Update links and using cars insteam of car

open-mmlab · Aug 12, 2022 · 7b1af11 · 7b1af11
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diff --git a/...s/_base_/datasets/stanford_car_bs8_448.py → .../_base_/datasets/stanford_cars_bs8_448.py b/...s/_base_/datasets/stanford_car_bs8_448.py → .../_base_/datasets/stanford_cars_bs8_448.py
@@ -1,5 +1,5 @@
 # dataset settings
-dataset_type = 'StanfordCar'
+dataset_type = 'StanfordCars'
 img_norm_cfg = dict(
     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
 train_pipeline = [

diff --git a/configs/_base_/schedules/stanford_car_bs8.py → ...igs/_base_/schedules/stanford_cars_bs8.py b/configs/_base_/schedules/stanford_car_bs8.py → ...igs/_base_/schedules/stanford_cars_bs8.py
diff --git a/configs/resnet/README.md b/configs/resnet/README.md
@@ -72,6 +72,12 @@ The pre-trained models on ImageNet-21k are used to fine-tune, and therefore don'
 | :-------: | :--------------------------------------------------: | :--------: | :-------: | :------: | :-------: | :------------------------------------------------: | :---------------------------------------------------: |
 | ResNet-50 | [ImageNet-21k-mill](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_3rdparty-mill_in21k_20220331-faac000b.pth) |  448x448   |   23.92   |  16.48   |   88.45   | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet50_8xb8_cub.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb8_cub_20220307-57840e60.pth) \| [log](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb8_cub_20220307-57840e60.log.json) |
 
+### Stanford-Cars
+
+|   Model   |                       Pretrain                       | resolution | Params(M) | Flops(G) | Top-1 (%) |                       Config                       |                       Download                        |
+| :-------: | :--------------------------------------------------: | :--------: | :-------: | :------: | :-------: | :------------------------------------------------: | :---------------------------------------------------: |
+| ResNet-50 | [ImageNet-21k-mill](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_3rdparty-mill_in21k_20220331-faac000b.pth) |  448x448   |   23.92   |  16.48   |   92.82   | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/resnet/resnet50_8xb8_cars.py) | [model](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb8_cars_20220812-9d85901a.pth) \| [log](https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb8_cars_20220812-9d85901a.log.json) |
+
 ## Citation
 
 ```

diff --git a/configs/resnet/metafile.yml b/configs/resnet/metafile.yml
@@ -350,3 +350,16 @@ Models:
     Pretrain: https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_3rdparty-mill_in21k_20220331-faac000b.pth
     Weights: https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb8_cub_20220307-57840e60.pth
     Config: configs/resnet/resnet50_8xb8_cub.py
+  - Name: resnet50_8xb8_cars
+    Metadata:
+      FLOPs: 16480000000
+      Parameters: 23920000
+    In Collection: ResNet
+    Results:
+      - Dataset: StanfordCars
+        Metrics:
+          Top 1 Accuracy: 92.82
+        Task: Image Classification
+    Pretrain: https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_3rdparty-mill_in21k_20220331-faac000b.pth
+    Weights: https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb8_cars_20220812-9d85901a.pth
+    Config: configs/resnet/resnet50_8xb8_cars.py
diff --git a/configs/resnet/resnet50_8xb8_stanford_car.py → configs/resnet/resnet50_8xb8_cars.py b/configs/resnet/resnet50_8xb8_stanford_car.py → configs/resnet/resnet50_8xb8_cars.py
@@ -1,7 +1,7 @@
 _base_ = [
     '../_base_/models/resnet50.py',
-    '../_base_/datasets/stanford_car_bs8_448.py',
-    '../_base_/schedules/stanford_car_bs8.py', '../_base_/default_runtime.py'
+    '../_base_/datasets/stanford_cars_bs8_448.py',
+    '../_base_/schedules/stanford_cars_bs8.py', '../_base_/default_runtime.py'
 ]
 
 # use pre-train weight converted from https://github.com/Alibaba-MIIL/ImageNet21K # noqa

diff --git a/mmcls/datasets/__init__.py b/mmcls/datasets/__init__.py
@@ -12,7 +12,7 @@
 from .mnist import MNIST, FashionMNIST
 from .multi_label import MultiLabelDataset
 from .samplers import DistributedSampler, RepeatAugSampler
-from .stanford_car import StanfordCar
+from .stanford_car import StanfordCars
 from .voc import VOC
 
 __all__ = [
@@ -21,5 +21,5 @@
     'DistributedSampler', 'ConcatDataset', 'RepeatDataset',
     'ClassBalancedDataset', 'DATASETS', 'PIPELINES', 'ImageNet21k', 'SAMPLERS',
     'build_sampler', 'RepeatAugSampler', 'KFoldDataset', 'CUB',
-    'CustomDataset', 'StanfordCar'
+    'CustomDataset', 'StanfordCars'
 ]
diff --git a/mmcls/datasets/stanford_car.py b/mmcls/datasets/stanford_car.py
@@ -10,16 +10,17 @@
 
 
 @DATASETS.register_module()
-class StanfordCar(BaseDataset):
-    """`Stanford Car <https://ai.stanford.edu/~jkrause/cars/car_dataset.html>`_
-    Dataset.
+class StanfordCars(BaseDataset):
+    """`Stanford Cars.
+
+    <https://ai.stanford.edu/~jkrause/cars/car_dataset.html>`_ Dataset.
 
     After downloading and decompression, the dataset
     directory structure is as follows.
 
-    Stanford Car dataset directory:
+    Stanford Cars dataset directory:
 
-        Stanford Car
+        Stanford Cars
         ├── cars_train
         │   ├── 00001.jpg
         │   ├── 00002.jpg
@@ -176,7 +177,7 @@ def __init__(self,
                 self.train_ann_file = osp.join(data_prefix,
                                                'devkit/cars_train_annos.mat')
             data_prefix = osp.join(data_prefix, 'cars_train')
-        super(StanfordCar, self).__init__(
+        super(StanfordCars, self).__init__(
             ann_file=ann_file,
             data_prefix=data_prefix,
             test_mode=test_mode,

diff --git a/requirements/runtime.txt b/requirements/runtime.txt
@@ -1,3 +1,4 @@
 matplotlib
 numpy
 packaging
+scipy
diff --git a/requirements/tests.txt b/requirements/tests.txt
@@ -4,6 +4,5 @@ interrogate
 isort==4.3.21
 mmdet
 pytest
-scipy
 xdoctest >= 0.10.0
 yapf
diff --git a/tests/test_data/test_datasets/test_common.py b/tests/test_data/test_datasets/test_common.py
@@ -764,8 +764,8 @@ def tearDownClass(cls):
         cls.tmpdir.cleanup()
 
 
-class TestStanfordCar(TestBaseDataset):
-    DATASET_TYPE = 'StanfordCar'
+class TestStanfordCars(TestBaseDataset):
+    DATASET_TYPE = 'StanfordCars'
 
     def test_initialize(self):
         dataset_class = DATASETS.get(self.DATASET_TYPE)
-Original file line number
+Diff line change
@@ Expand Up / @@ -4,6 +4,5 @@ interrogate @@
     isort==4.3.21
     mmdet
     pytest
-    scipy
     xdoctest >= 0.10.0
     yapf