Curious about applying augmentat

Curious about applying augmentation to computer vision datasets? 2017, Inria Aerial Image Labeling (inria.fr) Slovenia Land Cover Classification (Sinergise, Feb 2019) Draper Satellite Image Chronology (Draper, Jun 2016) It is now read-only. 2021. Please feel free to, Talk Title:"Microengineered tissues for regenerative medicine and organs-on-a-chip applications", IEEE CAS Charles Desoer Life Science Systems Student Attendance Grant, Assistive, Rehabilitation, and Quality of Life Technologies, Bio-inspired and Neuromorphic Circuits and Systems, Biofeedback, Electrical Stimulation, and Closed-Loop Systems, Biomedical Imaging Technologies & Image Processing, Innovative Circuits for Medical Applications, Medical Information Systems and Bioinformatics, Wireless and Energy Harvesting/Scavenging Technology. ), Paper: Yang & Newsam 2010, SEN12MS-CR & SEN12MS-CR-TS (TUM, Jun 2020) ), Paper: Mohajerani et al. ), COCO data format, baseline models, Paper: Christie et al. Intelinair, CVPR, Jan 2020) of provided building footprints (22,553), RGB UAV imagery (4cm res., 7 areas in 3 Carribbean countries), SpaceNet 5: Automated Road Network Extraction & Route Travel Time Estimation (CosmiQ Works, Maxar, Intel, AWS, Sep 2019) ), multiple AOIs in Tonga, NIST DSE Plant Identification with NEON Remote Sensing Data (inria.fr, Oct 2017) 10 land cover categories from industrial to permanent crop, 27k 64x64 pixel chips, 3/16 band Sentinel-2 satellite imagery (10m res. A multi-modal and mono-temporal data set for cloud removal. 45 scene categories from airplane to wetland, 31,500 images (700 per category, 256x256 px), image chips taken from Google Earth (rich image variations in resolution, angle, geography all over the world), Download Link, Paper: Cheng et al. 2020. Weekly Planetscope time-series (3m res.) 1980 image chips of 256 x 256 pixels in V1.0 spanning 66 tiles of Sentinel-2. So2Sat LCZ42 (TUM Munich & DLR, Aug 2018) Visdrone-DET training split comprises 6471 images. Open Cities AI Challenge (GFDRR, Mar 2020) . 20 land cover categories by fusing three data sources: Multispectral LiDAR, Hyperspectral (1m), RGB imagery (0.05m res. Dedicated to the free and open sharing of raw magnetic resonance imaging (MRI) datasets.. It is designed to promote the integration of vision and drones. ), LiDAR point cloud and canopy height model, NOAA Fisheries Steller Sea Lion Population Count (NOAA, Jun 2017) : (Common Objects in Context) is a large-scale dataset object detection, segmentation, and captioning dataset. 21 land cover categories from agricultural to parkinglot, 100 chips per class, aerial imagery (0.30m res. ), SpaceNet Challenge Asset Library. 2018, Open AI Challenge: Aerial Imagery of South Pacific Islands (WeRobotics & Worldbank, May 2018) Hub users may have access to a variety of publicly available datasets. Papers With Code is a free resource with all data licensed under, An Evaluation of Trajectory Prediction Approaches and Notes on the TrajNet Benchmark. IEEE Data Fusion Contest 2019 (IEEE, Mar 2019) SkyScapes: Urban infrastructure & lane markings (DLR, Nov 2019) Multiple landcover labels per chip based on CORINE Land Cover (CLC) 2018, 590,326 chips from Sentinel-2 L2A scenes (125 Sentinel-2 tiles from 10 European countries, 2017/2018), 66 GB archive, Paper: Sumbul et al. 7 categories (cloud, cloud shadows, cloud shadows over water, water etc. ), DSM/DTM, 3 cities, SpaceNet Challenge Asset Library, DSTL Satellite Imagery Feature Detection Challenge (Dstl, Feb 2017) Aircraft bounding boxes, 103 images of worlwide airports (Pleiades, 0.5m res., 2560px). res) timeseries for 2 years, 100 locations around the globe, for building footprint evolution & address propagation. are present. label: tensor representing the object detected. Tools. Local climate zone classification, 17 categories (10 urban e.g. Aerial imagery (0.13 m res.) 2019 Outcome Part A: Kunwar et al. 2017, RESISC45 (Northwestern Polytechnical University NWPU, Mar 2017) Paper: Shermeyer et al. ), covering cities in 30 countries, Paper: Helber et al. : Explore datasets by size, category, modality (including X-ray, Ultrasound, Whole Slide Images, CT Scans, ECGs), and more.

