# Find the best implementation available
try:
from cStringIO import StringIO
except ImportError:
from StringIO import StringIO
import lmdb
import numpy as np
import PIL.Image
if __name__ == '__main__':
dirname = os.path.dirname(os.path.realpath(__file__))
sys.path.insert(0, os.path.join(dirname,'..','..','..','..'))
from digits.config.load import load_config
load_config()
# Run load_config() first to set the path to Caffe
import caffe_pb2
IMAGE_SIZE = 10
TRAIN_IMAGE_COUNT = 360
#VAL_IMAGE_COUNT = 20
def create_lmdbs(folder, image_width=None, image_height=None, image_count=None):
"""
Creates LMDBs for generic inference
Returns the filename for a test image
# Find the best implementation available
try:
from cStringIO import StringIO
except ImportError:
from StringIO import StringIO
import lmdb
import numpy as np
import PIL.Image
if __name__ == '__main__':
dirname = os.path.dirname(os.path.realpath(__file__))
sys.path.insert(0, os.path.join(dirname, '..', '..'))
from digits.config.load import load_config
load_config()
from digits import utils
# Run load_config() first to set the path to Caffe
import caffe.io
import caffe_pb2
IMAGE_SIZE = 10
TRAIN_IMAGE_COUNT = 1000
VAL_IMAGE_COUNT = 1000
TEST_IMAGE_COUNT = 10
DB_BATCH_SIZE = 100
def create_lmdbs(folder,