Rename VinBrain_Dataset to VinDr_Dataset (keep backward-compatible alias)

BENCHMARKS.md

@@ -47,7 +47,7 @@ Results updated: 07/23/2023
 | jfhealthcare-DenseNet121 |12,525,301| 0.78 | 0.89 | 0.82 | 0.94 | 0.96 | - | - | - | - | - | - | - | - | - | - |
 | CheXpert-DenseNet121-ensemble | | 0.82 | 0.92 | 0.88 | 0.97 | 0.97 | - | - | - | - | - | - | - | - | - | - |
 
-## VinBrain
+## VinDr-CXR
 
 | Model Name |# Params|  Atelectasis | Cardiomegaly | Consolidation | Effusion | Infiltration | Lung Opacity | Pleural_Thickening | Pneumothorax |
 |-|-:|-|-|-|-|-|-|-|-|

README.md

@@ -185,8 +185,8 @@ d_siim = xrv.datasets.SIIM_Pneumothorax_Dataset(imgpath="dicom-images-train/",
                                                 csvpath="train-rle.csv")
 
 # VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations. https://arxiv.org/abs/2012.15029
-d_vin = xrv.datasets.VinBrain_Dataset(imgpath=".../train",
-                                      csvpath=".../train.csv")
+d_vin = xrv.datasets.VinDr_Dataset(imgpath=".../train",
+                                   csvpath=".../train.csv")
 
 # National Library of Medicine Tuberculosis Datasets. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256233/
 d_nlmtb = xrv.datasets.NLMTB_Dataset(imgpath="path to MontgomerySet or ChinaSet_AllFiles")

docs/source/datasets.rst

@@ -78,8 +78,8 @@ Available Datasets
      - TBX11K tuberculosis dataset
    * - :class:`xrv.datasets.SIIM_Pneumothorax_Dataset <xrv.datasets.SIIM_Pneumothorax_Dataset>`
      - SIIM-ACR Pneumothorax Segmentation
-   * - :class:`xrv.datasets.VinBrain_Dataset <xrv.datasets.VinBrain_Dataset>`
-     - VinBigData Chest X-ray Abnormalities Detection
+   * - :class:`xrv.datasets.VinDr_Dataset <xrv.datasets.VinDr_Dataset>`
+     - VinDr-CXR (VinBigData Chest X-ray Abnormalities Detection)
    * - :class:`xrv.datasets.StonyBrookCOVID_Dataset <xrv.datasets.StonyBrookCOVID_Dataset>`
      - Stony Brook University COVID-19 positive cases
    * - :class:`xrv.datasets.ObjectCXR_Dataset <xrv.datasets.ObjectCXR_Dataset>`
@@ -131,7 +131,7 @@ Dataset Classes
 .. autoclass:: xrv.datasets.SIIM_Pneumothorax_Dataset
     :members: string
 
-.. autoclass:: xrv.datasets.VinBrain_Dataset
+.. autoclass:: xrv.datasets.VinDr_Dataset
     :members: string
 
 .. autoclass:: xrv.datasets.StonyBrookCOVID_Dataset

scripts/dataset_utils.py

@@ -101,7 +101,7 @@ def get_data(dataset_str, masks=False, unique_patients=False,
         datasets.append(dataset)
 
     if "vin" in dataset_str:
-        dataset = xrv.datasets.VinBrain_Dataset(
+        dataset = xrv.datasets.VinDr_Dataset(
             imgpath=dataset_dir + "vinbigdata-chest-xray-abnormalities-detection/train",
             csvpath=dataset_dir + "vinbigdata-chest-xray-abnormalities-detection/train.csv",
             pathology_masks=masks, 

scripts/model_calibrate.py

@@ -94,7 +94,7 @@
     datas.append(dataset)
     datas_names.append("siim")
 if "vin" in cfg.dataset:
-    dataset = xrv.datasets.VinBrain_Dataset(
+    dataset = xrv.datasets.VinDr_Dataset(
         imgpath=cfg.dataset_dir + "vinbigdata-chest-xray-abnormalities-detection/train",
         csvpath=cfg.dataset_dir + "vinbigdata-chest-xray-abnormalities-detection/train.csv",
         transform=transforms, data_aug=data_aug)

scripts/train_model.py

@@ -117,7 +117,7 @@
     datas.append(dataset)
     datas_names.append("siim")
 if "vin" in cfg.dataset:
-    dataset = xrv.datasets.VinBrain_Dataset(
+    dataset = xrv.datasets.VinDr_Dataset(
         imgpath=cfg.dataset_dir + "vinbigdata-chest-xray-abnormalities-detection/train",
         csvpath=cfg.dataset_dir + "vinbigdata-chest-xray-abnormalities-detection/train.csv",
         transform=transform, data_aug=data_aug)

tests/test_dataloaders.py

@@ -22,10 +22,10 @@
                    xrv.datasets.Openi_Dataset,
                    xrv.datasets.CheX_Dataset,
                    xrv.datasets.SIIM_Pneumothorax_Dataset,
-                   xrv.datasets.VinBrain_Dataset]
+                   xrv.datasets.VinDr_Dataset]
 