5987 image chips (Google Earth), 7 landcover categories, 166768 labels, 3 cities in China. A ChemImage Company - 2022 Innotescus, LLC. Highly accurate street lane markings (12 categories e.g. BioCAS 2015 will comprise an excellent combination of invited talks and tutorials from pioneers in the field as well as peer-reviewed special and regular sessions plus live demonstrations. Manual labeling & active learning, Paper: Baetens et al. Visdrone-DET testing split comprises 548 images. Airbus Oil Storage Detection (Airbus, Mar 2021) ), Paper: Hughes, J.M. Semi-supervised semantic segmentation, 19 cities and surroundings with multi-sensor tiles (VHR Aerial imagery 50cm res., Elevation model) & per pixel labels (contains landcover / landuse classes from UrbanAtlas 2012), Data. Paper: Azimi et al. Newest datasets at the top of each category (Instance segmentation, object detection, semantic segmentation, scene classification, other). The benchmarks section lists all benchmarks using a given dataset or any of Version 1.0 of the dataset that contains data across Africa, (20% of the global dataset). This repository has been archived by the owner. SpaceNet: Multi-Sensor All-Weather Mapping (CosmiQ Works, Capella Space, Maxar, AWS, Intel, Feb 2020) 2017, Planet: Understanding the Amazon from Space (Planet, Jul 2017) Microsoft BuildingFootprints Canada & USA & Uganda/Tanzania & Australia (Microsoft, Mar 2019) Paper: Castillo-Navarro et al., 2021, LandCoverNet: A Global Land Cover Classification Training Dataset (Alemohammad S.H., et al., Jul 2020) Paper: SEN12MS-CR - Ebel et al. road-flooded, ). 175 globally distributed aois. BigEarthNet: Large-Scale Sentinel-2 Benchmark (TU Berlin, Jan 2019) satellite-image-deepl-learning & add Spacenet Round 6 - Multi-Sensor All Weather Mapping, Recent additions and ongoing competitions. Bi-cubicly resampled to same number of pixels in each image to counter courser native resolution with higher off-nadir angles, Paper: Weir et al. The Street View House Numbers (SVHN) Dataset. Includes clear, cloud and cloud-shadow classes. )., ca. 17k aerial photos, 13k cactus, 4k non-actus, Kaggle kernels, Paper: Lpez-Jimnez et al. 6 urban land cover classes, raster mask labels, 4-band RGB-IR aerial imagery (0.05m res.)

