…On the other hand, G5 has images of crosswalks during the day or at night with multiple cars and license plates (LPs).
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A high-quality, balanced dataset of 330,000 images featuring various types of Chinese license plates. The dataset is generated using Generative Adversarial Networks (GANs), ensuring excellent image quality and a balanced distribution of different license plate types. This dataset is perfect for training and evaluating license plate recognition models. Note: In order to ensure the balance of the characters, there may be some license plate numbers that do not conform to common sense (for example, all letters), but this phenomenon does not affect the training
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The Chinese City Parking Dataset (CCPD) is a dataset for license plate detection and recognition. It contains over 250k unique car images, with license plate location annotations.
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The Iranis Dataset is a Large-scale dataset of Farsi license plate characters containing a large-scale dataset with more than 83,000 images of Farsi numbers and letters collected from real-world license plate images captured by various cameras.
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This dataset includes 4,500 fully annotated images (over 30,000 license plate characters) from 150 vehicles in real-world scenarios where both the vehicle and the camera (inside another vehicle) are moving We collected 1,500 images with each camera, divided as follows: - 900 of cars with gray license plates; - 300 of cars with red license plates; - 300 of motorcycles with gray license plates. in a text file: the camera in which the image was taken, the vehicle’s position and information such as type (car or motorcycle), manufacturer, model and year; the identification and position of the license plate, as well as the position of its characters.
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CD-HARD comprises 102 images featuring vehicles with oblique license plates sourced from the Cars dataset. The dataset was presented in the 'License Plate Detection and Recognition in Unconstrained Scenarios' research paper.
The application-oriented license plate (AOLP) benchmark database has 2049 images of Taiwan license plates. The background are really cluttered, with road sign and multiple plates in one image.
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…The dataset was presented in the research paper titled "A Robust Attentional Framework for License Plate Recognition in the Wild."
…contains more than three hours of high-resolution videos, with accurate information about the make, model, color and year of nearly 3,000 vehicles, in addition to the position and identification of their license plates.
The ChineseLP dataset contains 411 vehicle images (mostly of passenger cars) with Chinese license plates (LPs).
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This dataset aims at evaluating the License Plate Character Segmentation (LPCS) problem. The experimental results of the paper Benchmark for License Plate Character Segmentation were obtained using a dataset providing 101 on-track vehicles captured during the day.
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…download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai This dataset is an extremely challenging set of over 20,000+ original Number plate Device used : Captured using mobile phones in 2020-2022 Usage : Number plate detection, ANPR, Number plate recognition, Self driving system, etc.
This dataset is an extremely challenging set of over 20,000+ original Number plate images captured and crowdsourced from over 700+ urban and rural areas, where each image is manually reviewed and verified cities and villages across India - Diversity : Various lighting conditions like day, night, varied distances, view points etc. - Device used : Captured using mobile phones in 2020-2022 - Usage : Number plate detection, ANPR, Number plate recognition, Self driving system, etc.
…An important feature of the proposed dataset is that it has images of two different license plate (LP) layouts: Brazilian and Mercosur (to maintain consistency with existing works, we refer to “Brazilian
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…It has 2,409 annotated objects divided into five classes: transmission tower, insulator, spacer, tower plate, and Stockbridge damper, which vary in size (resolution), orientation, illumination, angulation It has 2,409 annotated objects divided into five classes: transmission tower, insulator, spacer, tower plate, and Stockbridge damper, which vary in size (resolution), orientation, illumination, angulation | Average Precision | |--------------------|-----------------| | Transmission tower | 0.900 | | Insulator | 0.894 | | Spacer | 0.856 | | Tower plate
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Street View House Numbers (SVHN) is a digit classification benchmark dataset that contains 600,000 32×32 RGB images of printed digits (from 0 to 9) cropped from pictures of house number plates.
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5 domains: synthetic domain, document domain, street view domain, handwritten domain, and car license domain over five million images
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VideoLQ consists of videos downloaded from various video hosting sites such as Flickr and YouTube, with a Creative Common license.
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SA-1B consists of 11M diverse, high resolution, licensed, and privacy protecting images and 1.1B high-quality segmentation masks.
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…localized narratives (synchronized voice, mouse trace, and text caption) 66,391,027 point-level annotations on 5,827 classes 61,404,966 image-level labels on 20,638 classes Images are under a CC BY 2.0 license , annotations under CC BY 4.0 license.
