docs/.gitignore

@@ -0,0 +1 @@
+_build

fastreid/data/__init__.py

@@ -4,4 +4,14 @@
 @contact: sherlockliao01@gmail.com
 """
 
-from .build import build_reid_train_loader, build_reid_test_loader
+from . import transforms  # isort:skip
+from .build import (
+    build_reid_train_loader,
+    build_reid_test_loader
+)
+from .common import CommDataset
+
+# ensure the builtin datasets are registered
+from . import datasets, samplers  # isort:skip
+
+__all__ = [k for k in globals().keys() if not k.startswith("_")]

fastreid/data/build.py

@@ -16,10 +16,25 @@ from .common import CommDataset
 from .datasets import DATASET_REGISTRY
 from .transforms import build_transforms
 
+__all__ = [
+    "build_reid_train_loader",
+    "build_reid_test_loader"
+]
+
 _root = os.getenv("FASTREID_DATASETS", "datasets")
 
 
 def build_reid_train_loader(cfg, mapper=None, **kwargs):
+    """
+    Build reid train loader
+
+    Args:
+        cfg : image file path
+        mapper : one of the supported image modes in PIL, or "BGR"
+
+    Returns:
+        torch.utils.data.DataLoader: a dataloader.
+    """
     cfg = cfg.clone()
 
     train_items = list()
@@ -60,6 +75,19 @@ def build_reid_train_loader(cfg, mapper=None, **kwargs):
 
 
 def build_reid_test_loader(cfg, dataset_name, mapper=None, **kwargs):
+    """
+    Build reid test loader
+
+    Args:
+        cfg:
+        dataset_name:
+        mapper:
+        **kwargs:
+
+    Returns:
+
+    """
+
     cfg = cfg.clone()
 
     dataset = DATASET_REGISTRY.get(dataset_name)(root=_root, **kwargs)

fastreid/data/data_utils.py

@@ -13,6 +13,7 @@ def read_image(file_name, format=None):
     """
     Read an image into the given format.
     Will apply rotation and flipping if the image has such exif information.
+
     Args:
         file_name (str): image file path
         format (str): one of the supported image modes in PIL, or "BGR"

fastreid/data/datasets/AirportALERT.py

@@ -14,6 +14,9 @@ __all__ = ['AirportALERT', ]
 
 @DATASET_REGISTRY.register()
 class AirportALERT(ImageDataset):
+    """Airport 
+
+    """
     dataset_dir = "AirportALERT"
     dataset_name = "airport"
 

fastreid/data/datasets/bases.py

@@ -7,6 +7,7 @@
 import copy
 import logging
 import os
+
 from tabulate import tabulate
 from termcolor import colored
 
@@ -16,6 +17,7 @@ logger = logging.getLogger(__name__)
 class Dataset(object):
     """An abstract class representing a Dataset.
     This is the base class for ``ImageDataset`` and ``VideoDataset``.
+
     Args:
         train (list): contains tuples of (img_path(s), pid, camid).
         query (list): contains tuples of (img_path(s), pid, camid).

fastreid/data/datasets/caviara.py

@@ -19,6 +19,8 @@ __all__ = ['CAVIARa',]
 
 @DATASET_REGISTRY.register()
 class CAVIARa(ImageDataset):
+    """CAVIARa
+    """
     dataset_dir = "CAVIARa"
     dataset_name = "caviara"
 

fastreid/data/datasets/cuhk_sysu.py

@@ -15,7 +15,7 @@ from ..datasets import DATASET_REGISTRY
 
 @DATASET_REGISTRY.register()
 class cuhkSYSU(ImageDataset):
-    r"""CUHK SYSU datasets.
+    """CUHK SYSU datasets.
 
     The dataset is collected from two sources: street snap and movie.
     In street snap, 12,490 images and 6,057 query persons were collected

fastreid/data/datasets/iLIDS.py

@@ -15,6 +15,8 @@ __all__ = ['iLIDS', ]
 
 @DATASET_REGISTRY.register()
 class iLIDS(ImageDataset):
+    """iLIDS
+    """
     dataset_dir = "iLIDS"
     dataset_name = "ilids"
 

fastreid/data/datasets/lpw.py

@@ -15,7 +15,9 @@ __all__ = ['LPW', ]
 
 @DATASET_REGISTRY.register()
 class LPW(ImageDataset):
-    dataset_dir = "pep_256x128"
+    """LPW
+    """
+    dataset_dir = "pep_256x128/data_slim"
     dataset_name = "lpw"
 
     def __init__(self, root='datasets', **kwargs):

fastreid/data/datasets/pes3d.py

@@ -15,6 +15,8 @@ __all__ = ['PeS3D',]
 
 @DATASET_REGISTRY.register()
 class PeS3D(ImageDataset):
+    """3Dpes
+    """
     dataset_dir = "3DPeS"
     dataset_name = "pes3d"
 

fastreid/data/datasets/pku.py

@@ -15,6 +15,8 @@ __all__ = ['PKU', ]
 
 @DATASET_REGISTRY.register()
 class PKU(ImageDataset):
+    """PKU
+    """
     dataset_dir = "PKUv1a_128x48"
     dataset_name = 'pku'
 

fastreid/data/datasets/prai.py

@@ -5,18 +5,18 @@
 """
 
 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__ = ['PRAI', ]
 
 
 @DATASET_REGISTRY.register()
 class PRAI(ImageDataset):
+    """PRAI
+    """
     dataset_dir = "PRAI-1581"
     dataset_name = 'prai'
 
