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Top Earth Datasets and Models
The datasets below can be used to train fine-tuned models for earth detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
At the bottom of this page, we have guides on how to train a model using the earth datasets below.
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818 images
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254 images1 model
boltAC sensor connectorAir Cleaner Clip (4 Nos)Air Cleaner Hose Clamp (2 Nos)Brake reservoir tankBrake reservoir tank capCowl fender clipEarth bolt to body 2 NosEgr Cooler Hose X Heater TubeEgr Cooler Hose X Heater Tube 2Eng ByPass Hose X Egr Throttle Inlet TubeEng Outlet X Heater By Pass HoseEng Outlet X Heater Inlet HoseH capHose to llc tankPs oil capRelay Box No 1 Upper Cover 1air flow sensor connectorbattery clampbattery holder top
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739 images1 model
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1663 images1 model
capacitordiodeinductormetermotorpanelsockettransformer(RCD Circuit Breaker) Circuit Breaker with an Earth Connection and a Disconnector Isolator3wayswitchACpower supplyAir circuit breakerAmmeterAnnounciatorBRANCH CIRCUIT MINIMUM SIZE PER CKT BKRBRANCH CIRCUIT MINIMUM SIZE PER CKT BKR - REMAINBatteryBrake CluthesBusbarCapacitive Voltage transformer
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800 images
(x1,y1),(x2,y2),aGong Cheng, Junwei Han, Peicheng Zhou, Lei Guo. Multi-class geospatial object detection and geographic image classification based on collection of part detectors. ISPRS Journal of Photogrammetry and Remote Sensing, 98: 119-132, 2014.Gong Cheng, Junwei Han. A survey on object detection in optical remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 117: 11-28, 2016.Please cite the following relevant papers when publishing results that use this dataset fully or partly:The folder "ground truth" contains 650 separate text files and each one corresponds to an image in "positive image set" folder. Each line of those text files defines a ground truth bounding box in the following format:These images were cropped from Google Earth and Vaihingen data set and then manually annotated by experts. The Vaihingen data was provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF): http://www.ifp.uni-stuttgart.de/dgpf/DKEPAllg.html.This dataset contains totally 800 VHR remote sensing images, where the folder "negative image set" includes 150 images that do not contain any targets of the given object classes and the folder "positive image set" includes 650 images with each image containing at least one target to be detected.This is a 10-class geospatial object detection dataset used for research purposes only.These ten classes of objects are airplane, ship, storage tank, baseball diamond, tennis court, basketball court, ground track field, harbor, bridge, and vehicle.This very-high-resolution (VHR) remote sensing image dataset was constructed by Dr. Gong Cheng et al. from Northwestern Polytechnical University (NWPU).where (x1,y1) denotes the top-left coordinate of the bounding box, (x2,y2) denotes the right-bottom coordinate of the bounding box, and a is the object class (1-airplane, 2-ship, 3-storage tank, 4-baseball diamond, 5-tennis court, 6-basketball court, 7-ground track field, 8-harbor, 9-bridge, 10-vehicle).