patch_generator.generate_patches(BBOX, DOP_SIZE,
patch_size=PATCH_SIZE,
offset_steps=PATCH_OFFSET_STEPS,
target_folder=DATASETPATH,
data_folder='dop' + f,
force_refresh=False
)
try:
os.makedirs(TMP_DIR)
except:
None
algo.__clear_dir(TMP_DIR)
cats = [0,1]
ncats = len(cats)
print ""
print "---------------------"
print "## loading the images and extracting the sift features"
# list files
all_files = get_imgfiles(DATASETPATH)
all_labels = {}
all_weights = {}
for i in all_files:
certainty = float(i.replace("\\","/").rpartition("/")[2].partition("_")[0])
label = 1 if certainty > 0 else 0
# init
args = parse_arguments()
DATASET_DIR = args.d
cats = [0, 1]
ncats = len(cats)
# generate and prepare folders
algo.__try_mkdirs(DATASET_DIR)
algo.__try_mkdirs(TRAININGSET_DIR)
algo.__try_mkdirs(VALIDATIONSET_DIR)
algo.__try_mkdirs(TMP_DIR_TRAINING)
algo.__try_mkdirs(TMP_DIR_VALIDATION)
algo.__clear_dir(DATASET_DIR)
algo.__clear_dir(TRAININGSET_DIR)
algo.__clear_dir(VALIDATIONSET_DIR)
# do training
performances = [] # keep track of different parameter performances
# iterate over different patch_sizes
for patch_size in HYPERPARAMETERS_OPTIONS["patch_size"]:
hyperparameters = {} # keep track of current hyperparameters
performance = {} # keep track of current performance
hyperparameters["patch_size"] = patch_size
print "HYPERPARAMETER: patch_size = " + str(patch_size)
TMP_DIR = '../data/tmp/test/'
IMG_BBOX=(11.60339,48.17708,11.61304,48.18326) ; IMG_SIZE=(1500, 1000) ; IMG_NAME="dopA" # between Grasmeier and Crailsheimerstr.
SATELLITE_IMG_VISUALIZATION_INPUT="dopA/dop-annotated.png"
SATELLITE_IMG_VISUALIZATION_OUTPUT="../data/dopA-predictions.png"
#IMG_BBOX =(11.59221,48.17038,11.61233,48.18380) ; IMG_SIZE=(2000, 2000) ; SATELLITE_IMG_TMP="dopB.png" # bigger as above.
#SATELLITE_IMG_VISUALIZATION_INPUT="dopB-annotated.png"
#SATELLITE_IMG_VISUALIZATION_OUTPUT="dopB-predictions.png"
#important: a must be smaller than c, b must be smaller then d
if (__name__ == "__main__"):
# init
algo.__try_mkdirs(DATASET_DIR)
algo.__clear_dir(DATASET_DIR)
algo.__try_mkdirs(TMP_DIR)
algo.__clear_dir(TMP_DIR)
with open(HYPERPARAMETERS_FILE, "r") as f:
params = json.loads(f.read())
# generate patches
print "---------------------"
print "## generating patches from '" + IMG_NAME + "' (" + str(IMG_SIZE[0])+"x"+str(IMG_SIZE[1]) + "; " + str(IMG_BBOX) + ")"
patch_generator.generate_patches(IMG_BBOX, IMG_SIZE,
patch_size=params['hyperparameters']['patch_size'],
offset_steps=params['hyperparameters']['patch_offset'],
target_folder=DATASET_DIR,
force_refresh=False,
