Hello, I am going through the Detecting Objects with Deep Learning course in Esri training and keep running into the same error. I am using ArcGIS Pro 2.6.3 on my Dell XPS 15 Laptop with Nvidia GTX 1050 GPU which as far as I can tell is CUDA enabled. I have also installed deep learning frameworks for ArcGIS 2.6 from here. Whenever I run the Detect Objects Using Deep Learning tool I get the error below. I have tried running that tool using CPU by selecting CPU in the Environments menu under Processor Type. I have also tried cloning the default python environment and adding tensorflow-mkl package as seen in other similar posts in order to run Tensorflow using CPU in case it is a GPU issue, but at no avail - I cannot seem to install that package. Please help, would love to get that example to run. Thank you!
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I have two vector layers which I am having trouble lining up. First, I have a point layer that was developed a decade ago to sample information from Public Land Survey System records in Washington and Oregon State. Second layer I have is PLSS grid polygon layer recently downloaded from Bureau of Land Management. The points are not just nodes, but also were placed at various distances along the grid lines. Spatial reference: Point layer is projected in NAD83 / BC Albers, EPSG: 3005. PLSS grid polygon layer is not projected, instead it has GCS North American 1983, EPSG: 4269 I have tried to project the grid layer to EPSG: 3005 and several others. Similarly, I have tried to reproject the point layer. Essentially, sampled points should line up with PLSS grid corners and other point placed along the grid lines, however all of my attempts to project each layer have yielded no desirable results, points are always off. Unfortunately, no documentation is available on development of the point layer, therefore I do not know whether previous PLSS layer used a different projection, but I would expect BLM PLSS layers to be the same to layer available a decade ago. Please help to identify possible solutions, as the point layer contains a lot of valuable information which would take very long to replace or correct manually.
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