Tim-Oliver
07/14/2023, 11:29 AMpydantic.BaseModel
inputs are missing. They are visible in the default and custom view, but missing in the json view. Starting the flow-run results in an error that the respective parameters are missing.Jenny
07/14/2023, 12:46 PMTim-Oliver
07/14/2023, 12:52 PMJenny
07/14/2023, 12:52 PMTim-Oliver
07/14/2023, 1:51 PM{
"stride": 20,
"mesh_files": [
"/test/output/sections/s1080_g1/meshes.npz",
"/test/output/sections/s1094_g1/meshes.npz",
"/test/output/sections/s1082_g1/meshes.npz",
"/test/output/sections/s1077_g1/meshes.npz",
"/test/output/sections/s1093_g1/meshes.npz",
"/test/output/sections/s1089_g1/meshes.npz",
"/test/output/sections/s1076_g1/meshes.npz",
"/test/output/sections/s1090_g1/meshes.npz"
],
"output_dir": "/test/output/stitched-sections",
"warp_config": {
"nbins": 256,
"margin": 20,
"use_clahe": true,
"clip_limit": 0.01,
"kernel_size": 1024,
"warp_parallelism": 5
}
}
If I now go on "copy to new run" from this completed run the "warp_config" parameter is missing in the json view. If I submit the flow-run I get the error that the "warp_config" parameter is missing.
The obvious work-around would be to just copy-paste the complete json into the json-form. However, the flow still fails with the message that "warp_config" is missing.
One important thing might be that all values in "warp_config" are equal to the default values in that case.Jenny
07/17/2023, 6:34 PMCraig Harshbarger
07/17/2023, 7:52 PMWarpConfig
it'll work just how you'd expect. I see you're already doing this in the tile_stitching
flow so I think this will work fine for your use case.
def warp_tiles_flow(
output_dir: str,
mesh_files: list[str],
stride: int,
warp_config: WarpConfig = WarpConfig(),
):