def actually_solve_math_function(self, math_function):
'''
:param math_function:
:return:
'''
# TODO: DEBUGGING
print "Solving:", get_math_function_as_string(math_function),
''' If the function is already just a number, return it. '''
has_operations = False
for x in range(len(math_function)):
current = math_function[x]
if current == '^' or current == '*' or current == '/' or current == '+' or current == '-':
has_operations = True
if not has_operations:
return math_function[0]
else:
if self.solve_for_operator('^', math_function) == False:
return False
self.solve_for_operator('*', math_function)
if self.solve_for_operator('/', math_function) == False:
return False
self.solve_for_operator('+', math_function)
self.solve_for_operator('-', math_function)
if len(math_function) != 1:
print "Critical Error, the math function didn't have a length of 1."
MyTimer.terminate_program()
else:
return math_function[0]
def __init__(self, can, poids, coeff, py0, px0):
self.can = can
self.poids = poids
self.py0 = py0
self.px0 = px0
self.py = py0
self.px = px0
self.coeff = coeff
self.moov = 0
self.timer = MyTimer(0.001, self.deplace)
def attempt_solution(self):
expression = ""
if self.data_constant[0]:
expression = "f(x) = " + str(self.data[0][0])
elif self.data_constant[1]:
expression = "f(x) = " + str(self.data[0][0]) + " + x * " + str(self.data[1][0])
elif self.data_constant_multiplier[0]:
expression = "f(x) = " + str(self.data[0][0]) + " * (" + str(self.data_multiplier[0][0]) + " ^ x)"
if expression != "":
print expression
MyTimer.terminate_program()
def __init__(self, can, poids, coeff, py0, px0):
self.can = can;
self.poids = poids
self.py0 = py0
self.px0 = px0
self.py = py0
self.px = px0
self.coeff = coeff
self.moov = 0
self.timer = MyTimer(0.001, self.deplace)
class ObjetDeLaVie:
"""Unobjet avec les propriete Newton"""
def __init__(self, can, poids, coeff, py0, px0):
self.can = can
self.poids = poids
self.py0 = py0
self.px0 = px0
self.py = py0
self.px = px0
self.coeff = coeff
self.moov = 0
self.timer = MyTimer(0.001, self.deplace)
def shoot(self, vitesse, angle):
self.angle = angle
self.vitesse = vitesse
self.vx = cos(self.angle * 0.0174) * vitesse
self.vy = sin(self.angle * 0.0174) * vitesse
self.tps = 0
self.timer.start()
def deplace(self):
self.moov = 1
if (self.vitesse > 2):
if (self.py > 340):
self.timer.stop()
self.px0 = self.px
self.py0 = 340
self.vitesse *= self.coeff
self.shoot(self.vitesse, self.angle)
if (self.px < -20):
self.vx = -self.vx
self.px = -20
self.angle = self.angle - 2 * (self.angle - 90)
self.px0 = -20 - self.px0
elif (self.px > 1000):
self.vx = -self.vx
self.px = 1000
self.angle = self.angle - 2 * (self.angle - 90)
self.px0 = 2 * 1000 - self.px0
if (self.px >= -20 and self.px <= 1000):
self.px = self.vx * self.tps + self.px0
self.py = (
(self.poids * 9.81) /
2) * self.tps * self.tps - self.vy * self.tps + self.py0
self.can.coords(self.image, self.px, self.py)
self.tps += 0.018
else:
self.moov = 0
self.timer.stop()
class ObjetDeLaVie:
"""Unobjet avec les propriete Newton"""
def __init__(self, can, poids, coeff, py0, px0):
self.can = can;
self.poids = poids
self.py0 = py0
self.px0 = px0
self.py = py0
self.px = px0
self.coeff = coeff
self.moov = 0
self.timer = MyTimer(0.001, self.deplace)
def shoot(self, vitesse, angle):
self.angle = angle
self.vitesse = vitesse
self.vx = cos(self.angle * 0.0174) * vitesse
self.vy = sin(self.angle * 0.0174) * vitesse
self.tps = 0
self.timer.start()
def deplace(self):
self.moov = 1
if (self.vitesse > 2):
if (self.py > 340):
self.timer.stop()
self.px0 = self.px
self.py0 = 340
self.vitesse *= self.coeff
self.shoot(self.vitesse, self.angle)
if (self.px < -20):
self.vx = -self.vx
self.px = -20
self.angle = self.angle - 2*(self.angle - 90)
self.px0 = -20 - self.px0
elif (self.px > 1000):
self.vx = -self.vx
self.px = 1000
self.angle = self.angle - 2*(self.angle - 90)
self.px0 = 2*1000 - self.px0
if (self.px >= -20 and self.px <= 1000):
self.px = self.vx*self.tps + self.px0
self.py = ((self.poids*9.81)/2)*self.tps*self.tps - self.vy*self.tps + self.py0
self.can.coords(self.image, self.px, self.py)
self.tps += 0.018
else:
self.moov = 0
