Convert dataset to Parquet

README.md

@@ -1,30 +1,73 @@
 ---
 dataset_info:
+- config_name: all
   features:
-    - name: image
-      dtype: image
-    - name: depth
-      dtype: image
-    - name: mask
-      dtype: image
+  - name: image
+    dtype: image
+  - name: depth
+    dtype: image
+  - name: mask
+    dtype: image
   splits:
-    - name: train
-      num_examples: 12000
+  - name: train
+    num_bytes: 22712394633.0
+    num_examples: 12000
+  download_size: 22677841215
+  dataset_size: 22712394633.0
+- config_name: blender
+  features:
+  - name: image
+    dtype: image
+  - name: depth
+    dtype: image
+  - name: mask
+    dtype: image
+  splits:
+  - name: train
+    num_bytes: 11049913446.0
+    num_examples: 6000
+  download_size: 11050639109
+  dataset_size: 11049913446.0
+- config_name: default
+  features:
+  - name: image
+    dtype: image
+  - name: depth
+    dtype: image
+  - name: mask
+    dtype: image
+  splits:
+  - name: train
+    num_examples: 12000
   download_size: 21573770746
   dataset_size: 21702540415
+- config_name: sdxl
+  features:
+  - name: image
+    dtype: image
+  - name: depth
+    dtype: image
+  - name: mask
+    dtype: image
+  splits:
+  - name: train
+    num_bytes: 11662481187.0
+    num_examples: 6000
+  download_size: 11626921894
+  dataset_size: 11662481187.0
 configs:
-  - config_name: all
-    data_files:
-      - split: train
-        path: ["rendered/*.tar.gz", "generated/*.tar.gz"]
-  - config_name: blender
-    data_files:
-      - split: train
-        path: "rendered/*.tar.gz"
-  - config_name: sdxl
-    data_files:
-      - split: train
-        path: "generated/*.tar.gz"
+- config_name: all
+  data_files:
+  - split: train
+    path: all/train-*
+- config_name: blender
+  data_files:
+  - split: train
+    path: blender/train-*
+- config_name: sdxl
+  data_files:
+  - split: train
+    path: sdxl/train-*
 language:
 - en
 license: gpl-3.0