2020, IEEE Data Fusion Contest 2022 (IEEE GRSS, Universit Bretagne-Sud, ONERA, ESA, Jan 2022) : Search over 585 datasets for machine learning. 48k building footprints (enhanced 3DBAG dataset, building height attributes), Capella Space SAR data (0.5m res., four polarizations) & Worldview-3 imagery (0.3m res. Annual datasets. Instead of downloading the Visdrone-DET dataset in Python, you can effortlessly load it in Python via our. Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. You signed in with another tab or window. 8 classes (inc. cloud and cloud shadow) for 38 Sentinel-2 scenes (10 m res.). The engaging three-day single-track program, all of which is included in your registration, covers a wide range of topics, including but not limited to: On behalf of the Organizing Committee, I cordially invite you to participate in the 2015 Biomedical Circuits and Systems Conference and contribute to the continued success of this rapidly growing annual event at the intersection of medicine and engineering. 2017, EuroSAT (DFK, Aug 2017) Visdrone-DET Dataset Citation Information. 2020, xView 2018 Detection Challenge (DIUx, Jul 2018) ), 80 1kx1k px. Train a model on Visdrone-DET dataset with PyTorch in Python, dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False), Train a model on Visdrone-DET dataset with TensorFlow in Python, https://github.com/VisDrone/VisDrone-Dataset, Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin: Detection and Tracking Meet Drones Challenge, Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin, Visdrone-DET Dataset Licensing Information. The challenge consists on predicting 3161 human trajectories, observing for each trajectory 8 consecutive ground-truth values (3.2 seconds) i.e., t7,t6,,t, in world plane coordinates (the so-called world plane Human-Human protocol) and forecasting the following 12 (4.8 seconds), i.e., t+1,,t+12. The TrajNet Challenge represents a large multi-scenario forecasting benchmark. Individual tree crown objects, height&area estimates, 100 million instances, 37 geographic sites across the US, DeepForest Python package, Paper: Weinstein et al. and ImageNet 6464 are variants of the ImageNet dataset. author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin}. 10 land cover categories from crops to vehicle small, 57 1x1km images, 3/16-band Worldview 3 imagery (0.3m-7.5m res. 2021, NEON Tree Crowns Dataset (Weinstein et al., 2020) 2019. Buildings footprints, RGB satellite imagery, COCO data format, SpaceNet 2: Building Detection v2 (CosmiQ Works, Radiant Solutions, NVIDIA, May 2017) Agricultural Crop Cover Classification Challenge (CrowdANALYTIX, Jul 2018)

155k 128x128px image chips with wind turbines (SPOT, 1.5m res.). from 7-54 degrees off-nadir angle. ), Reunion island. Also comes with binary classification tags for each subscene, describing what surface types, cloud types, etc. ), Rotterdam, Netherlands. buildings, roads, vegetation). Classes: water, natural bare ground, artificial bare ground, woody vegetation, cultivated vegetation, (semi) natural vegetation, and permanent snow/ice. Land cover classification based on SEN12MS dataset (see category Semantic Segmentation on this list), low- and high-resolution tracks. Load Visdrone-DET Dataset in Python fast. 513 cropped subscenes (1022x1022 pixels) taken randomly from entire 2018 Sentinel-2 archive. For example, ImageNet 3232 ), and density (sparse and crowded scenes). 32k car bounding boxes, aerial imagery (0.15m res. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. 2018, TiSeLaC: Time Series Land Cover Classification Challenge (UMR TETIS, Jul 2017) FloodNet (University of Maryland, Jun 2021) 131k ships, 104k train / 88k test image chips, satellite imagery (1.5m res. All data upsampled to 10m res., georeferenced, covering all continents and meterological seasons, Paper: Schmitt et al. The benchmark dataset consists of 288 video clips composed of 261,908 frames and 10,209 static photos collected by several drone-mounted cameras, encompassing a wide variety of features such as location (taken from 14 different cities separated by thousands of kilometres in China), environment (urban and country), objects (pedestrian, automobiles, bicycles, etc. building flooded, building non-flooded, road-flooded, ..), 2 competition tracks (Binary & semantic flood classification; Object counting & condition recognition), Dynamic EarthNet Challenge (Planet, DLR, TUM, April 2021) Airbus Wind Turbine Patches (Airbus, Mar 2021) 12.6mil (Canada) & 125.2mil (USA) & 17.9mil (Uganda/Tanzania) & 11.3mil (Australia) building footprints, GeoJSON format, delineation based on Bing imagery using ResNet34 architecture. 10 land cover classes, temporal stack of hyperspectral Sentinel-2 imagery (R,G,B,NIR,SWIR1,SWIR2; 10 m res.) ), 5 cities, ISPRS Potsdam 2D Semantic Labeling Contest (ISPRS) In fact, TrajNet is a superset of diverse datasets that requires to train on four families of trajectories, namely 1) BIWI Hotel (orthogonal birds eye flight view, moving people), 2) Crowds UCY (3 datasets, tilted birds eye view, camera mounted on building or utility poles, moving people), 3) MOT PETS (multisensor, different human activities) and 4) Stanford Drone Dataset (8 scenes, high orthogonal birds eye flight view, different agents as people, cars etc. 124,422 Agricultural parcels, 2,433 Sentinel-2 image chip timeseries, France, panoptic labels (instance index + semantic label for each pixel). On behalf of the BioCAS 2015 Organizing Committee, This site is created, maintained, and managed by Conference Catalysts, LLC. satellite imagery, LiDAR (0.80m pulse spacing, ASCII format), semantic labels, urban setting USA, baseline methods provided, Paper: Le Saux et al. Multiple tracks: Semantic 3D reconstruction, Semantic Stereo, 3D-Point Cloud Classification. Maritime object bounding boxes for 1k Sentinel-1 scenes (VH & VV polarizations), ancillary data (land/ice mask, bathymetry, wind speed, direction, quality). 2019.

