added fov zip file

.gitignore

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+.DS_Store

.vscode/settings.json

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+{
+    "python.formatting.provider": "black"
+}

README.md

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+---
+TODO: Add YAML tags here. Copy-paste the tags obtained with the online tagging app: https://huggingface.co/spaces/huggingface/datasets-tagging
+---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:**
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.

ark_example.py

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+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+This dataset contains example data for running through the multiplexed imaging data pipeline in
+Ark Analysis: https://github.com/angelolab/ark-analysis
+"""
+
+import json
+import os
+
+import datasets
+import pathlib
+import glob
+import tifffile
+
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {Ark Analysis Example Dataset},
+author={Angelo Lab},
+year={2022}
+}
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This dataset contains 11 Field of Views (FOVs), each with 22 channels. 
+"""
+
+_HOMEPAGE = "https://github.com/angelolab/ark-analysis"
+
+_LICENSE = "https://github.com/angelolab/ark-analysis/blob/main/LICENSE"
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URL_REPO = "https://huggingface.co/datasets/angelolab/ark_example/resolve/main/"
+
+
+_URLS = {"base_dataset": f"{_URL_REPO}/data/fovs.zip"}
+
+"""
+https://huggingface.co/docs/datasets/dataset_script
+https://huggingface.co/docs/datasets/share
+https://huggingface.co/datasets/allenai/wmt22_african/blob/main/wmt22_african.py
+https://huggingface.co/docs/datasets/repository_structure
+"""
+
+# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
+class ArkExample(datasets.GeneratorBasedBuilder):
+    """The Dataset consists of 12 FOVs"""
+
+    VERSION = datasets.Version("0.0.1")
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'base_dataset')
+    # data = datasets.load_dataset('my_dataset', 'dev_dataset')
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="base_dataset",
+            version=VERSION,
+            description="This dataset contains only the 12 FOVs.",
+        ),
+        datasets.BuilderConfig(
+            name="dev_dataset",
+            version=VERSION,
+            description="This dataset is a superset of the base_dataset, and contains intermediate data for all notebooks. \
+                Therefore you can start at any notebook with this dataset.",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "base_dataset"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+    def _info(self):
+        # TODO: This method specifies the datasets.DatasetInfo object which contains information and typings for the dataset
+        if (
+            self.config.name == "base_dataset"
+        ):  # This is the name of the configuration selected in BUILDER_CONFIGS above
+            features = datasets.Features(
+                {
+                    "fov": datasets.Sequence({"channel": datasets.Image()}),
+                }
+            )
+        else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
+            features = datasets.Features(
+                {
+                    "sentence": datasets.Value("string"),
+                    "option2": datasets.Value("string"),
+                    "second_domain_answer": datasets.Value("string")
+                    # These are the features of your dataset like images, labels ...
+                }
+            )
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
+            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
+            # supervised_keys=("sentence", "label"),
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        urls = _URLS[self.config.name]
+        data_dir = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name="BASE_DATASET",
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": pathlib.Path(data_dir) / "fovs"
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath: pathlib.Path):
+        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+
+        file_paths = list(filepath.rglob("*"))
+        
+        for fp in file_paths:
+            if fp.suffix in [".tiff", ".tif"]:
+                
+                image_data = tifffile.imread(fp, key=0)
+                if self.config.name == "base_dataset":
+                    yield fp.parent.stem, {
+                        "chan": image_data,
+                        "path": fp
+                    }
+        
+        # with open(filepath, encoding="utf-8") as f:
+        #     for key, row in enumerate(f):
+        #         data = json.loads(row)
+        #         if self.config.name == "first_domain":
+        #             # Yields examples as (key, example) tuples
+        #             yield key, {
+        #                 "sentence": data["sentence"],
+        #                 "option1": data["option1"],
+        #                 "answer": "" if split == "test" else data["answer"],
+        #             }
+        #         else:
+        #             yield key, {
+        #                 "sentence": data["sentence"],
+        #                 "option2": data["option2"],
+        #                 "second_domain_answer": ""
+        #                 if split == "test"
+        #                 else data["second_domain_answer"],
+        #             }

data/fovs.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:86e72fb01ea522ffe9e981d7b1f7077cf9f81ffd5f1a405071eb4d2752d0ef5d
+size 400238028