def gen_mask_region_by_tile(field_region: str,
stack_ind: str,
working_dir: str,
current_tile: str,
all_model: str,
shp_rname: str,
path_to_img: str,
path_test: str,
path_to_config: str,
path_wd: Optional[str] = None) -> List[str]:
"""
Parameters
----------
field_region: string
stack_ind: string
working_dir: string
current_tile: string
all_model: string
shp_rname: string
path_to_image: string
path_test: string
path_wd: string
path_to_config: string
config file containing which model is associated to a given tile
Return
------
list(str)
"""
model_tile = []
for path in all_model:
current_model = path.split("/")[-1].split("_")[1]
tiles = fu.getListTileFromModel(current_model, path_to_config)
model = path.split("/")[-1].split("_")[1]
for tile in tiles:
# get the model which learn the current tile
if tile == current_tile:
model_tile.append(model)
path_to_feat = os.path.join(path_to_img, tile, "Final", stack_ind)
mask_shp = os.path.join(path_test, "shapeRegion",
f"{shp_rname}_region_{model}_{tile}.shp")
mask_tif = os.path.join(
working_dir, f"{shp_rname}_region_{model}_{tile}_NODATA.tif")
mask_tif_f = os.path.join(
path_test, "classif", "MASK",
f"{shp_rname}_region_{model}_{tile}_NODATA.tif")
# Create mask
if not os.path.exists(mask_tif_f):
cmd_raster = (
f"otbcli_Rasterization -in {mask_shp} -mode attribute "
f"-mode.attribute.field {field_region} -im {path_to_feat}"
f" -out {mask_tif}")
run(cmd_raster)
if path_wd is not None:
cmd = "cp " + mask_tif + " " + path_test + "/classif/MASK"
run(cmd)
return model_tile
def launchClassification(model, path_cfg, output_path: str,
classifier_name: str, classification_mode: str,
nomenclature_path: str, stat, pathToRT, pathToImg,
pathToRegion, fieldRegion, pathToCmdClassif, pathOut,
RAM, pathWd):
"""
Parameters
----------
output_path : str
iota2 output directory
"""
scriptPath = os.path.join(fu.get_iota2_project_dir(), "iota2")
pixType = fu.getOutputPixType(nomenclature_path)
AllCmd = []
maskFiles = pathOut + "/MASK"
if not os.path.exists(maskFiles):
run("mkdir " + maskFiles)
if pathToRegion is None:
pathToRegion = os.path.join(output_path, "MyRegion.shp")
shpRName = pathToRegion.split("/")[-1].replace(".shp", "")
AllModel_tmp = fu.FileSearch_AND(model, True, "model", ".txt")
AllModel = fu.fileSearchRegEx(model + "/*model*.txt")
for currentFile in AllModel_tmp:
if currentFile not in AllModel:
os.remove(currentFile)
for path in AllModel:
model = path.split("/")[-1].split("_")[1]
tiles = fu.getListTileFromModel(
model, output_path + "/config_model/configModel.cfg")
model_Mask = model
if re.search('model_.*f.*_', path.split("/")[-1]):
model_Mask = path.split("/")[-1].split("_")[1].split("f")[0]
seed = path.split("/")[-1].split("_")[-1].replace(".txt", "")
suffix = ""
if "SAR.txt" in os.path.basename(path):
seed = path.split("/")[-1].split("_")[-2]
suffix = "_SAR"
tilesToEvaluate = tiles
#construction du string de sortie
for tile in tilesToEvaluate:
pathToFeat = fu.FileSearch_AND(pathToImg + "/" + tile + "/tmp/",
True, "MaskCommunSL", ".tif")[0]
maskSHP = pathToRT + "/" + shpRName + "_region_" + model_Mask + "_" + tile + ".shp"
maskTif = shpRName + "_region_" + model_Mask + "_" + tile + ".tif"
CmdConfidenceMap = ""
confidenceMap_name = "{}_model_{}_confidence_seed_{}{}.tif".format(
tile, model, seed, suffix)
CmdConfidenceMap = " -confmap " + os.path.join(
pathOut, confidenceMap_name)
if not os.path.exists(maskFiles + "/" + maskTif):
pathToMaskCommun = pathToImg + "/" + tile + "/tmp/" + "MaskCommunSL" + ".shp"
#cas cluster
if pathWd != None:
maskFiles = pathWd
nameOut = fu.ClipVectorData(maskSHP, pathToMaskCommun,
maskFiles,
maskTif.replace(".tif", ""))
cmdRaster = "otbcli_Rasterization -in "+nameOut+" -mode attribute -mode.attribute.field "+\
fieldRegion+" -im "+pathToFeat+" -out "+maskFiles+"/"+maskTif
if "fusion" in classification_mode:
cmdRaster = "otbcli_Rasterization -in "+nameOut+" -mode binary -mode.binary.foreground 1 -im "+\
pathToFeat+" -out "+maskFiles+"/"+maskTif
run(cmdRaster)
if pathWd != None:
run("cp " + pathWd + "/" + maskTif + " " + pathOut +
"/MASK")
os.remove(pathWd + "/" + maskTif)
out = pathOut + "/Classif_" + tile + "_model_" + model + "_seed_" + seed + suffix + ".tif"
#hpc case
if pathWd != None:
out = "$TMPDIR/Classif_" + tile + "_model_" + model + "_seed_" + seed + suffix + ".tif"
CmdConfidenceMap = " -confmap $TMPDIR/" + confidenceMap_name
appli = "python " + scriptPath + "/Classification/ImageClassifier.py -conf " + path_cfg + " "
pixType_cmd = " -pixType " + pixType
if pathWd != None:
pixType_cmd = pixType_cmd + " --wd $TMPDIR "
cmd = appli + " -in " + pathToFeat + " -model " + path + " -mask " + pathOut + "/MASK/" + maskTif + " -out " + out + " " + pixType_cmd + " -ram " + str(
RAM) + " " + CmdConfidenceMap
# add stats if svm
if "svm" in classifier_name.lower():
model_statistics = os.path.join(
stat, "Model_{}_seed_{}.xml".format(model, seed))
cmd = "{} -imstat {}".format(cmd, model_statistics)
AllCmd.append(cmd)
fu.writeCmds(pathToCmdClassif + "/class.txt", AllCmd)
return AllCmd
