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pool_engine.py
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pool_engine.py
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#
# Cloudlet Infrastructure for Mobile Computing
# - Task Assistance
#
# Author: Zhuo Chen <zhuoc@cs.cmu.edu>
# Roger Iyengar <iyengar@cmu.edu>
#
# Copyright (C) 2011-2013 Carnegie Mellon University
# 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.
#
from gabriel_server import cognitive_engine
from gabriel_protocol import gabriel_pb2
import numpy as np
import pool_cv
import cv2
import instruction_pb2
import logging
ENGINE_NAME = "instruction"
# Max image width and height
IMAGE_MAX_WH = 1920
logger = logging.getLogger(__name__)
class PoolEngine(cognitive_engine.Engine):
def handle(self, from_client):
if from_client.payload_type != gabriel_pb2.PayloadType.IMAGE:
return cognitive_engine.wrong_input_format_error(
from_client.frame_id)
engine_fields = cognitive_engine.unpack_engine_fields(
instruction_pb2.EngineFields, from_client)
img_array = np.asarray(bytearray(from_client.payload), dtype=np.int8)
img = cv2.imdecode(img_array, -1)
if max(img.shape) > IMAGE_MAX_WH:
resize_ratio = float(IMAGE_MAX_WH) / max(img.shape[0], img.shape[1])
img = cv2.resize(img, (0, 0), fx=resize_ratio, fy=resize_ratio,
interpolation=cv2.INTER_AREA)
result_wrapper = gabriel_pb2.ResultWrapper()
result_wrapper.frame_id = from_client.frame_id
result_wrapper.status = gabriel_pb2.ResultWrapper.Status.SUCCESS
objects = pool_cv.process(img)
if objects is not None:
cue, CO_balls, pocket = objects
result = gabriel_pb2.ResultWrapper.Result()
result.payload_type = gabriel_pb2.PayloadType.TEXT
result.engine_name = ENGINE_NAME
speech = pool_cv.get_guidance(img, cue, CO_balls, pocket)
logger.info(speech)
result.payload = speech.encode(encoding="utf-8")
result_wrapper.results.append(result)
engine_fields.update_count += 1
result_wrapper.engine_fields.Pack(engine_fields)
return result_wrapper