SynWBM.py

@@ -1,184 +0,0 @@
-# 
- # This file is part of the SynWBM distribution (https://huggingface.co/datasets/ABC-iRobotics/SynWBM).
- # Copyright (c) 2023 ABC-iRobotics.
- # 
- # This program is free software: you can redistribute it and/or modify  
- # it under the terms of the GNU General Public License as published by  
- # the Free Software Foundation, version 3.
- #
- # This program is distributed in the hope that it will be useful, but 
- # WITHOUT ANY WARRANTY; without even the implied warranty of 
- # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU 
- # General Public License for more details.
- #
- # You should have received a copy of the GNU General Public License 
- # along with this program. If not, see <http://www.gnu.org/licenses/>.
- #
-"""SynWBM dataset"""
-
-import sys
-if sys.version_info < (3, 9):
-    from typing import Sequence, Generator, Tuple
-else:
-    from collections.abc import Sequence, Generator
-    Tuple = tuple
-
-from typing import Optional, IO
-
-import datasets
-import itertools
-
-
-# ---- Constants ----
-
-_CITATION = """\
-COMING SOON
-"""
-
-_DESCRIPTION = """\
-A synthetic instance segmentation dataset for white button mushrooms (Agaricus bisporus).
-The dataset incorporates rendered and generated synthetic images for training mushroom segmentation models.
-"""
-
-_HOMEPAGE = "https://huggingface.co/datasets/ABC-iRobotics/SynWBM"
-
-_LICENSE = "GNU General Public License v3.0"
-
-_LATEST_VERSIONS = {
-    "all": "1.0.0",
-    "blender": "1.0.0",
-    "sdxl": "1.0.0",
-}
-
-BASE_URL = "https://huggingface.co/datasets/ABC-iRobotics/SynWBM/resolve/main/"
-
-
-
-# ---- SynWBM dataset Configs ----
-
-class SynWBMDatasetConfig(datasets.BuilderConfig):
-    """BuilderConfig for SynWBM dataset."""
-
-    def __init__(self, name: str, base_urls: Sequence[str], images_txt: str, version: Optional[str] = None, **kwargs):
-        _version = _LATEST_VERSIONS[name] if version is None else version
-        super(SynWBMDatasetConfig, self).__init__(version=datasets.Version(_version), name=name, **kwargs)
-        with open(images_txt, 'r') as f:
-            image_list = f.readlines()
-        img_urls = []
-        depth_urls = []
-        mask_urls = []
-        for base_url in base_urls:
-            img_urls.extend([base_url + image.strip() for image in image_list])
-            depth_urls.extend([BASE_URL + "depths/" + image.strip() for image in image_list])
-            mask_urls.extend([BASE_URL + "masks/" + image.strip() for image in image_list])
-
-        self._imgs_urls = img_urls
-        self._depth_urls = depth_urls
-        self._masks_urls = mask_urls
-
-
-    @property
-    def features(self):
-        return datasets.Features(
-            {
-                "image": datasets.Image(),
-                "depth": datasets.Image(),
-                "mask": datasets.Image(),
-            }
-        )
-    
-    @property
-    def supervised_keys(self):
-        return None
-
-
-
-# ---- SynWBM dataset Loader ----
-
-class SynWBMDataset(datasets.GeneratorBasedBuilder):
-    """SynWBM dataset."""
-
-    BUILDER_CONFIG_CLASS = SynWBMDatasetConfig
-    BUILDER_CONFIGS = [
-        SynWBMDatasetConfig(
-            name = "all",
-            description = "All images",
-            base_urls = [
-                BASE_URL + "rendered/",
-                BASE_URL + "generated/"
-            ],
-            images_txt = "images.txt"
-        ),
-        SynWBMDatasetConfig(
-            name = "blender",
-            description = "Synthetic images rendered using Blender",
-            base_urls = [
-                BASE_URL + "rendered/"
-            ],
-            images_txt = "images.txt"
-        ),
-        SynWBMDatasetConfig(
-            name = "sdxl",
-            description = "Synthetic images generated by Stable Diffusion XL",
-            base_urls = [
-                BASE_URL + "generated/"
-            ],
-            images_txt = "images.txt"
-        ),
-    ]
-    DEFAULT_WRITER_BATCH_SIZE = 10
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=self.config.features,
-            supervised_keys=self.config.supervised_keys,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-            version=self.config.version,
-        )
-
-    def _split_generators(self, dl_manager):
-        imgs_paths = dl_manager.download(self.config._imgs_urls)
-        depths_paths = dl_manager.download(self.config._depth_urls)
-        masks_paths = dl_manager.download(self.config._masks_urls)
-
-        imgs_gen = itertools.chain.from_iterable([dl_manager.iter_archive(path) for path in imgs_paths])
-        depths_gen = itertools.chain.from_iterable([dl_manager.iter_archive(path) for path in depths_paths])
-        masks_gen = itertools.chain.from_iterable([dl_manager.iter_archive(path) for path in masks_paths])
-        
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "images": imgs_gen,
-                    "depths": depths_gen,
-                    "masks": masks_gen,
-                },
-            ),
-        ]
-
-    def _generate_examples(
-        self,
-        images: Generator[Tuple[str,IO], None, None],
-        depths: Generator[Tuple[str,IO], None, None],
-        masks: Generator[Tuple[str,IO], None, None],
-    ):
-        for i, (img_info, depth_info, mask_info) in enumerate(zip(images, depths, masks)):
-            img_file_path, img_file_obj = img_info
-            depth_file_path, depth_file_obj = depth_info
-            mask_file_path, mask_file_obj = mask_info
-
-            img_bytes = img_file_obj.read()
-            depth_bytes = depth_file_obj.read()
-            mask_bytes = mask_file_obj.read()
-            img_file_obj.close()
-            depth_file_obj.close()
-            mask_file_obj.close()
-
-            yield i, {
-                "image": {"path": img_file_path, "bytes": img_bytes},
-                "depth": {"path": depth_file_path, "bytes": depth_bytes},
-                "mask": {"path": mask_file_path, "bytes": mask_bytes},
-            }

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