The Natural-Color Dataset (NCD) is an image colorization dataset where images are true to their colors. For example, a carrot will have an orange color in most images. Bananas will be either greenish or yellowish. It contains 723 images from the internet distributed in 20 categories. Each image has an object and a white background.
MIT Licensehttps://opensource.org/licenses/MIT
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burkelibbey/colors dataset hosted on Hugging Face and contributed by the HF Datasets community
This dataset was created by Jamil
Released under Data files © Original Authors
Satellite-derived Ocean Color Data sets from historical and currently operational NASA and International Satellite missions including the NASA Coastal Zone Color Scanner (CZCS) (1978 - 1986), NASDA's Ocean Color Temperature Scanner (OCTS) (1996 - 1997), NASA/GeoEYE Sea-viewing Wide Field-of-view Sensor (SeaWiFS) (1997 - 2010), NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua spacecraft (2000 - present) and ESA's medium-spectral resolution, imaging spectrometer (MERIS) (2002 - present). Level-1A Data Products Level-1A products contain the raw radiance counts from all bands as well as spacecraft and instrument telemetry. Calibration and navigation data, and instrument and selected spacecraft telemetry are also included. Level-1A data are used as input for geolocation, calibration, and processing. Ocean Level-2 Data Products Each Level-2 product is generated from a corresponding Level-1A product.The main data contents of the product are the geophysical values for each pixel,derived from the Level-1A raw radiance counts by applying the sensor calibration, atmospheric corrections, and bio-optical algorithms. Each Level-2 product corresponds exactly in geographical coverage (scan-line and pixel extent) to that of its parent Level-1A product and is stored in one physical HDFfile. Ocean Level-3 Binned Data Products Level-3 binned data products consist of the accumulated data for all Level-2 data corresponding to a period of one day, 8 days, a calendar month, or a calendar year. Each Level-3 binned data product is stored in one or more HDF files. Each multi-file product includes a main file containing all product-level metadata and data for each bin that are common to all the binned geophysical parameters, and multiple subordinate files, each of which contains data of one binned geophysical parameter for all bins. Subordinate files must be read in conjunction with the associated main file. Ocean Level-3 Standard Mapped Image Products The Level-3 standard mapped image (SMI) products are image representations of binned data products generated from SeaWiFS, MODIS, OCTS or CZCS data. The data in each SMI product represents an image of the parameter specified by the global attribute Parameter. This object is a two-dimensional array of an Equidistant Cylindrical (also known as Platte Carre) projection of the globe. The values can be stored as bytes, 2-byte integers, or 4- byte floats. The first two are scaled real values and may be converted projected to geophysical values using the global attributes Scaling, Scaling Equation, Base, Slope, and Intercept. The standard SMI products are generated from binned data products, one for each of the following geophysical parameters: chlorophyll a concentration, angstrom coefficient, normalized water-leaving radiance at each visible wavelength, aerosol optical thickness, epsilon, and diffuse attenuation coefficient at 490 nm. For MODIS, products are generated for sea surface temperature (SST), 4 micron SST (SST4) and nighttime SST (NSST). Thus, each SMI product represents data binned over the period covered by the parent product. The arithmetic mean is used in each case to obtain the values for the SMI grid points from the binned data products. Each SMI product contains one image of a geophysical parameter and is stored in one physical HDF file.
The color FERET database is a dataset for face recognition. It contains 11,338 color images of size 512×768 pixels captured in a semi-controlled environment with 13 different poses from 994 subjects.
This dataset was created by Vineeth Vadlapalli
Released under Data files © Original Authors
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textures-color-1k
Dataset Summary
The textures-color-1k dataset is an image dataset of 1000+ color image textures in 512x512 resolution with associated text descriptions. The dataset was created for training/fine-tuning diffusion models on texture generation tasks. It contains a combination of CC0 procedural and photoscanned PBR materials from ambientCG.
Languages
The text descriptions are in English, and created by joining the tags of each material… See the full description on the dataset page: https://huggingface.co/datasets/dream-textures/textures-color-1k.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
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Dataset Details
Dataset Description
A dataset that contains the color names and their relations with their respective RGB Values with over 40k rows.
Repository: Generation-of-Colors-using-BiLSTMs Citation:
@misc{sinha2023generation, title={Generation Of Colors using Bidirectional Long Short Term Memory Networks}, author={A. Sinha}, year={2023}, eprint={2311.06542}, archivePrefix={arXiv}, primaryClass={cs.CV}
The Aerosol Robotic Network (AERONET), developed to sustain atmospheric studies at various scales with measurements from worldwide distributed autonomous sun-photometers has been extended to support marine applications. This new network component called AERONET – Ocean Color (AERONET-OC), provides the additional capability of measuring the radiance emerging from the sea (i.e., water-leaving radiance) with modified sun-photometers installed on offshore platforms like lighthouses, oceanographic and oil towers. AERONET-OC is instrumental in satellite ocean color validation activities through standardized measurements a) performed at different sites with a single measuring system and protocol, b) calibrated with an identical reference source and method, and c) processed with the same code.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
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This dataset was created by p190068 Usman Manzoor
Released under Apache 2.0
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Pyla-Koutsopetria Archaeological Project II: Geophysics and Excavation" data publication.
The eight color asteroid survey provides reflection spectra for minor planets using eight filter passbands. This dataset includes the primary data obtained for 589 minor planets. The mean values for each minor planet included in the survey, the response curves for the filters, and the values determined for standard stars, are included in other related datasets. The wavelength range covered is from .33 to 1.04 micrometers.
Pedestrian Color Naming (PCN) is a dataset for pedestrian color naming, which contains 14,213 images, each of which hand-labeled with color label for each pixel. All images in the PCN dataset are obtained from the Market- 1501 dataset.
The historical color image dataset is collected for the task of automatically estimating the age of historical color photos. Each image is annotated with its associated decade, where five decades from the 1930s to 1970s are considered. There are 265 images for each category
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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This README file was generated on 2023-09-22 by Rachel C. Thayer.
GENERAL INFORMATION
SHARING/ACCESS INFORMATION
U.S. Government Workshttps://www.usa.gov/government-works
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The eight color asteroid survey provides reflection spectra for minor planets using eight filter passbands. A system of standard stars was established to aid in the calibration of the ECAS photometric system. This dataset includes the standard magnitudes and color indices for the eight-color standard stars which were then used to calibrate the eight color asteroid survey data. The wavelength range covered is from .33 to 1.04 micrometers.
MIT Licensehttps://opensource.org/licenses/MIT
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Color Names dataset
A simple train and test dataset containing ~40000 rows of colour names and their hex codes.
Credits
This dataset is processed and cleaned from meodai/color-names on GitHub.
License
This dataset is licensed under the MIT license.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Petra Great Temple Excavations" data publication.
Data consists of worldwide ocean water color/transparency derived from NODC's ocean station data file from April 1901 to December 1985. The NODC Environmental Information Bulletin 87-1 (EIB 87-1, March 1987) contains a complete explanation of the data and their format.
This level 3 product includes ocean color and satellite ocean biology data produced or collected under EOSDIS. This dataset may be used for studying the biology and hydrology of coastal zones, changes in the diversity and geographical distribution of coastal marine habitats, biogeochemical fluxes and their influence in Earth's oceans …
The Natural-Color Dataset (NCD) is an image colorization dataset where images are true to their colors. For example, a carrot will have an orange color in most images. Bananas will be either greenish or yellowish. It contains 723 images from the internet distributed in 20 categories. Each image has an object and a white background.