Masoud Masoumi Moghadam masouduut94

## json_parser_v5.py
    def output(self):
        output = {'video_details': self.video_details}
        result = list(self.frames.values())
        output['frames'] = [item.dic() for item in result]
        return output

## json_parser_v4.py
class BaseJsonParser(object):
    """
    This is the base class that returns __dict__ of its own
    it also returns the dicts of objects in the attributes that are list instances
    """

    def dic(self):
        # returns dicts of objects
        out = {}
        for k, v in self.__dict__.items():

## json_parser_v3.py
    def set_top_k(self, value):
        self.top_k_labels = value

    def frame_exists(self, frame_id: int):
        return frame_id in self.frames.keys()

    def add_frame(self, frame_id: int):
        # Use this function to add frames with index.
        if not self.frame_exists(frame_id):
            self.frames[frame_id] = Frame(frame_id)

## test_json_parser_v2.py
    def test_add_frame(self):
        frames_ids = [1, 2, 3, 4, 5]
        self.json_parser.set_top_k(0)
        for frame_id in frames_ids:
            self.json_parser.add_frame(frame_id)
        output = self.json_parser.output()
        output_ids = [frame['frame_id'] for frame in output['frames']]
        for frame_id in frames_ids:
            self.assertIn(frame_id, output_ids)

## test_json_parser.py
import unittest
import sys
from unittest.case import TestCase

sys.path.append('../..')
from json_parser.json_parser import *


class TestFrame(TestCase):

## json_parser.py
class JsonParser:
    def __init__(self, top_k_labels: int = 1):
        self.frames = {}
        self.video_details = dict(frame_width=None,
                                  frame_height=None,
                                  frame_rate=None,
                                  video_name=None)
        self.top_k_labels = top_k_labels

## basic_classes.py
class Label:
    """
    For each bounding box there are various categories with confidences. Label class keeps track of that information.
    """

    def __init__(self, category: str, confidence: float):
        self.category = category
        self.confidence = confidence


## rtsp_webserver.py
"""
This code handles the pedestrian detection service on specified camera.
Also provides stream images for clients.

"""

from os.path import join
from os import getenv, environ
from dotenv import load_dotenv
import argparse

## server_cfg.py
"""
Configuring deep learning models parameters in dictionary variables.
"""
import sys
from os.path import dirname, abspath, isfile

sys.path.append(dirname(dirname(abspath(__file__))))

from dotenv import load_dotenv
from utils.asserts import assert_in_env

## index.html
<html lang="en">
  <head>
    <title>Camera #1 </title>
  </head>
  <body>
    <h1>Floor 2 </h1>
    <img src="{{ url_for('video_feed') }}">
  </body>
</html>
	def output(self):
	output = {'video_details': self.video_details}
	result = list(self.frames.values())
	output['frames'] = [item.dic() for item in result]
	return output
	class BaseJsonParser(object):
	"""
	This is the base class that returns __dict__ of its own
	it also returns the dicts of objects in the attributes that are list instances
	"""

	def dic(self):
	# returns dicts of objects
	out = {}
	for k, v in self.__dict__.items():
	def set_top_k(self, value):
	self.top_k_labels = value

	def frame_exists(self, frame_id: int):
	return frame_id in self.frames.keys()

	def add_frame(self, frame_id: int):
	# Use this function to add frames with index.
	if not self.frame_exists(frame_id):
	self.frames[frame_id] = Frame(frame_id)
	def test_add_frame(self):
	frames_ids = [1, 2, 3, 4, 5]
	self.json_parser.set_top_k(0)
	for frame_id in frames_ids:
	self.json_parser.add_frame(frame_id)
	output = self.json_parser.output()
	output_ids = [frame['frame_id'] for frame in output['frames']]
	for frame_id in frames_ids:
	self.assertIn(frame_id, output_ids)
	import unittest
	import sys
	from unittest.case import TestCase

	sys.path.append('../..')
	from json_parser.json_parser import *


	class TestFrame(TestCase):
	class JsonParser:
	def __init__(self, top_k_labels: int = 1):
	self.frames = {}
	self.video_details = dict(frame_width=None,
	frame_height=None,
	frame_rate=None,
	video_name=None)
	self.top_k_labels = top_k_labels
	class Label:
	"""
	For each bounding box there are various categories with confidences. Label class keeps track of that information.
	"""

	def __init__(self, category: str, confidence: float):
	self.category = category
	self.confidence = confidence
	"""
	This code handles the pedestrian detection service on specified camera.
	Also provides stream images for clients.

	"""

	from os.path import join
	from os import getenv, environ
	from dotenv import load_dotenv
	import argparse
	"""
	Configuring deep learning models parameters in dictionary variables.
	"""
	import sys
	from os.path import dirname, abspath, isfile

	sys.path.append(dirname(dirname(abspath(__file__))))

	from dotenv import load_dotenv
	from utils.asserts import assert_in_env
	<html lang="en">
	<head>
	<title>Camera #1 </title>
	</head>
	<body>
	<h1>Floor 2 </h1>
	<img src="{{ url_for('video_feed') }}">
	</body>
	</html>