{"url":"/dataset/prophesee-gen4-dataset","name":"Prophesee GEN4 Dataset","full_name":"Prophesee 1 Megapixel Automotive Detection Dataset","description_markdown":"The dataset is split between train, test and val folders. \r\n\r\nFiles consist of 60 seconds recordings that were cut from longer recording sessions. Cuts from a single recording session are all in the same training split.\r\n\r\nEach dat file is a binary file in which events are encoded using 4 bytes (unsigned int32) for the timestamps and 4 bytes (unsigned int32) for the data, encoding is little-endian ordering.\r\n\r\nThe data is composed of 14 bits for the x position, 14 bits for the y position and 1 bit for the polarity (encoded as -1/1).\r\n\r\nAnnotations use the numpy format and can simply be loaded form python using numpy boxes = np.load(path)\r\n\r\nBoxes have the following fields:\r\n\r\n* x abscissa of the top left corner in pixels\r\n* y ordinate of the top left corner in pixels\r\n* w width of the boxes in pixel\r\n* h height of the boxes in pixel\r\n* ts timestamp of the box in the sequence in microseconds\r\n* class_id 0 for pedestrians, 1 for two wheelers, 2 for cars, 3 for trucks, 4 for buses, 5 for traffic signs, 6 for traffic lights","description_withheld":null,"homepage":"https://www.prophesee.ai/2020/11/24/automotive-megapixel-event-based-dataset/","introduced_date":"2020-09-28","introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-to-detect-objects-with-a-1-megapixel","title":"Learning to Detect Objects with a 1 Megapixel Event Camera","first_author":"Etienne Perot","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Point cloud","url":"/datasets/modality/point-cloud"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Prophesee GEN4 Dataset"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}