def get_score(self):
"""盘面打分"""
try:
return self.info_handler.info['score'][1].cp
except Exception as e:
logging.warning(utils.get_trace())
return -1
def post(self):
"""post请求处理"""
try:
result = self.execute()
except:
logging.error('execute fail ' + utils.get_trace())
result = {'code': 1, 'msg': '查询失败'}
logging.info('API RES[' + self.request.path + '][' +
self.request.method + '][' + str(result['code']) + '][' +
str(result['msg']) + ']')
self.write(json.dumps(result))
def execute(self):
"""执行业务逻辑"""
logging.info('API REQUEST INFO[' + self.request.path + '][' +
self.request.method + '][' + self.request.remote_ip +
'][' + str(self.request.arguments) + ']')
img_file = self.get_argument('img_file', '')
tag_img = int(self.get_argument('tag_img', 0)) # 是否在图片上标记目标位置
detect_face = int(self.get_argument('detect_face', 0)) # 是否识别人脸
tts_caption = self.get_argument('tts_caption', '') # 是否为图像描述合成语音
if img_file == '':
return {'code': 2, 'msg': 'img_file不能为空', 'data': {}}
res = []
caption = ''
try:
# 图像目标检测
res = darknet.detect(img_file,
tag_img=tag_img,
detect_face=detect_face)
#print(res)
# 图像描述
caption = darknet.caption(res)
# 图像描述语音合成
tts_url = ''
if tts_caption:
s = caption[tts_caption]
voice_file = _tts._get_cache(s)
if not voice_file:
voice_file = _tts.get_speech(s)
cache_file = _tts._set_cache(s, voice_file)
if cache_file:
voice_file = cache_file
tts_url = voice_file.replace(IMG_PATH, IMG_URL)
except:
logging.error('execute fail [' + img_file + '] ' +
utils.get_trace())
return {'code': 5, 'msg': 'detect fail', 'data': {}}
# 组织返回格式
url = img_file.replace(IMG_PATH, IMG_URL)
return {
'code': 0,
'msg': 'success',
'data': {
'url': url,
'objects': res,
'caption': caption,
'tts_caption': tts_url
}
}
def get_action(self, board):
action = 0
while True:
san = input("Your move: ")
try:
action = board.san_to_action(san)
except Exception as e:
logging.warning(utils.get_trace())
action = -1
logging.info("Human action: %s %d,%s" % (board.current_player_name.upper(), action, board.action_to_move(action)))
if action in board.availables: # action legal check
break
else:
print("invalid action ! [{}] [{}]".format(action, board.actions_to_sans(board.availables)))
return action
def load_model(self, model_file):
"""重新加载模型(仅用于selfplay时load new model)"""
try:
#net_params = utils.pickle_load(model_file)
self.saver.restore(self.session, model_file)
self.load_model_done = True
except:
logging.error("load_model fail! {}\t{}".format(
model_file, utils.get_trace()))
self.load_model_done = False
if os.path.exists(
model_file
) and self.load_model_done is False: #鏂囦欢瀛樺湪鍗村鍦ㄥけ璐ユ椂缁堟杩愯
exit(-1)
return self.load_model_done
def load_model(self, model_file):
"""重新加载模型(仅用于selfplay时load new model)"""
try:
#net_params = pickle.load(open(model_file, 'rb'), encoding='bytes') #iso-8859-1')
net_params = utils.pickle_load(model_file)
self.model.set_weights(net_params)
self.load_model_done = True
except:
logging.error("load_model fail! {}\t{}".format(
model_file, utils.get_trace()))
self.load_model_done = False
if os.path.exists(
model_file
) and self.load_model_done is False: #鏂囦欢瀛樺湪鍗村鍦ㄥけ璐ユ椂缁堟杩愯
exit(-1)
return self.load_model_done
def get_action(self, board, return_prob=0, return_ponder=0, return_score=0):
logging.info("__get_action__ {}".format(len(board.book_variations['all'])))
action = -1
ponder = -1
score = -1
try:
self.engine.position(board.base)
res = self.engine.go(movetime=2000)
# print(res, self.info_handler.info)
action = board.move_to_action(res.bestmove)
ponder = board.move_to_action(res.ponder)
score = self.get_score()
except Exception as e:
logging.warning(utils.get_trace())
logging.info("Stockfish action: %s %d,%s ponder: %s" % (board.current_player_name.upper(), action, board.action_to_move(action), board.action_to_move(ponder)))
probs = np.zeros(board.action_ids_size)
