{"name": "Deepness: Deep Neural Remote Sensing", "package_name": "deepness", "description": "Inference of deep neural network models (ONNX) for segmentation, detection and regression", "about": "Deepness plugin allows to easily perform segmentation, detection and regression on raster ortophotos with custom ONNX Neural Network models, bringing the power of deep learning to casual users.\nFeatures highlights:\n- processing any raster layer (custom ortophoto from file or layers from online providers, e.g Google Satellite)\n- limiting processing range to predefined area (visible part or area defined by vector layer polygons)\n- common types of models are supported: segmentation, regression, detection\n- integration with layers (both for input data and model output layers). Once an output layer is created, it can be saved as a file manually\n- model ZOO under development (planes detection on Bing Aerial, Corn field damage, Oil Storage tanks detection, cars detection, ...)\n- training data Export Tool - exporting raster and mask as small tiles\n- parametrization of the processing for advanced users (spatial resolution, overlap, postprocessing)\nPlugin requires external python packages to be installed. After the first plugin startup, a Dialog will show, to assist in this process. Please visit plugin the documentation for details.", "homepage": "https://qgis-plugin-deepness.readthedocs.io/", "repository": "https://github.com/PUTvision/qgis-plugin-deepness", "tracker": "https://github.com/PUTvision/qgis-plugin-deepness/issues", "author": "PUT Vision", "tags": ["analysis", "classification", "remote sensing", "regression", "supervised classification", "machine learning", "segmentation", "deep learning", "neural network", "onnx", "deepness", "detection"], "downloads": 79085, "latest_version": "0.6.5", "versions": [{"version": "0.6.5", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 45736, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2024-12-10T04:38:22.549072"}, {"version": "0.6.4", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 5395, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2024-10-04T04:42:41.086754"}, {"version": "0.6.3", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 7528, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2024-04-14T07:48:03.235279"}, {"version": "0.6.2", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 2092, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2024-03-22T07:30:43.959338"}, {"version": "0.6.1", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 2022, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2024-02-23T05:32:04.941600"}, {"version": "0.6.0", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 1560, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2024-02-09T04:30:03.794279"}, {"version": "0.5.4", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 4267, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2023-09-28T05:09:09.402499"}, {"version": "0.5.3", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 1412, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2023-09-18T15:28:56.295377"}, {"version": "0.5.1", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 2049, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2023-07-17T04:31:40.398743"}, {"version": "0.4.1", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 3201, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2022-11-14T08:16:58.822580"}, {"version": "0.4.0", "experimental": false, "qgis_min": "3.10.14", "qgis_max": "3.99.0", "downloads": 3188, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2022-10-27T02:21:41.082963"}, {"version": "0.3.0", "experimental": true, "qgis_min": "3.10.14", "qgis_max": "3.99.0", "downloads": 1037, "uploaded_by": "przemyslawaszkowski", "upload_datetime": "2022-10-20T06:38:14.243751"}]}