完成训练模块的转移
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383
deep_sort/utils/json_logger.py
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383
deep_sort/utils/json_logger.py
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"""
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References:
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https://medium.com/analytics-vidhya/creating-a-custom-logging-mechanism-for-real-time-object-detection-using-tdd-4ca2cfcd0a2f
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"""
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import json
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from os import makedirs
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from os.path import exists, join
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from datetime import datetime
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class JsonMeta(object):
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HOURS = 3
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MINUTES = 59
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SECONDS = 59
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PATH_TO_SAVE = 'LOGS'
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DEFAULT_FILE_NAME = 'remaining'
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class BaseJsonLogger(object):
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"""
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This is the base class that returns __dict__ of its own
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it also returns the dicts of objects in the attributes that are list instances
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"""
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def dic(self):
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# returns dicts of objects
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out = {}
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for k, v in self.__dict__.items():
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if hasattr(v, 'dic'):
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out[k] = v.dic()
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elif isinstance(v, list):
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out[k] = self.list(v)
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else:
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out[k] = v
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return out
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@staticmethod
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def list(values):
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# applies the dic method on items in the list
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return [v.dic() if hasattr(v, 'dic') else v for v in values]
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class Label(BaseJsonLogger):
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"""
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For each bounding box there are various categories with confidences. Label class keeps track of that information.
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"""
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def __init__(self, category: str, confidence: float):
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self.category = category
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self.confidence = confidence
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class Bbox(BaseJsonLogger):
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"""
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This module stores the information for each frame and use them in JsonParser
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Attributes:
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labels (list): List of label module.
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top (int):
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left (int):
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width (int):
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height (int):
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Args:
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bbox_id (float):
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top (int):
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left (int):
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width (int):
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height (int):
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References:
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Check Label module for better understanding.
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"""
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def __init__(self, bbox_id, top, left, width, height):
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self.labels = []
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self.bbox_id = bbox_id
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self.top = top
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self.left = left
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self.width = width
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self.height = height
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def add_label(self, category, confidence):
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# adds category and confidence only if top_k is not exceeded.
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self.labels.append(Label(category, confidence))
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def labels_full(self, value):
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return len(self.labels) == value
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class Frame(BaseJsonLogger):
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"""
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This module stores the information for each frame and use them in JsonParser
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Attributes:
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timestamp (float): The elapsed time of captured frame
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frame_id (int): The frame number of the captured video
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bboxes (list of Bbox objects): Stores the list of bbox objects.
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References:
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Check Bbox class for better information
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Args:
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timestamp (float):
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frame_id (int):
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"""
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def __init__(self, frame_id: int, timestamp: float = None):
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self.frame_id = frame_id
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self.timestamp = timestamp
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self.bboxes = []
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def add_bbox(self, bbox_id: int, top: int, left: int, width: int, height: int):
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bboxes_ids = [bbox.bbox_id for bbox in self.bboxes]
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if bbox_id not in bboxes_ids:
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self.bboxes.append(Bbox(bbox_id, top, left, width, height))
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else:
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raise ValueError("Frame with id: {} already has a Bbox with id: {}".format(self.frame_id, bbox_id))
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def add_label_to_bbox(self, bbox_id: int, category: str, confidence: float):
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bboxes = {bbox.id: bbox for bbox in self.bboxes}
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if bbox_id in bboxes.keys():
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res = bboxes.get(bbox_id)
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res.add_label(category, confidence)
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else:
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raise ValueError('the bbox with id: {} does not exists!'.format(bbox_id))
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class BboxToJsonLogger(BaseJsonLogger):
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"""
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ُ This module is designed to automate the task of logging jsons. An example json is used
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to show the contents of json file shortly
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Example:
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{
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"video_details": {
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"frame_width": 1920,
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"frame_height": 1080,
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"frame_rate": 20,
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"video_name": "/home/gpu/codes/MSD/pedestrian_2/project/public/camera1.avi"
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},
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"frames": [
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{
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"frame_id": 329,
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"timestamp": 3365.1254
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"bboxes": [
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{
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"labels": [
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{
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"category": "pedestrian",
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"confidence": 0.9
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}
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],
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"bbox_id": 0,
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"top": 1257,
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"left": 138,
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"width": 68,
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"height": 109
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}
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]
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}],
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Attributes:
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frames (dict): It's a dictionary that maps each frame_id to json attributes.
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video_details (dict): information about video file.
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top_k_labels (int): shows the allowed number of labels
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start_time (datetime object): we use it to automate the json output by time.
