Update README.md

README.md

@@ -45,13 +45,13 @@ it contains id, "label, location1 & location2", subject_id, study_id, dicom_id.
 it contains id, "label1 && label2", subject_id, study_id, dicom_id.
 - **CXR-AL14:**
   - CXR_AL14_localization_xxx.tsv: is used for locatization and classification tasks. For each row,
-it contains id, label, "x1,y1,x2,y2", subject_id, study_id, dicom_id.
+it contains id, label, "x1,y1,x2,y2", image_id.
 - **VinDr-CXR:**
   - VinDr_CXR_localization_xxx.tsv: is used for locatization and classification tasks. For each row,
-it contains id, label, "x1,y1,x2,y2", subject_id, study_id, dicom_id.
+it contains id, label, "x1,y1,x2,y2", image_id.
 - **ChestX-Det:**
   - ChestX_Det_localization_xxx.tsv: is used for locatization and classification tasks. For each row,
-it contains id, label, "x1,y1,x2,y2", subject_id, study_id, dicom_id.
+it contains id, label, "x1,y1,x2,y2", image_id.
 - **CheXmask:**
   - CheXmask_segmentation_xxx.tsv: is used for segmentation task. For each row,
 it contains id, label, "x1,y1,x2,y2, ..., x30, y30", subject_id, study_id, dicom_id.
@@ -60,5 +60,5 @@ it contains id, label, "x1,y1,x2,y2, ..., x30, y30", subject_id, study_id, dicom
 it contains id, label, "x1,y1,x2,y2, ..., x30, y30", subject_id, study_id, dicom_id.
 
 ## Dataset Use
-- df = pd.read_csv(f, sep='\t', header=None)
+- Please run data_prepare.py, which constructs a training batch for all tasks. Each row should contain the following: id, instruction, label, image_id, and task_type.