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…QMNIST is licensed under the BSD-style license.
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…Images were licensed from Getty Images so that researchers can use the data set to support their work.
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…It is sourced from Wikimedia Commons, a crowdsourced and open-licensed collection of 50M images.
…ZOD is released under the permissive CC BY-SA 4.0 license, allowing for both commercial and non-commercial use. For more information about the license, see here.
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…All videos have been annotated by licensed sewer inspectors following the Danish sewer inspection standard, Fotomanualen.
…Due to license issue, we will not release the other 13K images used in training.
…The data is composed of radiometrically and geometrically corrected Top-Of-Atmosphere (TOA) reflectances for the RED and NIR spectral bands at 300m and 100m resolution in Plate Carrée projection.
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…Device used : Captured using mobile phones in 2021-2022 Usage : Vehicle detection, Autorickshaw detection, Self driving, Indian vehicles, Number Plate detection, etc.
…Device used : Captured using mobile phones in 2020-2021 Usage : Indian food classification, Dish classification, Food plate detection, etc.
…The dataset is licensed under a CC-BY 4.0 license.
…Dataset Description MatSynth is a new large-scale dataset comprising over 4,000 ultra-high resolution Physically Based Rendering (PBR) materials, all released under permissive licensing. Each material in the dataset comes with rich metadata, including information on its origin, licensing details, category, tags, creation method, and, when available, descriptions and physical size. Source Data The MatSynth dataset is the result of an extensively collection of data from multiple online sources operating under the CC0 and CC-BY licensing framework. Materials under CC0 license were collected from AmbientCG, CGBookCase, PolyHeaven, ShateTexture, and TextureCan. The dataset also includes limited set of materials from the artist Julio Sillet, distributed under CC-BY license.
…The total 2010 images are collected from the website of Flickr with the license of all creative commons. Pixel-level ground truths are manually annotated by 40 subjects.
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…Test U-Net sh cd SVWB_Unet sh test.sh Train U-Net sh cd SVWB_Unet sh train.sh Dataset License <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0 /">Creative Commons Attribution-NonCommercial 4.0 International License</a>
…It is released under creative commons (CC BY-NC 4.0) license to promote research in open set logo detection. The dataset can be used only for research purposes.
…Methods to combine spatial and temporal information with respect to automated dust detection using satellite images and ground climate data License As described here, ``` You are free to: Share — copy This license is acceptable for Free Cultural Works. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
YFCC100M is a that dataset contains a total of 100 million media objects, of which approximately 99.2 million are photos and 0.8 million are videos, all of which carry a Creative Commons license.
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…Only images under permissive licenses were collected.
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…Briefly, cells were seeded in 12-well culture plates ($20 \times 10^3$ cells per well) and grown to form a monolayer with 85\% or more confluency.
…WikiScenes is derived from the massive public catalog of freely-licensed crowdsourced data in the Wikimedia Commons project, which contains a large variety of images with captions and other metadata.
…Licensing of images and data All images and data derived from observations made at LCO facilities are made available for scientific or educational use, subject to the Creative Commons license BY-CC 2.0
…One set of images used in collecting the anthology originated from Flickr, under Creative Commons Licenses. The Flickr images' authors and copyright information and usage are documented in the Flickr imageset license spreadsheet. The second source of images came from a Search and Rescue (SAR) scenario.
…The dataset is released publicly under a Creative Commons BY-NC-ND 4.0 license and can be accessed through the project repository.
…project: IXI – Information eXtraction from Images (EPSRC GR/S21533/02) The images in NIFTI format can be downloaded from here: This data is made available under the Creative Commons CC BY-SA 3.0 license
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…Please note the original creators of the individual 3D scenes themselves (individual license files can be found in the individual .zip archives in the dataset): Bulldozer by "Heinzelnisse" (CC-BY-NC):
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…Terms and Conditions This work is licensed under a Creative Commons Attribution 4.0 International License. Both academic and commercial applications are allowed.
…The whole complete data set is now available in the CAP database with public domain license.
…License This dataset is published under the same MIT license as CIFAR-10: Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files
…It will be made publicly available for non-commercial, academic, and research purposes upon request and execution of a no-cost license agreement.