 dataset_classes_pydicom = [xrv.datasets.SIIM_Pneumothorax_Dataset,
-                           xrv.datasets.VinBrain_Dataset]
+                           xrv.datasets.VinDr_Dataset]
 
 test_data_path = "/tmp/testdata"
 test_png_img_file = os.path.join(file_path, "00000001_000.png")
@@ -76,7 +76,7 @@ def create_test_images(request):
     create_test_img(test_png_img_file, xrv.datasets.Openi_Dataset, "CXR10_IM-0002-1001.png")
     create_test_img(test_jpg_img_file, xrv.datasets.CheX_Dataset, "train/patient00004/study1/view1_frontal.jpg")
     create_test_img(test_dcm_img_file, xrv.datasets.SIIM_Pneumothorax_Dataset, "1.2.276.0.7230010.3.1.2.8323329.6904.1517875201.850818/1.2.276.0.7230010.3.1.3.8323329.6904.1517875201.850817/1.2.276.0.7230010.3.1.4.8323329.6904.1517875201.850819.dcm")
-    create_test_img(test_dcm_img_file, xrv.datasets.VinBrain_Dataset, "000434271f63a053c4128a0ba6352c7f.dicom")
+    create_test_img(test_dcm_img_file, xrv.datasets.VinDr_Dataset, "000434271f63a053c4128a0ba6352c7f.dicom")
 
 
 def test_dataloader_basic(create_test_images, is_pydicom_installed):
@@ -112,6 +112,10 @@ def test_dataloader_merging(is_pydicom_installed):
     xrv.datasets.Merge_Dataset(datasets)
 
 
+def test_vinbrain_alias():
+    assert xrv.datasets.VinBrain_Dataset is xrv.datasets.VinDr_Dataset
+
+
 def test_dataloader_merging_dups():
 
     datasets = []
@@ -438,7 +442,7 @@ def test_chexlocalize_dataset_segmentation_masks(tmp_path):
     assert atelectasis_idx in sample["pathology_masks"]
     assert sample["pathology_masks"][atelectasis_idx].sum() > 0
     # Pathologies absent from the segmentation JSON get no entry (sparse dict,
-    # matching NIH_Dataset/VinBrain_Dataset/ObjectCXR_Dataset)
+    # matching NIH_Dataset/VinDr_Dataset/ObjectCXR_Dataset)
     assert cardiomegaly_idx not in sample["pathology_masks"]
     assert bool(d.csv["has_masks"].iloc[0])
 

torchxrayvision/datasets.py

@@ -228,7 +228,7 @@ class MergeDataset(Dataset):
         - 1 RSNA_Pneumonia_Dataset num_samples=26684 views=['PA', 'AP']
         - 2 NIH_Dataset num_samples=112120 views=['PA', 'AP']
         - 3 SIIM_Pneumothorax_Dataset num_samples=12954
-        - 4 VinBrain_Dataset num_samples=15000 views=['PA', 'AP']
+        - 4 VinDr_Dataset num_samples=15000 views=['PA', 'AP']
     """
 
     def __init__(self, datasets, seed=0, label_concat=False):
@@ -1400,7 +1400,7 @@ def get_mask_dict(self, imgid, this_size):
                 "Airspace Opacity" if patho == "Lung Opacity" else patho
 
             # Don't add masks for labels we don't have (matches NIH_Dataset,
-            # VinBrain_Dataset, ObjectCXR_Dataset: sparse dict, no zero masks)
+            # VinDr_Dataset, ObjectCXR_Dataset: sparse dict, no zero masks)
             if json_key not in entry:
                 continue
 
@@ -2215,7 +2215,7 @@ def rle2mask(rle, width, height):
         return path_mask
 
 
-class VinBrain_Dataset(Dataset):
+class VinDr_Dataset(Dataset):
     """VinDr-CXR dataset
 
     A large chest X-ray dataset collected at two major hospitals in Vietnam
@@ -2234,11 +2234,13 @@ class VinBrain_Dataset(Dataset):
 
     Example::
 
-        d_vin = xrv.datasets.VinBrain_Dataset(
+        d_vin = xrv.datasets.VinDr_Dataset(
             imgpath=".../train",
             csvpath=".../train.csv"
         )
 
+    ``VinBrain_Dataset`` is kept as a backward-compatible alias of this class.
+
     Citation:
         Nguyen HQ, Lam K, Le LT, et al.
         VinDr-CXR: An open dataset of chest X-rays with radiologist's
@@ -2259,7 +2261,7 @@ def __init__(self,
                  seed=0,
                  pathology_masks=False
                  ):
-        super(VinBrain_Dataset, self).__init__()
+        super(VinDr_Dataset, self).__init__()
 
         np.random.seed(seed)  # Reset the seed so all runs are the same.
         self.imgpath = imgpath
@@ -2382,6 +2384,10 @@ def get_mask_dict(self, image_name, this_size):
         return path_mask
 
 
+# alias so it is backwards compatible
+VinBrain_Dataset = VinDr_Dataset
+
+
 class StonyBrookCOVID_Dataset(Dataset):
     """Stony Brook COVID-19 Radiographic Assessment of Lung Opacity (RALO) dataset