dataset: versioning and info

dataset_infos.json

@@ -1 +1,98 @@
-{"default": {"description": "\n    This dataset contains photos of rivers on which there may be waste. The waste items are annotated \n    through bounding boxes, and are assigned to one of the 4 following categories: plastic bottle, plastic bag, \n    another plastic waste, or non-plastic waste. Note that some photos may not contain any waste.\n", "citation": "", "homepage": "", "license": "", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "litter": {"feature": {"label": {"num_classes": 3, "names": ["PLASTIC_BAG", "PLASTIC_BOTTLE", "OTHER_PLASTIC_WASTE"], "names_file": null, "id": null, "_type": "ClassLabel"}, "bbox": {"feature": {"dtype": "float32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "litter_challenge_test", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 59176802, "num_examples": 50, "dataset_name": "litter_challenge_test"}, "test": {"name": "test", "num_bytes": 8336276, "num_examples": 7, "dataset_name": "litter_challenge_test"}, "validation": {"name": "validation", "num_bytes": 5948908, "num_examples": 6, "dataset_name": "litter_challenge_test"}}, "download_checksums": {"https://storage.googleapis.com/kili-datasets-public/plastic-in-river/train/images.tar.gz": {"num_bytes": 15297527, "checksum": "8667f292b829a9979d0bef6e9acc9f8981c2a2f8e669c7014f739f107329e4ad"}, "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/train/annotations.tar.gz": {"num_bytes": 4177, "checksum": "dd3856450d6d573a52e25215cc642bc5bca3804985c055661ff6cef7c581789f"}, "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/validation/images.tar.gz": {"num_bytes": 1461341, "checksum": "6074f2406d09897787e3c8e4814f63349fe9c709f63620bd3bab0619884af03a"}, "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/validation/annotations.tar.gz": {"num_bytes": 501, "checksum": "29c985cdf46e6c592a3899185e956ca11eee64c61660e09f9cdb2ed2148b68ea"}, "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/test/images.tar.gz": {"num_bytes": 2153491, "checksum": "6a69678d3723dbe8fea227526229e43969e55b3134a5927c8bf0279cc26c0edb"}, "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/test/annotations.tar.gz": {"num_bytes": 853, "checksum": "83a90a11bcc598080e54c0a300ec5c0eae970c78bc1638d2de822e0bb61c7884"}}, "download_size": 18917890, "post_processing_size": null, "dataset_size": 73461986, "size_in_bytes": 92379876}}
+{
+  "default": {
+    "description": "\n    This dataset contains photos of rivers on which there may be waste. The waste items are annotated\n    through bounding boxes, and are assigned to one of the 4 following categories: plastic bottle, plastic bag,\n    another plastic waste, or non-plastic waste. Note that some photos may not contain any waste.\n",
+    "citation": "",
+    "homepage": "",
+    "license": "",
+    "features": {
+      "image": { "decode": true, "id": null, "_type": "Image" },
+      "litter": {
+        "feature": {
+          "label": {
+            "num_classes": 4,
+            "names": [
+              "PLASTIC_BAG",
+              "PLASTIC_BOTTLE",
+              "OTHER_PLASTIC_WASTE",
+              "NOT_PLASTIC_WASTE"
+            ],
+            "names_file": null,
+            "id": null,
+            "_type": "ClassLabel"
+          },
+          "bbox": {
+            "feature": { "dtype": "float32", "id": null, "_type": "Value" },
+            "length": 4,
+            "id": null,
+            "_type": "Sequence"
+          }
+        },
+        "length": -1,
+        "id": null,
+        "_type": "Sequence"
+      }
+    },
+    "post_processed": null,
+    "supervised_keys": null,
+    "task_templates": null,
+    "builder_name": "plastic_in_river",
+    "config_name": "default",
+    "version": {
+      "version_str": "1.0.0",
+      "description": null,
+      "major": 1,
+      "minor": 0,
+      "patch": 0
+    },
+    "splits": {
+      "train": {
+        "name": "train",
+        "num_bytes": 1382005709,
+        "num_examples": 1186,
+        "dataset_name": "plastic_in_river"
+      },
+      "test": {
+        "name": "test",
+        "num_bytes": 174268213,
+        "num_examples": 149,
+        "dataset_name": "plastic_in_river"
+      },
+      "validation": {
+        "name": "validation",
+        "num_bytes": 170939935,
+        "num_examples": 148,
+        "dataset_name": "plastic_in_river"
+      }
+    },
+    "download_checksums": {
+      "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/v1.0.0/train/images.tar.gz": {
+        "num_bytes": 350379542,
+        "checksum": "38fcc632c2c158dc746933e385aecca9f60dac9288da6676f6594b3b585fc025"
+      },
+      "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/v1.0.0/train/annotations.tar.gz": {
+        "num_bytes": 180827,
+        "checksum": "70015049c893a3bb2e1bd0ff6a5926250908221f236dc2b75d54833e84aee4e0"
+      },
+      "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/v1.0.0/validation/images.tar.gz": {
+        "num_bytes": 43885822,
+        "checksum": "fd297e2c42a6b8480b9445522b69fb6daaffaf169d5e6735e1925a12ba4c07d6"
+      },
+      "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/v1.0.0/validation/annotations.tar.gz": {
+        "num_bytes": 15474,
+        "checksum": "6ff36a120ac0759426800557de7751317ce6f2c2b02857f0c53527f640747bf5"
+      },
+      "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/v1.0.0/test/images.tar.gz": {
+        "num_bytes": 44563692,
+        "checksum": "b869224b3204f4d2cab176a32f903b9afdb77005f9d15e1844c6bf8484b4bf8f"
+      },
+      "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/v1.0.0/test/annotations.tar.gz": {
+        "num_bytes": 15155,
+        "checksum": "e30057eac9f05c4759baab31830f1752fe42ef51680523d17df02a44183ed274"
+      }
+    },
+    "download_size": 439040512,
+    "post_processing_size": null,
+    "dataset_size": 1727213857,
+    "size_in_bytes": 2166254369
+  }
+}

plastic_in_river.py

@@ -16,10 +16,7 @@ _HOMEPAGE = ""
 
 _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 = "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/"
+_URL = "https://storage.googleapis.com/kili-datasets-public/plastic-in-river/<VERSION>/"
 
 _URLS = {
     "train_images": f"{_URL}train/images.tar.gz",
@@ -55,7 +52,9 @@ class PlasticInRiver(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download(_URLS)
+        urls = {k: v.replace("<VERSION>", f"v{str(self.VERSION)}") for k, v in _URLS.items()}
+
+        downloaded_files = dl_manager.download(urls)
 
         return [
             datasets.SplitGenerator(