Upload dataset files

DF_segmented_mask.py

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+import pandas as pd
+from huggingface_hub import hf_hub_url
+import datasets
+import os
+
+_VERSION = datasets.Version("0.0.1")
+
+_DESCRIPTION = "TODO"
+_HOMEPAGE = "TODO"
+_LICENSE = "TODO"
+_CITATION = "TODO"
+
+_FEATURES = datasets.Features(
+    {
+        "flawless": datasets.Image(),
+        "mask": datasets.Image(),
+        "reference": datasets.Image(),
+        "prompt": datasets.Value("string"),
+    },
+)
+
+METADATA_URL = hf_hub_url(
+    "NegarMov/DF_segmented_mask",
+    filename="train.jsonl",
+    repo_type="dataset",
+)
+
+FLAWLESS_URL = hf_hub_url(
+    "NegarMov/DF_segmented_mask",
+    filename="flawless.zip",
+    repo_type="dataset",
+)
+
+MASK_URL = hf_hub_url(
+    "NegarMov/DF_segmented_mask",
+    filename="mask.zip",
+    repo_type="dataset",
+)
+
+reference_URL = hf_hub_url(
+    "NegarMov/DF_segmented_mask",
+    filename="reference.zip",
+    repo_type="dataset",
+)
+
+_DEFAULT_CONFIG = datasets.BuilderConfig(name="default", version=_VERSION)
+
+
+class DF_segmented_mask(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [_DEFAULT_CONFIG]
+    DEFAULT_CONFIG_NAME = "default"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=_FEATURES,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        metadata_path = dl_manager.download(METADATA_URL)
+        flawless_dir = dl_manager.download_and_extract(
+            FLAWLESS_URL
+        )
+        mask_dir = dl_manager.download_and_extract(
+            MASK_URL
+        )
+        reference_dir = dl_manager.download_and_extract(
+            reference_URL
+        )
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "metadata_path": metadata_path,
+                    "flawless_dir": flawless_dir,
+                    "mask_dir": mask_dir,
+                    "reference_dir": reference_dir,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, metadata_path, flawless_dir, mask_dir, reference_dir):
+        metadata = pd.read_json(metadata_path, lines=True)
+
+        for _, row in metadata.iterrows():
+            prompt = row["prompt"]
+
+            flawless_path = row["flawless"]
+            flawless_path = os.path.join(flawless_dir, flawless_path)
+            flawless = open(flawless_path, "rb").read()
+
+            mask_path = row["mask"]
+            mask_path = os.path.join(
+                mask_dir, row["mask"]
+            )
+            mask = open(mask_path, "rb").read()
+
+            reference_path = row["reference"]
+            reference_path = os.path.join(
+                reference_dir, row["reference"]
+            )
+            reference = open(reference_path, "rb").read()
+
+            yield row["flawless"], {
+                "prompt": prompt,
+                "flawless": {
+                    "path": flawless_path,
+                    "bytes": flawless,
+                },
+                "mask": {
+                    "path": mask_path,
+                    "bytes": mask,
+                },
+                "reference": {
+                    "path": reference_path,
+                    "bytes": reference,
+                },
+            }

flawless.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5090c6b4fb01c647e0ca1ee0e703bac396be76ff932263466e050a025d30b26e
+size 100028209

mask.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1b706e37b3a28150b9d9674e74e6f308e72dbeec4b20987a35691396cc9f5e71
+size 23283557

reference.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5c2585692c9468f6473566ea74eb4a5215a4c7761a1afead845b66e47b0b5bbe
+size 101138075