self.timer.stop()
lsqe = el.LSqEllipse()
lsqe.fit(data)
center, width, height, phi = lsqe.parameters()
a = max(width, height)
b = min(width, height)
area = math.pi * a * b
eccentricity = pow((1 - (b / a)**2), 1 / 2)
pore_opening_degree = b / a
return a, b, area, eccentricity, pore_opening_degree
if __name__ == "__main__":
import os
base_path = r"C:\Users\LJY\Desktop\第一篇小论文-第二阶段\cropped_stomata\cropped_det"
# 计时开始
mytime = MyTimer.MyTimer()
mytime.start()
# 先统计一下
path = r"D:\Mask_RCNN\mask_rcnn\cropped_stomata\first_time"
# image_num 是 f
image_num = len([
lists for lists in os.listdir(path)
if os.path.isdir(os.path.join(path, lists))
])
# pore_num 是 s，表示总共有多少个匹配气孔
pore_num = 0
for img in range(image_num):
dirname = r"D:\Mask_RCNN\mask_rcnn\cropped_stomata\first_time\{}".format(
img)
filenum = len([
print __name__, "start ..." max = 20 fig = plt.figure() ax = fig.add_subplot(111) # some X and Y data li, = ax.plot(x, y, 'r.') # draw and show it fig.canvas.draw() plt.ylim((-5,25)) plt.show(block=False) HOST, PORT = "192.168.0.123", 9998 timer = MyTimer.MyTimer() print timer print "start server" # Create the server, binding to localhost on port 9999 server = SocketServer.TCPServer((HOST, PORT), MyTCPHandler) server_thread = threading.Thread(target=server.serve_forever) # Exit the server thread when the main thread terminates server_thread.daemon = True server_thread.start() print "start drawer" drawer = PlotDrawer() drawer_thread = threading.Thread(target=drawer.run) # Exit the server thread when the main thread terminates
def run(self):
#获取全局变量数据并更新全局数据
self.info = gl.GL_VInfo
self.model = gl.GL_Model
self.isEnd = False
gl.GL_TalScore = 0
#清空全局队列
while gl.GL_CurScoreQueue.empty() == False:
gl.GL_CurScoreQueue.get()
startTimer = MyTimer()
startTimer.start(1000) #开始计时
temp = 0
for oneInfo in self.info:
timeid = oneInfo['timeid'] #演示视频播放时间ms
reactime = float(oneInfo['reactime']) #反应时间
poseSocre = oneInfo['score'] #分数
posepoints = oneInfo['posepoints'] #关节点信息
posepoints = mxnet.nd.array(posepoints) #类型转换
temp += 1
print('*************这是第{}次'.format(temp))
print("timeid={}".format(timeid))
startTimer.resetWaitTime(timeid) #设置等待时间
startTimer.waitTimeOut() #等待时间，相当于 sleep
self.now_to_getImages.emit() #发送截取视频图像的信号
#等待截取的图片存入全局变量
while bool(gl.GL_Images == []) | bool(
gl.GL_Images.__len__() < gl.GL_Images_Length):
if self.isEnd == True: #当需要线程关闭时，退出
break
time.sleep(0.02)
if self.isEnd == True: #当需要线程关闭时，退出
break
images = gl.GL_Images #获取全局变量 (截取的图片list)
#跟新全局变量数据
gl.GL_Images = []
gl.GL_Images_Length = 0
use_gpu = False
maxScore = 0
score = 0
#给每一个图片匹配示范骨架，获取最大分数
for image in images:
if self.isEnd == True:
break
playerPre, playerImage = net.detection(self.model, image,
use_gpu) #模型预测骨架
if playerPre != None:
playerDis, playerSkeleton = tools.normalization(
playerPre['pred_coords'][0]) #结果归一化
score = tools.matching(playerSkeleton,
posepoints,
use_gpu=use_gpu) #计算匹配结果
if maxScore < score:
maxScore = score
if self.isEnd == True:
break
print("mxScore={}".format(maxScore))
#当分数超过10，认定匹配成功
if maxScore > 10:
#将分数更新在全局变量中
gl.GL_CurScoreQueue.put(poseSocre)
gl.GL_TalScore += poseSocre
self.update_date.emit(poseSocre) #发送信号，传递动作得分
else:
self.update_date.emit(0) #发送信号，传递动作得分
startTimer.end()
# |-test
# |-|-test
# |-|-|-***.png
# |-|=annotations
# |-|-|-***.json
dataset_test.load_coco(r"D:\Mask_RCNN\mask_rcnn\测试银杏的参数数据集\test2017",
"test2017")
dataset_test.prepare()
# image_ids 是记录test_datasets中共有多少张图片
image_ids = dataset_test.image_ids
IoU_all_photos = np.zeros((1, len(image_ids)))
all_statistic = np.zeros((2, len(image_ids)))
count_statistic = np.zeros((2, len(image_ids)))
# 计时
t1 = MyTimer.MyTimer()
t1.start()
# 测试集
for f in range(len(image_ids)):
image_id = f
info = dataset_test.image_info[image_id]
print("image ID: {}.{} ({}) {}".format(
info["source"], info["id"], image_id,
dataset_test.image_reference(image_id)))
# 原demo在使用图像之前已经对图像进行了裁剪 具体代码在model的1224行
image, image_meta, gt_class_id, gt_bbox, gt_mask = modellib.load_image_gt(
dataset_test, config, image_id, use_mini_mask=False)
# image 是 3D图像 [image]是4-D列表 len([image]) = 1 [image]代表把整个图像作为一个batch处理
results = model.detect([image], verbose=1)
