fix(data): fix bug in voc dataloader (#11)

README.md

@@ -90,7 +90,6 @@ python tools/demo.py video -n yolox-s -c /path/to/your/yolox_s.pth.tar --path /p
 Step1. Prepare COCO dataset
 ```shell
 cd <YOLOX_HOME>
-mkdir datasets
 ln -s /path/to/your/COCO ./datasets/COCO
 ```
 

docs/train_custom_data.md

@@ -21,7 +21,6 @@ You can also write the Dataset by you own. Let's take the [VOC](../yolox/data/da
             img, target = self.preproc(img, target, self.input_dim)
 
         return img, target, img_info, img_id
-
 ```
 
 One more thing worth noting is that you should also implement "[pull_item](../yolox/data/datasets/voc.py#L129)" and "[load_anno](../yolox/data/datasets/voc.py#L121)" method for the Mosiac and MixUp augmentation.
@@ -29,6 +28,12 @@ One more thing worth noting is that you should also implement "[pull_item](../yo
 **Step 3** Prepare the evaluator. We currently have [COCO evaluator](../yolox/evaluators/coco_evaluator.py) and [VOC evaluator](../yolox/evaluators/voc_evaluator.py).
 If you have your own format data or evaluation metric, you may write your own evaluator.
 
+**Step 4** Put your dataset under $YOLOX_DIR/datasets$, for VOC:
+```shell
+ln -s /path/to/your/VOCdevkit ./datasets/VOCdevkit
+```
+* The path "VOCdevkit" will be used in your exp file described in next section.Specifically, in "get_data_loader" and "get_eval_loader" function.
+
 ## 2. Create your Exp file to control everything
 We put everything involved in a model to one single Exp file, including model setting, training setting, and testing setting.
 

exps/example/yolox_voc/yolox_voc_s.py

@@ -6,7 +6,7 @@ import torch.nn as nn
 import torch.distributed as dist
 
 from yolox.exp import Exp as MyExp
-
+from yolox.data import get_yolox_datadir
 
 class Exp(MyExp):
     def __init__(self):
@@ -14,7 +14,6 @@ class Exp(MyExp):
         self.num_classes = 20
         self.depth = 0.33
         self.width = 0.50
-        self.eval_interval = 2
         self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]
 
     def get_data_loader(self, batch_size, is_distributed, no_aug=False):
@@ -28,7 +27,7 @@ class Exp(MyExp):
         )
 
         dataset = VOCDetection(
-            data_dir='/data/Datasets/VOCdevkit',
+            data_dir=os.path.join(get_yolox_datadir(), "VOCdevkit"),
             image_sets=[('2007', 'trainval'), ('2012', 'trainval')],
             img_size=self.input_size,
             preproc=TrainTransform(
@@ -83,7 +82,7 @@ class Exp(MyExp):
         from yolox.data import VOCDetection, ValTransform
 
         valdataset = VOCDetection(
-            data_dir='/data/Datasets/VOCdevkit',
+            data_dir=os.path.join(get_yolox_datadir(), "VOCdevkit"),
             image_sets=[('2007', 'test')],
             img_size=self.test_size,
             preproc=ValTransform(

yolox/data/datasets/__init__.py

@@ -6,3 +6,4 @@ from .coco import COCODataset
 from .coco_classes import COCO_CLASSES
 from .datasets_wrapper import ConcatDataset, Dataset, MixConcatDataset
 from .mosaicdetection import MosaicDetection
+from .voc import VOCDetection

yolox/evaluators/__init__.py

@@ -3,3 +3,4 @@
 # Copyright (c) Megvii, Inc. and its affiliates.
 
 from .coco_evaluator import COCOEvaluator
+from .voc_evaluator import VOCEvaluator