@@ -41,4 +41,3 @@ class PRAI(ImageDataset):
             camid = self.dataset_name + "_" + img_info[1]
             data.append([img_path, pid, camid])
         return data
-

fastreid/data/datasets/saivt.py

@@ -15,6 +15,8 @@ __all__ = ['SAIVT', ]
 
 @DATASET_REGISTRY.register()
 class SAIVT(ImageDataset):
+    """SAIVT
+    """
     dataset_dir = "SAIVT-SoftBio"
     dataset_name = "saivt"
 

fastreid/data/datasets/sensereid.py

@@ -15,6 +15,8 @@ __all__ = ['SenseReID', ]
 
 @DATASET_REGISTRY.register()
 class SenseReID(ImageDataset):
+    """Sense reid
+    """
     dataset_dir = "SenseReID"
     dataset_name = "senseid"
 

fastreid/data/datasets/shinpuhkan.py

@@ -14,6 +14,8 @@ __all__ = ['Shinpuhkan', ]
 
 @DATASET_REGISTRY.register()
 class Shinpuhkan(ImageDataset):
+    """shinpuhkan
+    """
     dataset_dir = "shinpuhkan"
     dataset_name = 'shinpuhkan'
 

fastreid/data/datasets/sysu_mm.py

@@ -17,6 +17,8 @@ __all__ = ['SYSU_mm', ]
 
 @DATASET_REGISTRY.register()
 class SYSU_mm(ImageDataset):
+    """sysu mm
+    """
     dataset_dir = "SYSU-MM01"
     dataset_name = "sysumm01"
 

fastreid/data/datasets/thermalworld.py

@@ -19,6 +19,8 @@ __all__ = ['Thermalworld',]
 
 @DATASET_REGISTRY.register()
 class Thermalworld(ImageDataset):
+    """thermal world
+    """
     dataset_dir = "thermalworld_rgb"
     dataset_name = "thermalworld"
 

fastreid/data/samplers/__init__.py

@@ -6,3 +6,10 @@
 
 from .triplet_sampler import BalancedIdentitySampler, NaiveIdentitySampler
 from .data_sampler import TrainingSampler, InferenceSampler
+
+__all__ = [
+    "BalancedIdentitySampler",
+    "NaiveIdentitySampler",
+    "TrainingSampler",
+    "InferenceSampler"
+]

fastreid/data/transforms/__init__.py

@@ -4,6 +4,8 @@
 @contact: sherlockliao01@gmail.com
 """
 
-from .autoaugment import *
+from .autoaugment import AutoAugment
 from .build import build_transforms
 from .transforms import *
+
+__all__ = [k for k in globals().keys() if not k.startswith("_")]

fastreid/data/transforms/transforms.py

@@ -149,13 +149,9 @@ class AugMix(object):
             np.random.dirichlet([self.aug_prob_coeff] * self.mixture_width))
         m = np.float32(np.random.beta(self.aug_prob_coeff, self.aug_prob_coeff))
 
-        # image = np.asarray(image, dtype=np.float32).copy()
-        # mix = np.zeros_like(image)
         mix = np.zeros([image.size[1], image.size[0], 3])
-        # h, w = image.shape[0], image.shape[1]
         for i in range(self.mixture_width):
             image_aug = image.copy()
-            # image_aug = Image.fromarray(image.copy().astype(np.uint8))
             depth = self.mixture_depth if self.mixture_depth > 0 else np.random.randint(1, 4)
             for _ in range(depth):
                 op = np.random.choice(self.augmentations)

fastreid/modeling/__init__.py

@@ -4,4 +4,20 @@
 @contact: sherlockliao01@gmail.com
 """
 
-from .meta_arch import build_model
+from . import losses
+from .backbones import (
+    BACKBONE_REGISTRY,
+    build_resnet_backbone,
+    build_backbone,
+)
+from .heads import (
+    REID_HEADS_REGISTRY,
+    build_heads,
+    EmbeddingHead,
+)
+from .meta_arch import (
+    build_model,
+    META_ARCH_REGISTRY,
+)
+
+__all__ = [k for k in globals().keys() if k not in k.startswith("_")]

fastreid/modeling/backbones/build.py

@@ -10,8 +10,7 @@ BACKBONE_REGISTRY = Registry("BACKBONE")
 BACKBONE_REGISTRY.__doc__ = """
 Registry for backbones, which extract feature maps from images
 The registered object must be a callable that accepts two arguments:
-1. A :class:`detectron2.config.CfgNode`
+1. A :class:`fastreid.config.CfgNode`
-2. A :class:`detectron2.layers.ShapeSpec`, which contains the input shape specification.
 It must returns an instance of :class:`Backbone`.
 """
 

fastreid/modeling/heads/build.py

@@ -8,7 +8,8 @@ from ...utils.registry import Registry
 
 REID_HEADS_REGISTRY = Registry("HEADS")
 REID_HEADS_REGISTRY.__doc__ = """
-Registry for ROI heads in a generalized R-CNN model.
+Registry for reid heads in a baseline model.
+
 ROIHeads take feature maps and region proposals, and
 perform per-region computation.
 The registered object will be called with `obj(cfg, input_shape)`.

fastreid/modeling/losses/__init__.py

@@ -4,7 +4,9 @@
 @contact: sherlockliao01@gmail.com
 """
 
+from .circle_loss import *
 from .cross_entroy_loss import cross_entropy_loss, log_accuracy
 from .focal_loss import focal_loss
 from .triplet_loss import triplet_loss
-from .circle_loss import *
+
+__all__ = [k for k in globals().keys() if k not in k.startswith("_")]