added datasets for nb2

ark_example.py

@@ -17,15 +17,10 @@ This dataset contains example data for running through the multiplexed imaging d
 Ark Analysis: https://github.com/angelolab/ark-analysis
 """
 
-import json
 import os
-
 import datasets
 import pathlib
 import glob
-import tifffile
-import xarray as xr
-import numpy as np
 
 # Find for instance the citation on arxiv or on the dataset repo/website
 _CITATION = """\
@@ -52,7 +47,20 @@ _LICENSE = "https://github.com/angelolab/ark-analysis/blob/main/LICENSE"
 _URL_REPO = "https://huggingface.co/datasets/angelolab/ark_example/resolve/main"
 
 
-_URLS = {"base_dataset": f"{_URL_REPO}/data/input_data.zip"}
+_URLS = {
+    "input_data": f"{_URL_REPO}/data/input_data.zip",
+    "segmentation/cell_table": f"{_URL_REPO}/data/segmentation/cell_table.zip",
+    "segmentation/deepcell_output": f"{_URL_REPO}/data/segmentation/deepcell_output.zip",
+}
+
+_URL_DATASET_CONFIGS = {
+    "nb1": {"input_data": _URLS["input_data"]},
+    "nb2": {
+        "input_data": _URLS["input_data"],
+        "segmentation/cell_table": _URLS["segmentation/cell_table"],
+        "segmentation/deepcell_output": _URLS["segmentation/deepcell_output"],
+    },
+}
 
 """
 Dataset Fov renaming:
@@ -74,7 +82,7 @@ TMA24_R9C1 -> fov10
 class ArkExample(datasets.GeneratorBasedBuilder):
     """The Dataset consists of 11 FOVs"""
 
-    VERSION = datasets.Version("0.0.1")
+    VERSION = datasets.Version("0.0.2")
 
     # This is an example of a dataset with multiple configurations.
     # If you don't want/need to define several sub-sets in your dataset,
@@ -85,45 +93,30 @@ class ArkExample(datasets.GeneratorBasedBuilder):
     # 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')
+    # data = datasets.load_dataset('my_dataset', 'nb1')
+    # data = datasets.load_dataset('my_dataset', 'nb2')
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
-            name="base_dataset",
+            name="nb1",
             version=VERSION,
-            description="This dataset contains only the 12 FOVs.",
+            description="This dataset contains only the 12 FOVs, and their 22 channels.",
         ),
         datasets.BuilderConfig(
-            name="dev_dataset",
+            name="nb2",
             version=VERSION,
-            description="This dataset is a superset of the base_dataset, and contains intermediate data for all notebooks. \
+            description="This dataset is a superset of the nb1 and contains data from notebook 1 in order to start with notebook 2. \
                 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):
         # This is the name of the configuration selected in BUILDER_CONFIGS above
-        if self.config.name == "base_dataset":
-            features = datasets.Features(
-                {
-                    "Channel Data": datasets.Sequence(datasets.Image()),
-                    "Channel Names": datasets.Sequence(datasets.Value("string")),
-                    "Data Path": datasets.Value("string"),
-                }
-            )
-        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 ...
-                }
-            )
+        if self.config.name == "nb1":
+            features = datasets.Features({"Data Path": datasets.Value("string")})
+        elif self.config.name == "nb2":
+            features = datasets.Features({"Data Path": datasets.Value("string")})
+        else:
+            features = datasets.Features({"Data Path": datasets.Value("string")})
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,
@@ -147,12 +140,12 @@ class ArkExample(datasets.GeneratorBasedBuilder):
         # 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]
+        urls = _URL_DATASET_CONFIGS[self.config.name]
         data_dir = dl_manager.download_and_extract(urls)
 
         return [
             datasets.SplitGenerator(
-                name="base_dataset",
+                name=self.config.name,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={"filepath": pathlib.Path(data_dir)},
             ),
@@ -167,24 +160,10 @@ class ArkExample(datasets.GeneratorBasedBuilder):
         # Loop over all the TMAs
         for fp in file_paths:
 
-            # Get the TMA FOV Name
-            fov_name = fp.stem
-
-            # Get all channels per TMA FOV
-            channel_paths = fp.glob("*.tiff")
-
-            chan_data = []
-            chan_names = []
-            for chan in channel_paths:
-                chan_name = chan.stem
-                chan_image: np.ndarray = tifffile.imread(chan)
-
-                chan_data.append(chan_image)
-                chan_names.append(chan_name)
+            # Get the file Name
+            fn = fp.stem
 
-            if self.config.name == "base_dataset":
-                yield fov_name, {
-                    "Channel Data": chan_data,
-                    "Channel Names": chan_names,
+            if self.config.name == "fovs":
+                yield fn, {
                     "Data Path": filepath.as_posix(),
                 }

data/segmentation/cell_table.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a537cf42788feb05b7efe91c4f6867930b99a029ae5a68b374d09c2cca0a34c4
+size 10366535

data/segmentation/deepcell_output.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:06d50ac056dd766909c4d66e7de3305e18e7dfa4326692395353fea30cd2a8d0
+size 916593