def extract_chips_from_scene(job):
scene_dir = job.kwargs['scene_dir']
from satlomasproc.chips import extract_chips
rasters = glob(os.path.join(scene_dir, '*.tif'))
logger.info("Num. rasters: %i", len(rasters))
chips_dir = os.path.join(CHIPS_DIR, os.path.basename(scene_dir))
logger.info("Extract chips on images from %s into %s", scene_dir,
chips_dir)
# TODO: Generate RGB image
# TODO: Load RGB image
# FIXME: Once RGB image is prepared, there is no need to rescale on chips...
extract_chips(rasters,
aoi=AOI_PATH,
rescale_mode='values',
rescale_range=RESCALE_RANGE,
bands=BANDS,
type='tif',
size=SIZE,
step_size=STEP_SIZE,
output_dir=chips_dir)
enqueue_job('eo_sensors.tasks.perusat1.predict_scene',
chips_dir=chips_dir,
queue='processing')
def pansharpen_scene(job):
raw_scene_dir = job.kwargs['scene_dir']
from perusatproc.console.process import process_product
basename = os.path.basename(raw_scene_dir)
proc_scene_dir = os.path.join(PROC_DIR, basename)
logger.info("Process %s into %s", raw_scene_dir, proc_scene_dir)
process_product(raw_scene_dir, proc_scene_dir)
logger.info("Delete raw scene directory")
shutil.rmtree(raw_scene_dir)
enqueue_job('eo_sensors.tasks.perusat1.extract_chips_from_scene',
scene_dir=proc_scene_dir,
queue='processing')
def post(self, request):
serializer = ImportSFTPSerializer(data=request.data)
if not serializer.is_valid():
return Response(serializer.errors,
status=status.HTTP_400_BAD_REQUEST)
params = serializer.data
sftp_conn_info = {
'hostname': params['hostname'],
'port': params['port'],
'username': params['username'],
'password': params['password']
}
for file in params['files']:
enqueue_job('lomas_changes.tasks.perusat1.import_scene_from_sftp',
sftp_conn_info=sftp_conn_info,
file=file,
queue='processing')
return Response({}, status=status.HTTP_204_NO_CONTENT)
def import_scene_from_sftp(job):
"""Connects to an SFTP server and downloads a scene"""
sftp_conn_info = job.kwargs['sftp_conn_info']
filepath = job.kwargs['file']
client = SFTPClient(**sftp_conn_info)
with tempfile.TemporaryDirectory() as tmpdir:
basename = os.path.basename(filepath)
id_s = f"{job.pk}_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
scene_dir = os.path.join(RAW_DIR, id_s)
# Download file and extract to RAW_DIR
dst = os.path.join(tmpdir, basename)
logger.info("Download %s to %s", filepath, dst)
client.get(filepath, dst)
logger.info("Unzip %s into %s", dst, scene_dir)
unzip(dst, scene_dir)
enqueue_job('eo_sensors.tasks.perusat1.pansharpen_scene',
scene_dir=scene_dir,
queue='processing')
def post(self, request):
serializer = ImportSFTPSerializer(data=request.data)
if not serializer.is_valid():
return Response(serializer.errors,
status=status.HTTP_400_BAD_REQUEST)
params = serializer.data
sftp_conn_info = {
"hostname": params["hostname"],
"port": params["port"],
"username": params["username"],
"password": params["password"],
}
for file in params["files"]:
enqueue_job(
"eo_sensors.tasks.perusat1.import_scene_from_sftp",
sftp_conn_info=sftp_conn_info,
file=file,
queue="processing",
)
return Response({}, status=status.HTTP_204_NO_CONTENT)
def predict_scene(job):
chips_dir = job.kwargs['chips_dir']
from satlomasproc.unet.predict import PredictConfig, predict
predict_chips_dir = os.path.join(PREDICT_DIR, os.path.basename(chips_dir))
cfg = PredictConfig(images_path=chips_dir,
results_path=predict_chips_dir,
batch_size=BATCH_SIZE,
model_path=MODEL_PATH,
height=SIZE,
width=SIZE,
n_channels=len(BANDS),
n_classes=len(CLASSES))
logger.info("Predict chips on %s", predict_chips_dir)
predict(cfg)
logger.info("Delete chips directory")
shutil.rmtree(chips_dir)
enqueue_job('eo_sensors.tasks.perusat1.postprocess_scene',
predict_chips_dir=predict_chips_dir,
queue='processing')