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"""
References:
https://medium.com/analytics-vidhya/creating-a-custom-logging-mechanism-for-real-time-object-detection-using-tdd-4ca2cfcd0a2f
"""
import json
from os import makedirs
from os.path import exists, join
from datetime import datetime
class JsonMeta(object):
HOURS = 3
MINUTES = 59
SECONDS = 59
PATH_TO_SAVE = 'LOGS'
DEFAULT_FILE_NAME = 'remaining'
class BaseJsonLogger(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():
if hasattr(v, 'dic'):
out[k] = v.dic()
elif isinstance(v, list):
out[k] = self.list(v)
else:
out[k] = v
return out
@staticmethod
def list(values):
# applies the dic method on items in the list
return [v.dic() if hasattr(v, 'dic') else v for v in values]
class Label(BaseJsonLogger):
"""
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
class Bbox(BaseJsonLogger):
"""
This module stores the information for each frame and use them in JsonParser
Attributes:
labels (list): List of label module.
top (int):
left (int):
width (int):
height (int):
Args:
bbox_id (float):
top (int):
left (int):
width (int):
height (int):
References:
Check Label module for better understanding.
"""
def __init__(self, bbox_id, top, left, width, height):
self.labels = []
self.bbox_id = bbox_id
self.top = top
self.left = left
self.width = width
self.height = height
def add_label(self, category, confidence):
# adds category and confidence only if top_k is not exceeded.
self.labels.append(Label(category, confidence))
def labels_full(self, value):
return len(self.labels) == value
class Frame(BaseJsonLogger):
"""
This module stores the information for each frame and use them in JsonParser
Attributes:
timestamp (float): The elapsed time of captured frame
frame_id (int): The frame number of the captured video
bboxes (list of Bbox objects): Stores the list of bbox objects.
References:
Check Bbox class for better information
Args:
timestamp (float):
frame_id (int):
"""
def __init__(self, frame_id: int, timestamp: float = None):
self.frame_id = frame_id
self.timestamp = timestamp
self.bboxes = []
def add_bbox(self, bbox_id: int, top: int, left: int, width: int, height: int):
bboxes_ids = [bbox.bbox_id for bbox in self.bboxes]
if bbox_id not in bboxes_ids:
self.bboxes.append(Bbox(bbox_id, top, left, width, height))
else:
raise ValueError("Frame with id: {} already has a Bbox with id: {}".format(self.frame_id, bbox_id))
def add_label_to_bbox(self, bbox_id: int, category: str, confidence: float):
bboxes = {bbox.id: bbox for bbox in self.bboxes}
if bbox_id in bboxes.keys():
res = bboxes.get(bbox_id)
res.add_label(category, confidence)
else:
raise ValueError('the bbox with id: {} does not exists!'.format(bbox_id))
class BboxToJsonLogger(BaseJsonLogger):
"""
ُ This module is designed to automate the task of logging jsons. An example json is used
to show the contents of json file shortly
Example:
{
"video_details": {
"frame_width": 1920,
"frame_height": 1080,
"frame_rate": 20,
"video_name": "/home/gpu/codes/MSD/pedestrian_2/project/public/camera1.avi"
},
"frames": [
{
"frame_id": 329,
"timestamp": 3365.1254
"bboxes": [
{
"labels": [
{
"category": "pedestrian",
"confidence": 0.9
}
],
"bbox_id": 0,
"top": 1257,
"left": 138,
"width": 68,
"height": 109
}
]
}],
Attributes:
frames (dict): It's a dictionary that maps each frame_id to json attributes.
video_details (dict): information about video file.
top_k_labels (int): shows the allowed number of labels
start_time (datetime object): we use it to automate the json output by time.
Args:
top_k_labels (int): shows the allowed number of labels
"""
def __init__(self, top_k_labels: int = 1):
self.frames = {}
self.video_details = self.video_details = dict(frame_width=None, frame_height=None, frame_rate=None,
video_name=None)
self.top_k_labels = top_k_labels
self.start_time = datetime.now()
def set_top_k(self, value):
self.top_k_labels = value
def frame_exists(self, frame_id: int) -> bool:
"""
Args:
frame_id (int):
Returns:
bool: true if frame_id is recognized
"""
return frame_id in self.frames.keys()
def add_frame(self, frame_id: int, timestamp: float = None) -> None:
"""
Args:
frame_id (int):
timestamp (float): opencv captured frame time property
Raises:
ValueError: if frame_id would not exist in class frames attribute
Returns:
None
"""
if not self.frame_exists(frame_id):
self.frames[frame_id] = Frame(frame_id, timestamp)
else:
raise ValueError("Frame id: {} already exists".format(frame_id))
def bbox_exists(self, frame_id: int, bbox_id: int) -> bool:
"""
Args:
frame_id:
bbox_id:
Returns:
bool: if bbox exists in frame bboxes list
"""
bboxes = []
if self.frame_exists(frame_id=frame_id):
bboxes = [bbox.bbox_id for bbox in self.frames[frame_id].bboxes]
return bbox_id in bboxes
def find_bbox(self, frame_id: int, bbox_id: int):
"""
Args:
frame_id:
bbox_id:
Returns:
bbox_id (int):
Raises:
ValueError: if bbox_id does not exist in the bbox list of specific frame.
