What's caching? It's simple. Adding the decorator @st.experimental_memo will make the function get_data() run once. Then every time you rerun your app, the data will stay memoized! This way you can avoid downloading the dataset again and again. Read more about caching in Streamlit docs.
Mapbox Studio is a suite of applications for designing custom map styles and managing your location data. Use Mapbox Studio to build and design a map to your exact specifications by uploading and editing your own data, utilizing Mapbox-provided tilesets, adding custom fonts and icons, or refining the built-in core styles. With Mapbox Studio, full data management and design control are at your fingertips.
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Mapbox Studio gives you full control over styling interactive maps through the style editor. You can tweak the colors and fonts on a core style in minutes and start using the map in an app or website, or you can build your own map style from the ground up with custom data and carefully crafted style layers.Mapbox Studio also lets you import data to use in your styles. When you import data into Mapbox Studio, your data is converted into vector tiles. Supported formats include Shapefiles, geoJSON files, CSV files, and more.Finally, Mapbox Studio includes a dataset editor that lets you manage your own datasets. The dataset editor makes it possible to add point, line, and polygon features with draw tools. It includes a property editor for adding custom fields to your features. In Mapbox Studio, datasets can be converted to tilesets and then used in styles.
With Tabidoo, users can be in full control of their data and projects. All of the data, processes, and activities are transparent which contributes to a more efficient, open, and well-organized working environment. Also, this data entry application is constantly improving, and you can always contact the development team to find out all you need to know about the app.
25.2.2021: We have updated the evaluation procedure for Tracking and MOTS. Evaluation now uses the HOTA metrics and is performed with the TrackEval codebase.
04.12.2019: We have added a novel benchmark for multi-object tracking and segmentation (MOTS)!
18.03.2018: We have added novel benchmarks for semantic segmentation and semantic instance segmentation!
11.12.2017: We have added novel benchmarks for depth completion and single image depth prediction!
26.07.2017: We have added novel benchmarks for 3D object detection including 3D and bird's eye view evaluation.
26.07.2016: For flexibility, we now allow a maximum of 3 submissions per month and count submissions to different benchmarks separately.
29.07.2015: We have released our new stereo 2015, flow 2015, and scene flow 2015 benchmarks. In contrast to the stereo 2012 and flow 2012 benchmarks, they provide more difficult sequences as well as ground truth for dynamic objects. We hope for numerous submissions :)
09.02.2015: We have fixed some bugs in the ground truth of the road segmentation benchmark and updated the data, devkit and results.
11.12.2014: Fixed the bug in the sorting of the object detection benchmark (ordering should be according to moderate level of difficulty).
04.09.2014: We are organizing a workshop on reconstruction meets recognition at ECCV 2014!
31.07.2014: Added colored versions of the images and ground truth for reflective regions to the stereo/flow dataset.
30.06.2014: For detection methods that use flow features, the 3 preceding frames have been made available in the object detection benchmark.
04.04.2014: The KITTI road devkit has been updated and some bugs have been fixed in the training ground truth. The server evaluation scripts have been updated to also evaluate the bird's eye view metrics as well as to provide more detailed results for each evaluated method
04.11.2013: The ground truth disparity maps and flow fields have been refined/improved. Thanks to Donglai for reporting!
31.10.2013: The pose files for the odometry benchmark have been replaced with a properly interpolated (subsampled) version which doesn't exhibit artefacts when computing velocities from the poses.
10.10.2013: We are organizing a workshop on reconstruction meets recognition at ICCV 2013!
03.10.2013: The evaluation for the odometry benchmark has been modified such that longer sequences are taken into account
25.09.2013: The road and lane estimation benchmark has been released!
20.06.2013: The tracking benchmark has been released!
29.04.2013: A preprint of our IJRR data paper is available for download now!
06.03.2013: More complete calibration information (cameras, velodyne, imu) has been added to the object detection benchmark.
27.01.2013: We are looking for a PhD student in 3D semantic scene parsing (position available at MPI Tübingen).
23.11.2012: The right color images and the Velodyne laser scans have been released for the object detection benchmark.
19.11.2012: Added demo code to read and project 3D Velodyne points into images to the raw data development kit.
12.11.2012: Added pre-trained LSVM baseline models for download.
04.10.2012: Added demo code to read and project tracklets into images to the raw data development kit.
01.10.2012: Uploaded the missing oxts file for raw data sequence 2011_09_26_drive_0093.
26.09.2012: The velodyne laser scan data has been released for the odometry benchmark.
11.09.2012: Added more detailed coordinate transformation descriptions to the raw data development kit.
26.08.2012: For transparency and reproducability, we have added the evaluation codes to the development kits.
24.08.2012: Fixed an error in the OXTS coordinate system description. Plots and readme have been updated.
19.08.2012: The object detection and orientation estimation evaluation goes online!
24.07.2012: A section explaining our sensor setup in more details has been added.
23.07.2012: The color image data of our object benchmark has been updated, fixing the broken test image 006887.png.
04.07.2012: Added error evaluation functions to stereo/flow development kit, which can be used to train model parameters.
03.07.2012: Don't care labels for regions with unlabeled objects have been added to the object dataset.
02.07.2012: Mechanical Turk occlusion and 2D bounding box corrections have been added to raw data labels.
28.06.2012: Minimum time enforced between submission has been increased to 72 hours.
27.06.2012: Solved some security issues. Login system now works with cookies.
02.06.2012: The training labels and the development kit for the object benchmarks have been released.
29.05.2012: The images for the object detection and orientation estimation benchmarks have been released.
28.05.2012: We have added the average disparity / optical flow errors as additional error measures.
27.05.2012: Large parts of our raw data recordings have been added, including sensor calibration.
08.05.2012: Added color sequences to visual odometry benchmark downloads.
24.04.2012: Changed colormap of optical flow to a more representative one (new devkit available). Added references to method rankings.
23.04.2012: Added paper references and links of all submitted methods to ranking tables. Thanks to Daniel Scharstein for suggesting!
05.04.2012: Added links to the most relevant related datasets and benchmarks for each category.
04.04.2012: Our CVPR 2012 paper is available for download now!
20.03.2012: The KITTI Vision Benchmark Suite goes online, starting with the stereo, flow and odometry benchmarks.
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