# 这里的model.detect
__author__ = 'utarsuno'
# Regular Expression library being using to parse Strings (specifically to split a string by a denominator).
import re
# Self made library to derive the derivatives from the data.
from Derivative import Derivative
# Self made library to generate all possible functions to a character limit in hopes of finding a match to the data.
from FunctionGenerator import FunctionGenerator
# Self made library used for timing the program's speed.
import MyTimer
''' Obtain the data to analyze. '''
user_input = raw_input("Enter the numbers to be analyzed: ")
MyTimer.initiate_timer()
''' Parse the data based off commas. '''
user_input = re.split(",", user_input)
''' Convert the data from a string array to an int array '''
user_input = map(int, user_input)
''' Make sure user input is more than one number. '''
if len(user_input) <= 1:
print "Too few inputs provided. Program will now terminate."
MyTimer.terminate_program()
derivative = Derivative(user_input)
data = derivative.get_data()
def get_camera_images(self):
'''
截取摄像头图片，存入全局变量中
'''
reactTimer = MyTimer()
waitTimer = MyTimer()
reactTime = 0.5
imageSize = (640, 480)
images = []
reactTime = int(reactTime * 1000)
reactTimer.start(reactTime)
waitTime = 100
while reactTimer.isTimeOut() == False:
waitTimer.start(waitTime)
flag, image = self.cap.read()
image = cv2.resize(image, imageSize)
images.append(image)
waitTimer.waitTimeOut()
gl.GL_Images = images
gl.GL_Images_Length = images.__len__()
print("length={}".format(images.__len__()))
import sys,MyTimer
reps = 10000
repslist = range(reps)
def forLoop():
res = []
for x in repslist:
res.append(x + 10)
return res
def listComp():
return [x + 10 for x in repslist]
def mapCall():
return list(map(lambda x: x + 10,repslist))
def genExpr():
return list(x + 10 for x in repslist)
def genFunc():
def gen():
for x in repslist:
yield x + 10
return list(gen())
print(sys.version)
for test in (forLoop,listComp,mapCall,genExpr,genFunc):
elapsed,result = MyTimer.timer(test)
print ('-'*33)
print('%-9s: %.5f => [%s...%s]' %(test.__name__,elapsed,result[0],result[-1]))
def attempt_to_find_math_function_for_data(self):
#NOTE IN THE FUTURE HAVE A PARAMETER FOR NUMBER OF DIGITS: character_limit
"""
There are X main steps to this program.
0x1. Generate random sudo math functions.
0x2. Ignore sudo math functions that are invalid.
0x3. Prepare the sudo math function conversion.
0x4. Convert the sudo math function to a math function and test it.
:return:
The math function if it was found. Otherwise return 'f(x)'.
"""
character_limit = 6
''' 0x1 '''
# This is the maximum number of different possible characters in the sudo math function.
# TODO: Change this variable name to sudo characters.
number_of_unique_characters = 5
# Calculate the number of possible sudo functions.
number_of_max_sudo_functions = number_of_unique_characters
for x in range(character_limit - 1):
number_of_max_sudo_functions *= number_of_unique_characters
number_of_sudo_functions = 0
# Go through each possible sudo function and test it.
for x in range(number_of_max_sudo_functions):
# Generate a single permutation.
sudo_math_function = DecimalToAnyBaseArray(x, number_of_unique_characters)
# Once the sudo function is generated, map the numbers to their respective character.
for y in range(len(sudo_math_function)):
sudo_math_function[y] = entity_map(sudo_math_function[y])
''' 0x2 '''
if self.verify_sudo_math_function_dbg(sudo_math_function):
''' 0x3 '''
#sudo_math_function = self.prepare_sudo_math_function_for_converstion(sudo_math_function)
''' 0x4 '''
if self.convert_sudo_math_function_to_math_functions_and_test_them(sudo_math_function):
MyTimer.terminate_program()
print "f(x) =", get_math_function_as_string(sudo_math_function)
number_of_sudo_functions += 1
'''
Max number of subs data
zero: 2 ^ x - 1
no zero: x ^ 2 + 1 + x
1: 1
2: 3
3: 7
4: 14
5: 36
6: 116
7: 379
8: 1134
___________
NEW:
1:
2:
3:
4:
5:
6:
7:
8:
'''
print "Max Number of Sudo Functions:", number_of_max_sudo_functions, "\tActual:", number_of_sudo_functions
for a in range(len(self.error_list)):
print a, "\t", self.error_list[a]