Latest Contributions by AsafEvenPaz

I have a table with several rows of data for each month of the year and I want to display it in the dashboard giving the user the option to filter by month. I know there is the data picker but when I try to add it and apply an action it doe snot seem to filter the correct results. Any ideas?  ... View more

We have many users which belong to different groups but all belong to our AGOL organization. Sometime, some of the users from one group decide to share items (specifically Survey123 forms) to the whole organization and we need to revert those shares so that those surveys don't show up to users which belong to other groups. Is there a way to restrict the users to share outside of their group?  ... View more

Has anyone had any experience calculating and presenting Net Promoter Score with dashboards? I have a table with score values (from 1 to 10) and I want to calculate the Net Promoter Score as an indicator ... View more

When you create a new survey in Survey123 Connect you have the option to use a survey from a template. How can I add more templates to this list and can I point it to an AGOL group where our organization stores these templates? ... View more

I am trying to run a notebook given to me by Esri Support staff (case #02587809) and when I try to run the arcpy.ia.DetectObjectsUsingDeepLearning function I recieve the following error message: Line 1: arcpy.ia.DetectObjectsUsingDeepLearning(imagery, r"C:\Users\Administrator\Documents\ArcGIS\Projects\Haiti_AI\Haiti_AI.gdb\bldg_detected_jupyterGPU_10July2020", r"D:\TrainingData\MaskRCNN_chips\models\Building_footprint_40epochsGPU\Building_footprint_40epochsGPU.emd", "padding 64;batch_size 4;threshold 0.9;return_bboxes False", "NO_NMS", "Confidence", "Class", 0, "PROCESS_AS_MOSAICKED_IMAGE") File c:\program files\arcgis\pro\Resources\arcpy\arcpy\ia\Functions.py, in DetectObjectsUsingDeepLearning: Line 2888: processing_mode) File c:\program files\arcgis\pro\Resources\arcpy\arcpy\sa\Utils.py, in swapper: Line 53: result = wrapper(*args, **kwargs) File c:\program files\arcgis\pro\Resources\arcpy\arcpy\ia\Functions.py, in Wrapper: Line 2877: processing_mode) File c:\program files\arcgis\pro\Resources\arcpy\arcpy\geoprocessing\_base.py, in <lambda>: Line 511: return lambda *args: val(*gp_fixargs(args, True)) ExecuteError: ERROR 999999: Something unexpected caused the tool to fail. Contact Esri Technical Support (http://esriurl.com/support) to Report a Bug, and refer to the error help for potential solutions or workarounds. Unable to initialize python raster function with scalar arguments. Traceback (most recent call last): File "D:\TrainingData\MaskRCNN_chips\models\Building_footprint_40epochsGPU\ArcGISInstanceDetector.py", line 169, in initialize self.child_instance_detector.initialize(model, model_as_file) File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_inferencing\_maskrcnn_inferencing.py", line 158, in initialize self.mask_rcnn = MaskRCNN.from_model(emd_path=model) File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_maskrcnn.py", line 215, in from_model data = _EmptyData(path=emd_path.parent.parent, loss_func=None, c=len(class_mapping) + 1, chip_size=emd['ImageHeight']) File "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\lib\site-packages\arcgis\learn\models\_arcgis_model.py", line 60, in __init__ if getattr(arcgis.env, "_processorType", "") == "GPU" and torch.cuda.is_available(): NameError: name 'torch' is not defined Unable to initialize python raster function with scalar arguments. Failed to execute (DetectObjectsUsingDeepLearning). I have tried various workarounds from similar threads but nothing so far. I am using a g3s.xlarge machine and remote desktop (windows machine) with GPU enabled. I have verified that the GPU is being used by running: cudaDevice=torch.cuda.current_device() print ("GPU-Device: "+str(cudaDevice)) print ("GPU-Device-Info: "+str(torch.cuda.device(cudaDevice))) print ("GPU-Device-Count: "+str(torch.cuda.device_count())) print ("GPU-Device-Name: "+str(torch.cuda.get_device_name(cudaDevice))) print ("GPU-Device-Availability: "+str(torch.cuda.is_available())) #now some more info device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') print('Using device:', device) print() #Additional Info when using cuda if device.type == 'cuda': print(torch.cuda.get_device_name(0)) print('Memory Usage:') print('Allocated:', round(torch.cuda.memory_allocated(0)/1024**3,1), 'GB') print('Cached: ', round(torch.cuda.memory_cached(0)/1024**3,1), 'GB') # use this to test: Run code, dont close, # go to OS and run nvidia-smi to see process runs on GPU print (torch.rand(3,3).cuda()) os.system('nvidia-smi.exe>c:/temp/log.txt') with open(r'c:/temp/log.txt', 'r') as f: print(f.read()) Resulting in: GPU-Device: 0 GPU-Device-Info: <torch.cuda.device object at 0x000002B5B5DCD390> GPU-Device-Count: 1 GPU-Device-Name: Tesla M60 GPU-Device-Availability: True Using device: cuda Tesla M60 Memory Usage: Allocated: 0.0 GB Cached: 0.0 GB tensor([[0.3166, 0.1292, 0.2083], [0.2514, 0.0501, 0.4692], [0.8568, 0.1868, 0.6476]], device='cuda:0') Any thoughts? ... View more