MiniFrance (Universit Bretagne-Sud and ONERA, Jul 2020) Load Visdrone-DET Dataset Training Subset in Python, Load Visdrone-DET Dataset Testing Subset in Python, Load Visdrone-DET Dataset Validation Subset in Python, Load Visdrone-DET Dataset Testing-DEV Subset in Python, How to use Visdrone-DET Dataset with PyTorch and TensorFlow in Python, Additional Information about Visdrone-DET Dataset. 41 orthophotos (9000x9000 px) over Poland, Aerial Imagery (25cm & 50cm res. subset Landsat 8 scenes (30m res. 2020, SEN12MS-CR-TS - Ebel et al. 2019, DEEPGLOBE - 2018 Satellite Challange (CVPR, Apr 2018)

Visdrone-DET validation split comprises 1580 images. Check our our latest webinar to learn more! ), COCO data format, pre-trained Tensorflow and Pytorch baseline models, Paper: Lam et al. List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. dash line, long line, zebra zone) & urban infrastructure (19 categories e.g. Synthetic (630k planes, 50k images) and real (14.7k planes, 253 Worldview-3 images (0.3m res. 180,748 corresponding image triplets containing Sentinel-1 (VV&VH), Sentinel-2 (all bands, cloud-free), and MODIS-derived land cover maps (IGBP, LCCS, 17 classes, 500m res.). Paper: Xia et al. Corresponding imagery from drone, satellite and ground camera of 1,652 university buildings, Paper: Zheng et al. Paper: Wang et al., 2021, FloodNet Challenge (UMBC, Microsoft, Texas A&M, Dewberry, May 2021) 63 categories from solar farms to shopping malls, 1 million chips, 4/8 band satellite imagery (0.3m res. journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}. University-1652: Drone-based Geolocalization (Image Retrieval) (ACM Multimedia, Oct 2020) Sentinel-2 Cloud Mask Catalogue (Francis, A., et al., Nov 2020) Oil storage tank annotations, 98 worldwide images (SPOT, 1.2m res., 2560px). Building footprints & 3 building conditions, RGB UAV imagery - Link to data, LPIS agricultural field boundaries Denmark - Netherlands - France 2020. 2343 image chips (drone imagery), 10 landcover categories (background, water, building flooded, building non-flooded, for 5.7 km2 of Munich, Germany. Multi-View Stereo 3D Mapping Challenge (IARPA, Nov 2016)

