changed edgenet360 to edgenet-360

scripts/360monodepthexecution/extractDepthMap.ps1

@@ -6,7 +6,7 @@ $imageNameOrId = (Get-Content $configPath | Where-Object { $_ -match "imageId="
 $scriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
 # Calculate paths
 $rootDir = Split-Path -Parent (Split-Path -Parent $scriptDir)
-$outputDir = Join-Path $rootDir "edgenet360\Data\Input"
+$outputDir = Join-Path $rootDir "edgenet-360\Data\Input"
 
 # Docker container name or ID
 $containerNameOrId = docker ps --filter "ancestor=$imageNameOrId" --format "{{.ID}}"

scripts/GUI.py

@@ -20,8 +20,8 @@ def shift_image_selection():
     pass
 
 def copy_intermediary_outputs():
-    source_folder = os.path.join(ROOT_DIR, "edgenet360", "Data", "Input")
-    destination_folder = os.path.join(ROOT_DIR, "edgenet360", "Output")
+    source_folder = os.path.join(ROOT_DIR, "edgenet-360", "Data", "Input")
+    destination_folder = os.path.join(ROOT_DIR, "edgenet-360", "Output")
     files_to_copy = ["depth_e.png", "enhanced_depth_e.png", "material.png", "rgb.png"]
     
     for file_name in files_to_copy:

scripts/combined.bat

@@ -20,13 +20,13 @@ for /f "tokens=1,2 delims==" %%a in (config.ini) do (
 set scriptDir=%~dp0
 set workingDir=%scriptDir%..
 set monoDepthDir=%workingDir%\scripts\360monodepthexecution
-set outputDir=%workingDir%\edgenet360\Output
+set outputDir=%workingDir%\edgenet-360\Output
 set materialRecogDir=%workingDir%\Dynamic-Backward-Attention-Transformer
-set edgeNetDir=%workingDir%\edgenet360
+set edgeNetDir=%workingDir%\edgenet-360
 
 :: File paths
 set checkpointFile=%materialRecogDir%\checkpoints\dpglt_mode95\accuracy\epoch=126-valid_acc_epoch=0.87.ckpt
-set shiftedImage=%scriptDir%shifted_t.png
+set shiftedImage=%scriptDir%\shifted_t.png
 set monoDepthImage=%monoDepthDir%\rgb.jpg
 
 :: Ensure the input file exists
@@ -82,7 +82,7 @@ popd
 echo Running material recognition...
 pushd "%materialRecogDir%"
 call "%condaDir%\condabin\activate.bat" %materialEnv%
-python train_sota.py --data-root "./datasets" --batch-size 1 --tag dpglt --gpus 1 --num-nodes 1 --epochs 200 --mode 95 --seed 42 --test "%checkpointFile%" --infer "%materialRecogDir%/split_output/"
+python train_sota.py --data-root "./datasets" --batch-size 1 --tag dpglt --gpus 1 --num-nodes 1 --epochs 200 --mode 95 --seed 42 --test "%checkpointFile%" --infer "%materialRecogDir%/cubemap_faces/"
 if errorlevel 1 (
     echo Error: Material recognition failed. Please check the output above for more details.
     call "%condaDir%\condabin\deactivate.bat"