pietrocolombo

import threading
import queue
import time
import random

# Producer class
class Producer(threading.Thread):
    def __init__(self, buffer):
        super().__init__()
        self.buffer = buffer

pietrocolombo

pietrocolombo

pietrocolombo

class optimization:

	def __init__(self, enc_vector, gps_vector, ratio_t2ml, ratio_t2mr,
		abs_zero_initial, abs_first_coef, abs_second_coef, abs_third_coef,
		abs_first_exp, abs_second_exp, abs_third_exp, orientation_start):

		self.enc_vector = enc_vector
		self.gps_vector = gps_vector
		self.ratio_t2ml = ratio_t2ml
		self.ratio_t2mr = ratio_t2mr

pietrocolombo

# pip install opencv-python
import cv2
import queue
import threading
import time

class Video(threading.Thread):
    def __init__(self, camera, interval, path) -> None:
        threading.Thread.__init__(self)
        self._cam = cv2.VideoCapture(camera)

pietrocolombo

from reportlab.pdfgen import canvas
from reportlab.lib.units import mm
from reportlab.lib.pagesizes import A4
from reportlab.pdfbase.ttfonts import TTFont
from reportlab.pdfbase import pdfmetrics
from reportlab.lib.enums import TA_LEFT, TA_CENTER

from reportlab.lib.styles import ParagraphStyle
from reportlab.platypus import Paragraph

pietrocolombo

class DataDevice(Resource):
    def put(self):
        """ it receives the data from the devices and puts them in the database

        :return:
        """
        args = device_data_put_args.parse_args()
        # check if the device exist
        device = Device.query.get(args['id_device'])
        if device is None:

pietrocolombo

import cv2
import os
  
# Read the video from specified path
cam = cv2.VideoCapture("/content/gdrive/MyDrive/Foto & Video/2021/Casargo/Volo 2/DJI_0049.MP4")
  
try:
      
    # creating a folder named data
    if not os.path.exists('/content/gdrive/MyDrive/Foto & Video/2021/Casargo/Volo 2/DJI_0049'):

pietrocolombo

import json
import requests
import urllib


TOKEN = ""
URL = "https://api.telegram.org/bot{}/".format(TOKEN)
USERNAME_BOT = ""

pietrocolombo

counting = {}

for activity in df['class'].unique():
    counting[activity] = {}
    activity_df = df[df['class'] == activity]
    n_instance = activity_df.shape[0]
    for user in df['user'].unique():
        counting[activity][user] = activity_df[activity_df['user'] == user].shape[0]/n_instance*100

bars = []