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fix path in readme and preprocessing of multimodal tutorial #927

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Sep 14, 2022
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fix path in readme and preprocessing of multimodal tutorial #927

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8 changes: 3 additions & 5 deletions multimodal/openi_multilabel_classification_transchex/README.md
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Expand Up @@ -14,10 +14,8 @@ completed, the dataset can be readily used for the tutorial.

### Preprocessing Steps
1) Create a new folder named 'monai_data' for downloading the raw data and preprocessing.
2) Download the chest X-ray images in PNG format from this [link](https://openi.nlm.nih.gov/imgs/collections/NLMCXR_png.tgz). Copy the downloaded file (NLMCXR_png.tgz)
to 'monai_data' directory and extract it.
3) Download the reports in XML format from this [link](https://openi.nlm.nih.gov/imgs/collections/NLMCXR_reports.tgz). Copy the downloaded file (NLMCXR_reports.tgz)
to 'monai_data' directory and extract it.
2) Download the chest X-ray images in PNG format from this [link](https://openi.nlm.nih.gov/imgs/collections/NLMCXR_png.tgz). Copy the downloaded file (NLMCXR_png.tgz) to 'monai_data' directory and extract it to 'monai_data/dataset_orig/NLMCXR_png/'.
3) Download the reports in XML format from this [link](https://openi.nlm.nih.gov/imgs/collections/NLMCXR_reports.tgz). Copy the downloaded file (NLMCXR_reports.tgz) to 'monai_data' directory and extract it to 'monai_data/dataset_orig/NLMCXR_reports/'.
4) Download the splits of train, validation and test datasets from this [link](https://drive.google.com/u/1/uc?id=1jvT0jVl9mgtWy4cS7LYbF43bQE4mrXAY&export=download). Copy the downloaded file (TransChex_openi.zip)
to 'monai_data' directory and extract it.
to 'monai_data' directory and extract it here.
5) Run 'preprocess_openi.py' to process the images and reports.
8 changes: 5 additions & 3 deletions multimodal/openi_multilabel_classification_transchex/preprocess_openi.py
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Expand Up @@ -28,6 +28,8 @@ def create_report(img_names_list_, report_list_, gt_list_, save_add):

report_file_add= './monai_data/dataset_orig/NLMCXR_reports/ecgen-radiology'
img_file_add= './monai_data/dataset_orig/NLMCXR_png'
npy_add= './monai_data/TransChex_openi/'

img_save_add = './monai_data/dataset_proc/images'
report_train_save_add = './monai_data/dataset_proc/train.csv'
report_val_save_add = './monai_data/dataset_proc/validation.csv'
Expand All @@ -37,15 +39,15 @@ def create_report(img_names_list_, report_list_, gt_list_, save_add):
os.makedirs(img_save_add)
report_files = [f for f in listdir(report_file_add) if isfile(join(report_file_add, f))]

train_data = np.load('./train.npy', allow_pickle=True).item()
train_data = np.load(npy_add+'train.npy', allow_pickle=True).item()
train_data_id = train_data['id_GT']
train_data_gt = train_data['label_GT']

val_data = np.load('./validation.npy', allow_pickle=True).item()
val_data = np.load(npy_add+'validation.npy', allow_pickle=True).item()
val_data_id = val_data['id_GT']
val_data_gt = val_data['label_GT']

test_data = np.load('./test.npy', allow_pickle=True).item()
test_data = np.load(npy_add+'test.npy', allow_pickle=True).item()
test_data_id = test_data['id_GT']
test_data_gt = test_data['label_GT']

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