update training instruction

Summary: update dataset configuration and training instruction

GETTING_STARTED.md

@@ -12,3 +12,25 @@ Then you should set the pretrain model path in `configs/Base-bagtricks.yml`.
 ```bash
 cd fastreid/evaluation/rank_cylib; make all
 ```
+
+## Training & Evaluation in Command Line
+
+We provide a script in "tools/train_net.py", that is made to train all the configs provided in fastreid.
+You may want to use it as a reference to write your own training script.
+
+To train a model with "train_net.py", first setup up the corresponding datasets following [datasets/README.md](https://github.com/JDAI-CV/fast-reid/tree/master/datasets), then run:
+
+```bash
+CUDA_VISIBLE_DEVICES=$gpus tools/train_net.py --config-file ./configs/Market1501/bagtricks_R50.yml
+```
+
+The configs are made for 1-GPU training.
+
+To evaluate a model's performance, use
+
+```bash
+CUDA_VISIBLE_DEVICES=$gpus tools/train_net.py --config-file ./configs/Market1501/bagtricks_R50.yml \
+--eval-only MODEL.WEIGHTS /path/to/checkpoint_file
+```
+
+For more options, see `./train_net.py -h`.

datasets/README.md

@@ -2,9 +2,9 @@
 
 Fastreid has buildin support for a few datasets. The datasets are assumed to exist in a directory specified by the environment variable `FASTREID_DATASETS`. Under this directory, fastreid expects to find datasets in the structure described below.
 
-You can set the location for builtin datasets by `export FASTREID_DATASETS=/path/to/datasets/`. If left unset, the default is `./datasets` relative to your current working directory.
+You can set the location for builtin datasets by `export FASTREID_DATASETS=/path/to/datasets/`. If left unset, the default is `datasets/` relative to your current working directory.
 
-The model zoo contains configs and models that use these buildin datasets.
+The [model zoo](https://github.com/JDAI-CV/fast-reid/blob/master/MODEL_ZOO.md) contains configs and models that use these buildin datasets.
 
 ## Expected dataset structure for Market1501
 
@@ -20,4 +20,24 @@ datasets/
 
 ## Expected dataset structure for DukeMTMC
 
+1. Download datasets to `datasets/`
+2. Extract dataset. The dataset structure would like:
+
+```bash
+datasets/
+    DukeMTMC-reID/
+        bounding_box_train/
+        bounding_box_test/
+```
+
 ## Expected dataset structure for MSMT17
+
+1. Download datasets to `datasets/`
+2. Extract dataset. The dataset structure would like:
+
+```bash
+datasets/
+    MSMT17_V2/
+        mask_train_v2/
+        mask_test_v2/
+```

fastreid/data/build.py

@@ -4,6 +4,7 @@
 @contact: sherlockliao01@gmail.com
 """
 
+import os
 import torch
 from torch._six import container_abcs, string_classes, int_classes
 from torch.utils.data import DataLoader
@@ -13,13 +14,15 @@ from .common import CommDataset
 from .datasets import DATASET_REGISTRY
 from .transforms import build_transforms
 
+_root = os.getenv("FASTREID_DATASETS", "datasets")
+
 
 def build_reid_train_loader(cfg):
     train_transforms = build_transforms(cfg, is_train=True)
 
     train_items = list()
     for d in cfg.DATASETS.NAMES:
-        dataset = DATASET_REGISTRY.get(d)(combineall=cfg.DATASETS.COMBINEALL)
+        dataset = DATASET_REGISTRY.get(d)(root=_root, combineall=cfg.DATASETS.COMBINEALL)
         dataset.show_train()
         train_items.extend(dataset.train)
 
@@ -50,7 +53,7 @@ def build_reid_train_loader(cfg):
 def build_reid_test_loader(cfg, dataset_name):
     test_transforms = build_transforms(cfg, is_train=False)
 
-    dataset = DATASET_REGISTRY.get(dataset_name)()
+    dataset = DATASET_REGISTRY.get(dataset_name)(root=_root)
     dataset.show_test()
     test_items = dataset.query + dataset.gallery
 

fastreid/data/datasets/__init__.py

@@ -19,3 +19,5 @@ from .msmt17 import MSMT17
 from .veri import VeRi
 from .vehicleid import VehicleID, SmallVehicleID, MediumVehicleID, LargeVehicleID
 from .veriwild import VeRiWild, SmallVeRiWild, MediumVeRiWild, LargeVeRiWild
+
+__all__ = [k for k in globals().keys() if "builtin" not in k and not k.startswith("_")]

fastreid/data/datasets/bases.py

@@ -5,11 +5,8 @@
 """
 
 import copy
-import os
-
-import numpy as np
-import torch
 import logging
+import os
 
 
 class Dataset(object):

fastreid/utils/checkpoint.py

@@ -95,7 +95,7 @@ class Checkpointer(object):
         if not path:
             # no checkpoint provided
             self.logger.info(
-                "No checkpoint found. Initializing model from scratch"
+                "No checkpoint found. Training model from scratch"
             )
             return {}
         self.logger.info("Loading checkpoint from {}".format(path))

tools/train_net.py

@@ -1,3 +1,4 @@
+#!/usr/bin/env python
 # encoding: utf-8
 """
 @author:  sherlock