#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
import sys
sys.path.append('.')
base_dir = sys.argv[1]
#from ikalog.utils import WeaponRecoginizer
from ikalog.utils.neuralnet.weapon import WeaponClassifier
#weapons = WeaponRecoginizer()
weapons = WeaponClassifier()
weapons.load_model_from_file()
#weapons.knn_train()
weapons.test_samples_from_directory(base_dir)
weapons.dump_test_results_html(short=True)
#
from http.server import HTTPServer, SimpleHTTPRequestHandler
import json
import logging
import time
import ikalog.constants
from ikalog.utils import *
from ikalog.utils.character_recoginizer import DeadlyWeaponRecoginizer
from ikalog.utils.neuralnet.weapon import WeaponClassifier
import cv2
import numpy as np
import umsgpack
weapons = WeaponClassifier()
weapons.load_model_from_file()
abilities = GearPowerRecoginizer()
abilities.load_model_from_file()
abilities.knn_train()
class APIServer(object):
def _decode_deadly_weapons_image(self, payload):
h = payload['sample_height']
w = payload['sample_width']
img_bytes = payload['samples']
samples1 = cv2.imdecode(np.fromstring(img_bytes, dtype='uint8'), 1)
num_samples = int(samples1.shape[0] / h)
#
from http.server import HTTPServer, SimpleHTTPRequestHandler
import json
import logging
import time
import ikalog.constants
from ikalog.utils import *
from ikalog.utils.character_recoginizer import DeadlyWeaponRecoginizer
from ikalog.utils.neuralnet.weapon import WeaponClassifier
import cv2
import numpy as np
import umsgpack
weapons = WeaponClassifier()
weapons.load_model_from_file()
abilities = GearPowerRecoginizer()
abilities.load_model_from_file()
abilities.knn_train()
class APIServer(object):
def _decode_deadly_weapons_image(self, payload):
h = payload['sample_height']
w = payload['sample_width']
img_bytes = payload['samples']
samples1 = cv2.imdecode(np.fromstring(img_bytes, dtype='uint8'), 1)
num_samples = int(samples1.shape[0] / h)
