def init():
if 'toto' in request.form:
dataset_name = request.form['toto']
else:
dataset_name = "pima-indians-diabetes.csv"
import data_reader
dataset = data_reader.reader(dataset_name)
return render_template('init.html', value2=dataset)
#--------------------------
parser = argparse.ArgumentParser()
parser.add_argument('--ticker', help="The symbol you want to predict")
parser.add_argument(
'--interval', help="time interval for data collection: 30m, 60m, 90m, 1d")
parser.add_argument('--n_run', help="number of simulations to run")
args = parser.parse_args()
if not args.interval:
interval = "1d"
else:
interval = args.interval
df = data_reader.reader(args.ticker, interval)
if not args.n_run:
simulation_size = 10
else:
simulation_size = int(args.n_run)
#--------------------------
minmax = MinMaxScaler().fit(df.iloc[:, 4:5].astype('float32')) # Close index
df_log = minmax.transform(df.iloc[:, 4:5].astype('float32')) # Close index
df_log = pd.DataFrame(df_log)
df_log.head()
num_layers = 1
size_layer = 128
def my_form_post():
import data_reader
dataset = data_reader.reader()
return render_template('init.html', value2=dataset)
import numpy as np
import netpart
import data_reader
import model as M
import tensorflow as tf
import cv2
import time
import os
#if not os.path.exists('./model/'):
# os.mkdir('./model/')
reader = data_reader.reader(height=720,width=1280,scale_range=[0.8,1.2])
def draw(img,c,b,multip,name):
c = c[0]
b = b[0]
row,col,_ = b.shape
# print(b.shape,c.shape)
# print(row,col)
for i in range(row):
for j in range(col):
# print(i,j)
if c[i][j][0]>=-0.05:
#print (c.max())
x = int((b[i][j][0]+j+1/2)*multip)
y = int((b[i][j][1]+i+1/2)*multip)
w = int(b[i][j][2]*640)
h = int(b[i][j][3]*480)
cv2.rectangle(img,(x-w//2,y-h//2),(x+w//2,y+h//2),(0,255,0),2)
import netpart
import data_reader
import model as M
import tensorflow as tf
import cv2
import time
import myconvertmod as cvt
import os
if not os.path.exists('./model/'):
os.mkdir('./model/')
reader = data_reader.reader(height=480,
width=640,
scale_range=[0.05, 2.5],
lower_bound=3,
upper_bound=7,
index_multiplier=2)
def draw(img, c, b, multip, name):
c = c[0]
b = b[0]
row, col, _ = b.shape
# print(b.shape,c.shape)
# print(row,col)
for i in range(row):
for j in range(col):
# print(i,j)
if c[i][j][0] > -0.5:
x = int(b[i][j][0]) + j * multip + multip // 2
import numpy as np
import netpart
import data_reader
import model as M
import tensorflow as tf
import cv2
import time
import os
#if not os.path.exists('./model/'):
# os.mkdir('./model/')
reader = data_reader.reader(height=480,width=640,scale_range=[0.7,1.2])
def draw(img,c,b,multip,name):
c = c[0]
b = b[0]
row,col,_ = b.shape
# print(b.shape,c.shape)
# print(row,col)
for i in range(row):
for j in range(col):
# print(i,j)
if c[i][j][0]>=-0.05:
#print (c.max())
x = int((b[i][j][0]+j+1/2)*multip)
y = int((b[i][j][1]+i+1/2)*multip)
w = int(b[i][j][2]*640)
h = int(b[i][j][3]*480)
cv2.rectangle(img,(x-w//2,y-h//2),(x+w//2,y+h//2),(0,255,0),2)