probs[action] = 1.0
if return_prob and return_ponder and return_score:
return action, probs, ponder, score
if return_prob:
return action, probs
return action
def execute(self):
"""执行业务逻辑"""
logging.info('API REQUEST INFO[' + self.request.path + '][' +
self.request.method + '][' + self.request.remote_ip +
'][' + str(self.request.arguments) + ']')
img_file = self.get_argument('img_file', '')
if img_file == '':
return {'code': 2, 'msg': 'img_file不能为空'}
res = {}
try:
ret, msg, res = dogcat_infer.infer(img_file)
if ret != 0:
logging.error('execute fail [' + img_file + '] ' + msg)
return {'code': 4, 'msg': '查询失败'}
except:
logging.error('execute fail [' + img_file + '] ' +
utils.get_trace())
return {'code': 5, 'msg': '查询失败'}
# 组织返回格式
return {'code': 0, 'msg': 'success', 'data': res}
def show_camera_face_window(camera_data,
warning_faceids=['mjs', 'zhu', 'yjy', 'zn']):
"""创建视频人脸监控windows窗口"""
# create window
face_imgs, face_labels = [], []
for i in range(MAX_FACE):
face_imgs.append(
sg.Image(filename=CUR_PATH + '/../data/image/kuang.png',
size=(80, 80),
key='face' + str(i)))
face_labels.append(sg.Text('', size=(14, 1), key='label' + str(i)))
layout = [[
sg.Image(filename=CUR_PATH + '/../data/image/pic.png',
size=(600, 400),
key='camera')
], face_imgs, face_labels,
[sg.Text('filename', size=(100, 1), key='filename')]]
window = sg.Window('视频人脸监控',
return_keyboard_events=True,
default_element_size=(30, 2),
location=(0, 0),
use_default_focus=False).Layout(layout).Finalize()
# window.FindElement('filename').Update(str(time.time()))
# show camera_data
while True:
event, values = window.Read(timeout=5) # wait 5ms for a GUI event
if event is None or event == 'Exit': # exit
break
while True: # 刷新页面数据
logging.debug('___show_camera_face_window__')
if camera_data['camera']['filename']:
# print(camera_data['camera']['filename'])
window.FindElement('camera').Update(
filename=camera_data['camera']['filename'])
window.FindElement('filename').Update(
camera_data['camera']['filename'])
try:
# show face
for i in range(len(camera_data['face']['list'])):
face = camera_data['face']['list'][i]
window.FindElement('face' + str(i)).Update(
face['filename'])
window.FindElement('label' + str(i)).Update(
face['faceid'] + ' ' +
str(round(face['weight'] / face['cnt'], 3)))
except: # will get exception when Queue is empty
logging.warning('refresh window fail! {}'.format(
utils.get_trace()))
break
window.Refresh()
# 重要人物刚出现时报警
if len(camera_data['face']['list']
) > 0 and time.time() - camera_data['face']['list'][-1][
'lasttime'] < 2.0 and camera_data['face']['list'][
-1]['faceid'] in warning_faceids:
# utils.play_sound('warning0.wav')
Thread(target=utils.play_sound, daemon=True).start()
logging.debug('___show_camera_face_window__ done')
# close window
window.Close()
def execute(self):
"""执行业务逻辑"""
logging.info('API REQUEST INFO[' + self.request.path + '][' +
self.request.method + '][' + self.request.remote_ip +
'][' + str(self.request.arguments) + ']')
session_id = self.get_argument('session_id', '')
res = {
'session_id': session_id,
'player': -1,
'step': 0,
'move': '',
'san': '',
'end': False,
'winner': -1,
'curr_player': 0,
'state': {},
'ponder': '',
'score': -1
}
move = self.get_argument('move', '')
if session_id == '':
return {'code': 2, 'msg': 'session_id不能为空', 'data': res}
try:
# 1.新的对局
session = {}
if session_id not in self.games:
logging.info("[{}] init new game!".format(session_id))
# plays id
session['human_player_id'] = int(
self.get_argument('human_player_id', '1')) # human默认执黑
session['ai_player_id'] = (session['human_player_id'] +
1) % 2 # ai与human相反
session['players'] = {
session['human_player_id']: 'Human',
session['ai_player_id']: 'AI'
}
session['step'] = 0
session['actions'], session['mcts_probs'] = [], []
# 初始化棋盘
session['game'] = Game()
