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)