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Args:
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top_k_labels (int): shows the allowed number of labels
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"""
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def __init__(self, top_k_labels: int = 1):
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self.frames = {}
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self.video_details = self.video_details = dict(frame_width=None, frame_height=None, frame_rate=None,
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video_name=None)
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self.top_k_labels = top_k_labels
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self.start_time = datetime.now()
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def set_top_k(self, value):
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self.top_k_labels = value
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def frame_exists(self, frame_id: int) -> bool:
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"""
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Args:
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frame_id (int):
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Returns:
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bool: true if frame_id is recognized
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"""
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return frame_id in self.frames.keys()
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def add_frame(self, frame_id: int, timestamp: float = None) -> None:
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"""
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Args:
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frame_id (int):
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timestamp (float): opencv captured frame time property
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Raises:
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ValueError: if frame_id would not exist in class frames attribute
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Returns:
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None
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"""
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if not self.frame_exists(frame_id):
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self.frames[frame_id] = Frame(frame_id, timestamp)
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else:
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raise ValueError("Frame id: {} already exists".format(frame_id))
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def bbox_exists(self, frame_id: int, bbox_id: int) -> bool:
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"""
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Args:
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frame_id:
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bbox_id:
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Returns:
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bool: if bbox exists in frame bboxes list
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"""
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bboxes = []
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if self.frame_exists(frame_id=frame_id):
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bboxes = [bbox.bbox_id for bbox in self.frames[frame_id].bboxes]
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return bbox_id in bboxes
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def find_bbox(self, frame_id: int, bbox_id: int):
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"""
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Args:
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frame_id:
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bbox_id:
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Returns:
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bbox_id (int):
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Raises:
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ValueError: if bbox_id does not exist in the bbox list of specific frame.
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"""
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if not self.bbox_exists(frame_id, bbox_id):
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raise ValueError("frame with id: {} does not contain bbox with id: {}".format(frame_id, bbox_id))
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bboxes = {bbox.bbox_id: bbox for bbox in self.frames[frame_id].bboxes}
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return bboxes.get(bbox_id)
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def add_bbox_to_frame(self, frame_id: int, bbox_id: int, top: int, left: int, width: int, height: int) -> None:
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"""
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Args:
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frame_id (int):
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bbox_id (int):
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top (int):
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left (int):
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width (int):
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height (int):
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Returns:
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None
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Raises:
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ValueError: if bbox_id already exist in frame information with frame_id
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ValueError: if frame_id does not exist in frames attribute
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"""
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if self.frame_exists(frame_id):
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frame = self.frames[frame_id]
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if not self.bbox_exists(frame_id, bbox_id):
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frame.add_bbox(bbox_id, top, left, width, height)
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else:
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raise ValueError(
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"frame with frame_id: {} already contains the bbox with id: {} ".format(frame_id, bbox_id))
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else:
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raise ValueError("frame with frame_id: {} does not exist".format(frame_id))
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def add_label_to_bbox(self, frame_id: int, bbox_id: int, category: str, confidence: float):
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"""
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Args:
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frame_id:
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bbox_id:
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category:
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confidence: the confidence value returned from yolo detection
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Returns:
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None
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Raises:
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ValueError: if labels quota (top_k_labels) exceeds.
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"""
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bbox = self.find_bbox(frame_id, bbox_id)
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if not bbox.labels_full(self.top_k_labels):
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bbox.add_label(category, confidence)
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else:
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raise ValueError("labels in frame_id: {}, bbox_id: {} is fulled".format(frame_id, bbox_id))
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def add_video_details(self, frame_width: int = None, frame_height: int = None, frame_rate: int = None,
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video_name: str = None):
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self.video_details['frame_width'] = frame_width
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self.video_details['frame_height'] = frame_height
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self.video_details['frame_rate'] = frame_rate
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self.video_details['video_name'] = video_name
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def output(self):
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output = {'video_details': self.video_details}
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result = list(self.frames.values())
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output['frames'] = [item.dic() for item in result]
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return output
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def json_output(self, output_name):
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"""
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Args:
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output_name:
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Returns:
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None
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Notes:
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It creates the json output with `output_name` name.
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"""
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if not output_name.endswith('.json'):
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output_name += '.json'
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with open(output_name, 'w') as file:
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json.dump(self.output(), file)
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file.close()
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def set_start(self):
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self.start_time = datetime.now()
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def schedule_output_by_time(self, output_dir=JsonMeta.PATH_TO_SAVE, hours: int = 0, minutes: int = 0,
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seconds: int = 60) -> None:
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"""
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Notes:
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Creates folder and then periodically stores the jsons on that address.
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Args:
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output_dir (str): the directory where output files will be stored
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hours (int):
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minutes (int):
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seconds (int):
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Returns:
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None
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"""
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end = datetime.now()
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interval = 0
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interval += abs(min([hours, JsonMeta.HOURS]) * 3600)
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interval += abs(min([minutes, JsonMeta.MINUTES]) * 60)
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interval += abs(min([seconds, JsonMeta.SECONDS]))
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diff = (end - self.start_time).seconds
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if diff > interval:
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output_name = self.start_time.strftime('%Y-%m-%d %H-%M-%S') + '.json'
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if not exists(output_dir):
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makedirs(output_dir)
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output = join(output_dir, output_name)
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self.json_output(output_name=output)
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self.frames = {}
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self.start_time = datetime.now()
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def schedule_output_by_frames(self, frames_quota, frame_counter, output_dir=JsonMeta.PATH_TO_SAVE):
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"""
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saves as the number of frames quota increases higher.
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:param frames_quota:
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:param frame_counter:
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:param output_dir:
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:return:
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"""
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pass
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def flush(self, output_dir):
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"""
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Notes:
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We use this function to output jsons whenever possible.
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like the time that we exit the while loop of opencv.
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Args:
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output_dir:
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Returns:
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None
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"""
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filename = self.start_time.strftime('%Y-%m-%d %H-%M-%S') + '-remaining.json'
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output = join(output_dir, filename)
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self.json_output(output_name=output)
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