session['game'].board.init_board()
# 初始化AI棋手
#session['ai_player'] = AIPlayer(self.best_policy.policy_value_fn, n_playout=50)
session['ai_player'] = StockfishPlayer()
self.games[session_id] = session
else:
session = self.games[session_id]
# clear old games
for k in list(self.games.keys()):
if int(time.time()
) - int(k) / 1000 > 60 * 40: # 超过40分钟的session清理
del (self.games[k])
logging.warning("[{}] timeout clear!".format(k))
# 2.get ai move
res['players'], res['human_player_id'], res[
'ai_player_id'] = session['players'], session[
'human_player_id'], session['ai_player_id']
res['curr_player'] = session['game'].board.current_player_id
res['availables'] = [
session['game'].board.action_to_move(act)
for act in session['game'].board.availables
]
res['state'] = session['game'].board.state()
action = -1
if res['curr_player'] == session[
'ai_player_id']: # 轮到ai时，忽略传入的move参数
action, probs, ponder, res['score'] = session[
'ai_player'].get_action(session['game'].board,
return_prob=1,
return_ponder=1,
return_score=1)
move = session['game'].board.action_to_move(action)
res['ponder'] = session['game'].board.action_to_move(ponder)
logging.info(
"[{}] {} AI move: {} Score: {} Ponder: {}".format(
session_id, res['curr_player'], move, res['score'],
res['ponder']))
# save state
session['actions'].append(
session['game'].board.current_actions())
session['mcts_probs'].append(probs)
else: # 轮到human走
if len(move) < 4: # 没有传入move
logging.info("[{}] {} Human need give move !".format(
session_id, res['curr_player']))
return {'code': 2, 'msg': '轮到人类走子', 'data': res}
logging.info("[{}] {} Human move: {}".format(
session_id, res['curr_player'], move))
action = session['game'].board.move_to_action(move)
if action not in session[
'game'].board.availables: # human action不合法
logging.info(
"[{}] {} Human action ({},{}) invalid !".format(
session_id, res['curr_player'], move, action))
return {
'code': 3,
'msg': '错误的落子位置:{}'.format(move),
'data': res
}
# save state
session['actions'].append(
session['game'].board.current_actions())
probs = np.zeros(session['game'].board.action_ids_size)
probs[action] = 0.01
session['mcts_probs'].append(probs)
# 3.do move
if len(move) >= 4 and action != -1:
# do move
res['san'] = session['game'].board.move_to_san(move)
session['game'].board.do_move(action) # do move
try:
if len(res['ponder']) > 2:
res['ponder'] = session['game'].board.move_to_san(
res['ponder'])
except:
logging.warning(utils.get_trace())
session['step'] += 1
res['player'], res['move'], res['step'] = res[
'curr_player'], move, session['step']
res['end'], res['winner'] = session['game'].board.game_end()
res['curr_player'] = session['game'].board.current_player_id
res['availables'] = [
session['game'].board.action_to_move(act)
for act in session['game'].board.availables
]
res['state'] = session['game'].board.state(
) # res['state'][move[:2]] + move[:2]
# save state -> databuffer
if res['end']:
# 从当前玩家视角确定winner
winners_z = np.zeros(
len(session['game'].board.book_variations['all']))
if res['winner'] != -1: # 不是和棋
for i in range(len(winners_z)):
if (i + res['winner']) % 2 == 0:
winners_z[i] = 1.0 # 更新赢家步骤位置=1
else:
winners_z[i] = -1.0 # 更新输家步骤位置=-1
play_data = list(
zip(session['actions'], session['mcts_probs'],
winners_z))[:]
data_file = session['game']._get_databuffer_file(
event='vs',
winner=res['winner'],
white=session['players'][0],
black=session['players'][1],
step_num=len(play_data))
utils.pickle_dump(play_data, data_file)
logging.info(
"api vs play save to databuffer: {}".format(data_file))
return {'code': 0, 'msg': 'success', 'data': res}
except:
logging.error('execute fail [' + str(move) + '][' + session_id +
'] ' + utils.get_trace())
return {'code': 5, 'msg': '请求失败', 'data': res}
# 组织返回格式
return {'code': 0, 'msg': 'success', 'data': res}