"""
if not self.bbox_exists(frame_id, bbox_id):
raise ValueError("frame with id: {} does not contain bbox with id: {}".format(frame_id, bbox_id))
bboxes = {bbox.bbox_id: bbox for bbox in self.frames[frame_id].bboxes}
return bboxes.get(bbox_id)
def add_bbox_to_frame(self, frame_id: int, bbox_id: int, top: int, left: int, width: int, height: int) -> None:
"""
Args:
frame_id (int):
bbox_id (int):
top (int):
left (int):
width (int):
height (int):
Returns:
None
Raises:
ValueError: if bbox_id already exist in frame information with frame_id
ValueError: if frame_id does not exist in frames attribute
"""
if self.frame_exists(frame_id):
frame = self.frames[frame_id]
if not self.bbox_exists(frame_id, bbox_id):
frame.add_bbox(bbox_id, top, left, width, height)
else:
raise ValueError(
"frame with frame_id: {} already contains the bbox with id: {} ".format(frame_id, bbox_id))
else:
raise ValueError("frame with frame_id: {} does not exist".format(frame_id))
def add_label_to_bbox(self, frame_id: int, bbox_id: int, category: str, confidence: float):
"""
Args:
frame_id:
bbox_id:
category:
confidence: the confidence value returned from yolo detection
Returns:
None
Raises:
ValueError: if labels quota (top_k_labels) exceeds.
"""
bbox = self.find_bbox(frame_id, bbox_id)
if not bbox.labels_full(self.top_k_labels):
bbox.add_label(category, confidence)
else:
raise ValueError("labels in frame_id: {}, bbox_id: {} is fulled".format(frame_id, bbox_id))
def add_video_details(self, frame_width: int = None, frame_height: int = None, frame_rate: int = None,
video_name: str = None):
self.video_details['frame_width'] = frame_width
self.video_details['frame_height'] = frame_height
self.video_details['frame_rate'] = frame_rate
self.video_details['video_name'] = video_name
def output(self):
output = {'video_details': self.video_details}
result = list(self.frames.values())
output['frames'] = [item.dic() for item in result]
return output
def json_output(self, output_name):
"""
Args:
output_name:
Returns:
None
Notes:
It creates the json output with `output_name` name.
"""
if not output_name.endswith('.json'):
output_name += '.json'
with open(output_name, 'w') as file:
json.dump(self.output(), file)
file.close()
def set_start(self):
self.start_time = datetime.now()
def schedule_output_by_time(self, output_dir=JsonMeta.PATH_TO_SAVE, hours: int = 0, minutes: int = 0,
seconds: int = 60) -> None:
"""
Notes:
Creates folder and then periodically stores the jsons on that address.
Args:
output_dir (str): the directory where output files will be stored
hours (int):
minutes (int):
seconds (int):
Returns:
None
"""
end = datetime.now()
interval = 0
interval += abs(min([hours, JsonMeta.HOURS]) * 3600)
interval += abs(min([minutes, JsonMeta.MINUTES]) * 60)
interval += abs(min([seconds, JsonMeta.SECONDS]))
diff = (end - self.start_time).seconds
if diff > interval:
output_name = self.start_time.strftime('%Y-%m-%d %H-%M-%S') + '.json'
if not exists(output_dir):
makedirs(output_dir)
output = join(output_dir, output_name)
self.json_output(output_name=output)
self.frames = {}
self.start_time = datetime.now()
def schedule_output_by_frames(self, frames_quota, frame_counter, output_dir=JsonMeta.PATH_TO_SAVE):
"""
saves as the number of frames quota increases higher.
:param frames_quota:
:param frame_counter:
:param output_dir:
:return:
"""
pass
def flush(self, output_dir):
"""
Notes:
We use this function to output jsons whenever possible.
like the time that we exit the while loop of opencv.
Args:
output_dir:
Returns:
None
"""
filename = self.start_time.strftime('%Y-%m-%d %H-%M-%S') + '-remaining.json'
output = join(output_dir, filename)
self.json_output(output_name=output)
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