Update Tuberculosis_Dataset.py

Tuberculosis_Dataset.py

@@ -1,12 +1,9 @@
-from datasets import GeneratorBasedBuilder, DownloadManager, DatasetInfo, Array3D, BuilderConfig, SplitGenerator, Version
-from datasets.features import Features, Value, Sequence
+from datasets import GeneratorBasedBuilder, DownloadManager, DatasetInfo, Features, Value, Sequence, ClassLabel, Image, BuilderConfig, SplitGenerator, Version
 import datasets
 import pandas as pd
 import json
 import zipfile
-from PIL import Image
-import numpy as np
-import io
+import os
 
 _DESCRIPTION = """\
 This dataset is curated from the original “The MultiCaRe Dataset” to focus on the chest tuberculosis patients and can be used to develop algorithms of the segmentation of chest CT images and the classification of tuberculosis positive or control.
@@ -24,19 +21,19 @@ class TuberculosisDataset(GeneratorBasedBuilder):
 
     def _info(self):
         return DatasetInfo(
-            description = _DESCRIPTION,
+            description=_DESCRIPTION,
             features=Features({
                 "case_id": Value("string"),
                 "gender": Value("string"),
                 "age": Value("int8"),
                 "case_text": Value("string"),
                 "keywords": Value("string"),
-                "image_arrays": Sequence(Value(dtype="uint8")),
+                "image_files": Sequence(Image()),  # Change from image_arrays to image_files
                 "caption": Value("string"),
             }),
-            supervised_keys = None,
-            homepage = "https://zenodo.org/api/records/10079370/files-archive",
-            citation = _CITATION,
+            supervised_keys=None,
+            homepage="https://zenodo.org/api/records/10079370/files-archive",
+            citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager):
@@ -47,7 +44,7 @@ class TuberculosisDataset(GeneratorBasedBuilder):
             "caption_json": f"{base_url}image_metadata.json",
             "images_zip": "https://github.com/zhankai-ye/tuberculosis_dataset/raw/main/images/PMC.zip"
         }
-        downloaded_files = dl_manager.download(urls)
+        downloaded_files = dl_manager.download_and_extract(urls)
 
         return [
             SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=downloaded_files),
@@ -77,31 +74,30 @@ class TuberculosisDataset(GeneratorBasedBuilder):
         merged_df = merged_df.where(pd.notnull(merged_df), None)
         merged_df['age'] = merged_df['age'].astype('int8')
 
-        # Prepare images
-        image_arrays = self._prepare_images(images_zip)
+        # Extract and prepare image file paths
+        image_file_paths = self._prepare_image_file_paths(images_zip)
 
         # Yield examples
         for idx, row in merged_df.iterrows():
+            image_files = image_file_paths.get(row["case_id"], [])
             yield idx, {
                 "case_id": row["case_id"],
                 "gender": row["gender"],
                 "age": int(row["age"]),
                 "case_text": row["case_text"],
                 "keywords": row["keywords"],
-                "image_arrays": image_arrays.get(row["case_id"], []),
+                "image_files": image_files,
                 "caption": row["caption"],
             }
 
-    def _prepare_images(self, images_zip_path):
-        image_arrays = {}
-        with zipfile.ZipFile(images_zip_path, 'r') as zip_ref:
-            for file_info in zip_ref.infolist():
-                if file_info.filename.endswith('.jpg') and not file_info.is_dir():
-                    with zip_ref.open(file_info) as image_file:
-                        img = Image.open(io.BytesIO(image_file.read()))
-                        img_array = np.array(img)
-                        key = file_info.filename.split('/')[-1].split('_')[0]
-                        if key not in image_arrays:
-                            image_arrays[key] = []
-                        image_arrays[key].append(img_array)
-        return image_arrays
+    def _prepare_image_file_paths(self, images_zip_path):
+        # Assumes images have been extracted to a directory in dl_manager's cache directory
+        image_file_paths = {}
+        for root, _, files in os.walk(images_zip_path):
+            for file in files:
+                if file.endswith('.jpg'):
+                    key = file.split('_')[0]
+                    if key not in image_file_paths:
+                        image_file_paths[key] = []
+                    image_file_paths[key].append(os.path.join(root, file))
+        return image_file_paths