join ( data_dir, 'cities' ) # path to new cities directory print ( f 'Dataset unzipped at: ' ) # Extract data unzip_data () ZipFile ( zipped_file_path, 'r' ) zip_ref. join ( data_dir, 'sedf_guide_data.zip' ) # path to zipped file inside data folder # unzip the data zip_ref = zipfile.
download ( data_dir ) # download the data item zipped_file_path = os.
rmtree ( data_dir ) print ( f 'Removed existing data directory' ) else : os.
getcwd (), 'sedf_data' ) # path to downloaded data folder # remove existing cities directory if exists if os. # Download and extract the data def unzip_data (): """ This function: - creates a directory `sedf_data` to download the data from the item - downloads the item as `sedf_guide_data.zip` file in the sedf_data directory - unzips and extracts the data to '.\sedf_data\cities'. Deep Learning with ArcGIS Geospatial Deep Learning with arcgis.learn How does feature categorization work? Object detection and tracking on videos How SSD works How RetinaNet works YOLOv3 Object Detector Faster R-CNN Object Detector How Mask RCNN works Multi-object Tracking using ObjectTracker Track objects using SiamMask How U-net Works How PSPNet works How DeepLabV3 works Edge Detection How Multi-task road extractor works How Change Detection Works How CycleGAN works How Pix2Pix translation works How SuperResolution works How Image Captioning works Point Cloud Segmentation using PointCNN Geo referencing and digitization of scanned maps with arcgis.learn Unsupervised Machine Learning using arcgis.learn Full圜onnectedNetwork and MLModel guide TimeseriesModel Text classification with arcgis.learn Named entity extraction workflow Labeling text using Doccano How SequenceToSequence works? Inference only Text Models Training Mobile-Ready models using TensorFlow Lite Monitor model training with TensorBoard Retraining Windows and Doors Extraction model Working with Multispectral Data Utilize multiple GPUs to train models
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