created the code file

signals.py

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+import csv
+import json
+import os
+from typing import List
+import datasets
+import logging
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {A great new dataset},
+author={huggingface, Inc.
+},
+year={2020}
+}
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This dataset contains traffic images from traffic signal cameras of singapore. The images are captured at 1.5 minute interval from 6 pm to 7 pm everyday for the month of January 2024.
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "https://beta.data.gov.sg/collections/354/view"
+
+# TODO: Add the licence for the dataset here if you can find it
+_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://github.com/Sayali-pingle/HuggingFace--Traffic-Image-Dataset/blob/main/camera_data.csv"
+_URLS = {
+    "train": _URL + "train-v1.1.json",
+    "dev": _URL + "dev-v1.1.json",
+}
+
+# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
+class TrafficImages(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    _URLS = _URLS
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "timestamp": datasets.Value("string"),
+                    "camera_id": datasets.Value("string"),
+                    "latitude": datasets.Value("float"),
+                    "longitude": datasets.Value("float"),
+                    "image_url": datasets.Value("string"),
+                    "image_metadata": datasets.Value("string")
+                }
+            ),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+    
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+      urls_to_download = self._URLS
+      downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+      return [
+          datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+          datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+      ]
+      
+    def _generate_examples(self, file_path):
+        # This method will yield examples from your dataset
+        start_date = datetime(2024, 1, 1, 18, 0, 0)
+        end_date = datetime(2024, 1, 31, 19, 0, 0)
+        interval_seconds = 240
+
+        date_time_strings = [
+            (current_date + timedelta(seconds=seconds)).strftime('%Y-%m-%dT%H:%M:%S+08:00')
+            for current_date in pd.date_range(start=start_date, end=end_date, freq='D')
+            for seconds in range(0, 3600, interval_seconds)
+        ]
+
+        url = 'https://api.data.gov.sg/v1/transport/traffic-images'
+        camera_data = []
+
+        for date_time in date_time_strings:
+            params = {'date_time': date_time}
+            response = requests.get(url, params=params)
+
+            if response.status_code == 200:
+                data = response.json()
+                camera_data.extend([
+                    {
+                        'timestamp': item['timestamp'],
+                        'camera_id': camera['camera_id'],
+                        'latitude': camera['location']['latitude'],
+                        'longitude': camera['location']['longitude'],
+                        'image_url': camera['image'],
+                        'image_metadata': camera['image_metadata']
+                    }
+                    for item in data['items']
+                    for camera in item['cameras']
+                ])
+            else:
+                print(f"Error: {response.status_code}")
+
+        for idx, example in enumerate(camera_data):
+            yield idx, {
+                "timestamp": example["timestamp"],
+                "camera_id": example["camera_id"],
+                "latitude": example["latitude"],
+                "longitude": example["longitude"],
+                "image_url": example["image_url"],
+                "image_metadata": example["image_metadata"]
+            }
+