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README.md

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+---
+dataset_info:
+  config_name: video_00
+  features:
+  - name: original_image
+    dtype: image
+  - name: edit_prompt
+    dtype: string
+  - name: edited_image
+    dtype: image
+  - name: fr_image
+    dtype: image
+  - name: ls_image
+    dtype: image
+  - name: oh_image
+    dtype: image
+  - name: rs_image
+    dtype: image
+  splits:
+  - name: train
+    num_bytes: 4765012
+    num_examples: 4934
+  download_size: 2825400113
+  dataset_size: 4765012
+---

data/video_00.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:426142cc53207f0314afcb974b02ee662718aa693ad3499e3563b25f4a1b521d
+size 2825400113

multi2img.py

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+import os
+from xml.etree import ElementTree as ET
+import datasets
+
+_DESCRIPTION = """\
+The dataset img2img data.
+"""
+_NAME = "multi2img"
+
+_HOMEPAGE = f"https://huggingface.co/datasets/pranjalipathre/{_NAME}"
+
+_LICENSE = ""
+
+_DATA = f"https://huggingface.co/datasets/pranjalipathre/{_NAME}/resolve/main/data/"
+# _DATA = f"/home/pranjali/Documents/Research/pybullet/img2img/{_NAME}/data/"
+
+class i2iDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        # rlbench-doors multiview dataset. - 4.9k 
+        datasets.BuilderConfig(name="video_00", data_dir=f"{_DATA}video_00.zip"),
+    ]
+    DEFAULT_CONFIG_NAME = "video_00"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "original_image": datasets.Image(),
+                    "edit_prompt": datasets.Value("string"),
+                    "edited_image": datasets.Image(),
+                    "fr_image": datasets.Image(),
+                    "ls_image": datasets.Image(),
+                    "oh_image": datasets.Image(),
+                    "rs_image": datasets.Image(),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        data = dl_manager.download_and_extract(self.config.data_dir)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data": data,
+                },
+            ),
+        ]
+
+    @staticmethod
+    def parse_text(root: ET.Element, file: str, index: int) -> dict:
+        idx = str(index).zfill(6)
+        ele = root.find(f".//*[@frame='{idx}']")
+        dt = {
+            "text": ele.get("text")
+        }
+        return dt
+
+    def _generate_examples(self, data):
+        treePath = os.path.join(data, "annotations.xml")
+
+        tree = ET.parse(treePath)
+        root = tree.getroot()
+
+        for idx, file in enumerate(sorted(os.listdir(os.path.join(data, "original_images")))):
+            dat = self.parse_text(root, file, idx)
+            txt = dat["text"]
+
+            yield idx, {
+                "original_image": os.path.join(data, "original_images", file),
+                "edit_prompt": txt,
+                "edited_image": os.path.join(data, "edited_images", file),
+                "fr_image":  os.path.join(data, "fr_images", file),
+                "ls_image":  os.path.join(data, "ls_images", file),
+                "oh_image":  os.path.join(data, "oh_images", file),
+                "rs_image":  os.path.join(data, "rs_images", file),
+            }