126k building footprints (Atlanta), 27 WorldView 2 images (0.3m res.) ), 12 biomes with 8 scenes each, Paper: Foga et al. 13 land cover categories + 4 cloud condition categories, 4-band (RGB-NIR) satelitte imagery (5m res. Develop a Multi-View Stereo (MVS) 3D mapping algorithm that can convert high-resolution Worldview-3 satellite images to 3D point clouds, 0.2m lidar ground truth data. Paper: & RGB imagery (0.25m res. Agriculture-Vision Database & CVPR 2020 challenge (UIUC, 2000 very high resolution aerial images over 16 cities in France (50cm res., from IGN BDORTHO), 16 landcover categories (Urban, Industrial, Pastures, Forests, etc. Land cover time series classification (9 categories), Landsat-8 (23 images time series, 10 band features, 30m res. Tree position, tree species and crown parameters, hyperspectral (1m res.) 15 categories from plane to bridge, 188k instances, object instances and segmentation masks (MS COCO format), Google Earth & JL-1 image chips, Faster-RCNN baseline model (MXNet), devkit, Academic use only, replaces DOTA dataset, Paper: Zamir et al. 60 categories from helicopter to stadium, 1 million instances, Worldview-3 imagery (0.3m res. It should be noted that the dataset was gathered utilising a variety of drone platforms (i.e., drones of various types), in a variety of settings, and under a variety of weather and lighting circumstances. The IEEE Biomedical Circuits and Systems Conference (BioCAS) serves as a premier international. Prediction of presence of oil palm plantations, Planet satellite imagery (3m res. 2 categories ship and iceberg, 2-band HH/HV polarization SAR imagery, Kaggle kernels, Functional Map of the World Challenge (IARPA, Dec 2017) boxes: tensor representing bounding box for the object of interest.

Three challenge tracks: Road Extraction, Building Detection, Land cover classification, Paper: Demir et al. 2018. Stream Visdrone-DET while training ML models. Worldview-3 (8-band, 0.35cm res.) List of satellite image training datasets with annotations for computer vision and deep learning, The list is now archived. Awesome_Satellite_Benchmark_Datasets. from Copernicus UrbanAtlas 2012), designed for semi-supervised semantic segmentation. ), Paper: Xu et al. 550k building footprints & 4 damage scale categories, 20 global locations and 7 disaster types (wildfire, landslides, dam collapses, volcanic eruptions, earthquakes/tsunamis, wind, flooding), Worldview-3 imagery (0.3m res. ), 51 GB, Cactus Aerial Photos (CONACYT Mexico, Jun 2018) We use variants to distinguish between results evaluated on 2016, Cars Overhead With Context (COWC) (Lawrence Livermore National Laboratory, Sep 2016) SpaceNet 4: Off-Nadir Buildings (CosmiQ Works, DigitalGlobe, Radiant Solutions, AWS, Dec 2018) over 2 years, 75 aois, landcover labels (7 categories), 2 competition tracks (Binary land cover classification & multi-class change detection). We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets.

), manual segmentations masks for Buildings, Woodland and Water, Paper: Boguszewski et al., 2020, 95-Cloud: A Cloud Segmentation Dataset (S. Mohajerani et. ALCD Reference Cloud Masks (CNES, Oct 2018) Mark PhelpsTalk Title:The next wave of microelectronics integration: human biology & implantable devicesBio, Jan RabaeyTalk Title: "The Human Intranet"Bio, AliKhademhosseiniTalk Title:"Microengineered tissues for regenerative medicine and organs-on-a-chip applications"Bio. Our favorite source for free datasets, collaboration, and competition is Kaggle. ), raster mask labels in in run-length encoding format, Kaggle kernels. Visdrone-DET test-dev split comprises 1610 images. Predict the chronological order of images taken at the same locations over 5 days, Kaggle kernels. 157k building footprint masks, RGB orthophotos (0.5m res. RarePlanes: Synthetic Data Takes Flight (CosmiQ Works, A.I.Reverie, June 2020) Paper: 2019, Statoil/C-CORE Iceberg Classifier Challenge (Statoil/C-CORE, Jan 2018) SpaceNet 7: Multi-Temporal Urban Development Challenge (CosmiQ Works, Planet, Aug 2020) 2 main categories corn and soybeans, Landsat 8 imagery (30m res. Monthly building footprints and Planet imagery (4m. Denmark: 293 crop/vegetation catgeories, 600k parcels. title={Detection and Tracking Meet Drones Challenge}. All bands resampled to 20m, stored as numpy arrays. Agricultural Pattern Analysis, 21k aerial farmland images (RGB-NIR, USA, 2019 season, 512x512px chips), label masks for 6 field anomaly patterns (Cloud shadow, Double plant, Planter skip, Standing Water, Waterway and Weed cluster).

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Curious about applying augmentat