Delete vlm-projects-multi-lang-final.py

vlm-projects-multi-lang-final.py

@@ -1,97 +0,0 @@
-# dataset.py
-import os
-import pandas as pd
-import datasets
-
-_DESCRIPTION = "A multilingual medical imaging dataset with questions and answers, structured by language."
-_HOMEPAGE = "https://huggingface.co/datasets/tungvu3196/vlm-projects-multi-lang-final"
-_LICENSE = "apache-2.0"
-_CITATION = ""
-
-LANGUAGES = [
-    "English","Vietnamese","French","German","Spanish","Russian","Korean",
-    "Mandarin","Japanese","Thai","Indonesian","Malay","Arabic","Hindi",
-    "Turkish","Portuguese"
-]
-
-class VlmProjectsMultiLangFinal(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name=lang_name,
-            version=datasets.Version("1.0.0"),
-            description=f"Dataset in {lang_name}",
-        )
-        for lang_name in LANGUAGES
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-            features=datasets.Features({
-                "A1": datasets.Value("string"),
-                "A2": datasets.Value("string"),
-                "A3": datasets.Value("string"),
-                "A4": datasets.Value("string"),
-                "Bbox coordinates normalized (X, Y, W, H)": datasets.Value("string"),
-                "Column 9": datasets.Value("float64"),
-                "Deliverable": datasets.Value("string"),
-                "Doctor": datasets.Value("string"),
-                "Google Drive Link": datasets.Value("string"),
-                "No.": datasets.Value("int64"),
-                "Notes": datasets.Value("string"),
-                "Original": datasets.Value("string"),
-                "Patient ID": datasets.Value("string"),
-                "Q1": datasets.Value("string"),
-                "Q2": datasets.Value("string"),
-                "Q3": datasets.Value("string"),
-                "Q4": datasets.Value("string"),
-                "Remove Status": datasets.Value("string"),
-                "Slide": datasets.Value("string"),
-                "Start date": datasets.Value("float64"),
-                "Status": datasets.Value("string"),
-                "__index_level_0__": datasets.Value("int64"),
-                # These two will render in the Viewer if the underlying files exist in the repo:
-                "image": datasets.Image(),                 # path or dict -> file in repo
-                "image_with_bboxes": datasets.Image(),
-                # keep as string/URL if it's not a local file:
-                "rotated_link": datasets.Value("string"),
-            }),
-        )
-
-    def _split_generators(self, dl_manager):
-        # Map config name ("English") to folder ("english")
-        lang_dir = self.config.name.lower()
-        base = os.path.join(self.config.data_dir or "data", lang_dir)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": os.path.join(base, "train.parquet"),
-                            "base_dir": base},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": os.path.join(base, "test.parquet"),
-                            "base_dir": base},
-            ),
-        ]
-
-    def _generate_examples(self, filepath, base_dir):
-        # Read parquet produced by your pipeline
-        df = pd.read_parquet(filepath)
-
-        for i, row in df.iterrows():
-            ex = row.to_dict()
-
-            # If parquet stored relative paths like "images/xyz.png", keep them relative to repo:
-            for col in ("image", "image_with_bboxes"):
-                p = ex.get(col)
-                if isinstance(p, str) and len(p):
-                    # If the path isn't an URL, make it relative to the dataset files
-                    if not (p.startswith("http://") or p.startswith("https://")):
-                        ex[col] = os.path.join(base_dir, p).replace("\\", "/")
-                    # if it *is* a URL, leave as-is (Image will try to download)
-
-            yield i, ex