mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
249 lines
8.2 KiB
Python
Executable File
249 lines
8.2 KiB
Python
Executable File
import collections
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import datetime
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import hashlib
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import json
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import signal
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import subprocess as sp
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import threading
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import time
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import traceback
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from abc import ABC, abstractmethod
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from multiprocessing import shared_memory
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from typing import AnyStr
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import cv2
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import matplotlib.pyplot as plt
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import numpy as np
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def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label, info, thickness=2, color=None, position='ul'):
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if color is None:
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color = (0,0,255)
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display_text = "{}: {}".format(label, info)
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cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, thickness)
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font_scale = 0.5
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font = cv2.FONT_HERSHEY_SIMPLEX
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# get the width and height of the text box
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size = cv2.getTextSize(display_text, font, fontScale=font_scale, thickness=2)
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text_width = size[0][0]
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text_height = size[0][1]
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line_height = text_height + size[1]
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# set the text start position
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if position == 'ul':
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text_offset_x = x_min
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text_offset_y = 0 if y_min < line_height else y_min - (line_height+8)
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elif position == 'ur':
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text_offset_x = x_max - (text_width+8)
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text_offset_y = 0 if y_min < line_height else y_min - (line_height+8)
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elif position == 'bl':
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text_offset_x = x_min
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text_offset_y = y_max
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elif position == 'br':
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text_offset_x = x_max - (text_width+8)
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text_offset_y = y_max
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# make the coords of the box with a small padding of two pixels
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textbox_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y + line_height))
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cv2.rectangle(frame, textbox_coords[0], textbox_coords[1], color, cv2.FILLED)
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cv2.putText(frame, display_text, (text_offset_x, text_offset_y + line_height - 3), font, fontScale=font_scale, color=(0, 0, 0), thickness=2)
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def calculate_region(frame_shape, xmin, ymin, xmax, ymax, multiplier=2):
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# size is larger than longest edge
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size = int(max(xmax-xmin, ymax-ymin)*multiplier)
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# dont go any smaller than 300
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if size < 300:
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size = 300
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# if the size is too big to fit in the frame
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if size > min(frame_shape[0], frame_shape[1]):
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size = min(frame_shape[0], frame_shape[1])
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# x_offset is midpoint of bounding box minus half the size
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x_offset = int((xmax-xmin)/2.0+xmin-size/2.0)
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# if outside the image
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if x_offset < 0:
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x_offset = 0
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elif x_offset > (frame_shape[1]-size):
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x_offset = (frame_shape[1]-size)
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# y_offset is midpoint of bounding box minus half the size
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y_offset = int((ymax-ymin)/2.0+ymin-size/2.0)
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# if outside the image
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if y_offset < 0:
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y_offset = 0
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elif y_offset > (frame_shape[0]-size):
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y_offset = (frame_shape[0]-size)
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return (x_offset, y_offset, x_offset+size, y_offset+size)
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def yuv_region_2_rgb(frame, region):
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height = frame.shape[0]//3*2
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width = frame.shape[1]
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# make sure the size is a multiple of 4
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size = (region[3] - region[1])//4*4
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x1 = region[0]
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y1 = region[1]
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uv_x1 = x1//2
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uv_y1 = y1//4
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uv_width = size//2
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uv_height = size//4
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u_y_start = height
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v_y_start = height + height//4
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two_x_offset = width//2
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yuv_cropped_frame = np.zeros((size+size//2, size), np.uint8)
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# y channel
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yuv_cropped_frame[0:size, 0:size] = frame[y1:y1+size, x1:x1+size]
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# u channel
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yuv_cropped_frame[size:size+uv_height, 0:uv_width] = frame[uv_y1+u_y_start:uv_y1+u_y_start+uv_height, uv_x1:uv_x1+uv_width]
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yuv_cropped_frame[size:size+uv_height, uv_width:size] = frame[uv_y1+u_y_start:uv_y1+u_y_start+uv_height, uv_x1+two_x_offset:uv_x1+two_x_offset+uv_width]
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# v channel
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yuv_cropped_frame[size+uv_height:size+uv_height*2, 0:uv_width] = frame[uv_y1+v_y_start:uv_y1+v_y_start+uv_height, uv_x1:uv_x1+uv_width]
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yuv_cropped_frame[size+uv_height:size+uv_height*2, uv_width:size] = frame[uv_y1+v_y_start:uv_y1+v_y_start+uv_height, uv_x1+two_x_offset:uv_x1+two_x_offset+uv_width]
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return cv2.cvtColor(yuv_cropped_frame, cv2.COLOR_YUV2RGB_I420)
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def intersection(box_a, box_b):
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return (
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max(box_a[0], box_b[0]),
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max(box_a[1], box_b[1]),
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min(box_a[2], box_b[2]),
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min(box_a[3], box_b[3])
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)
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def area(box):
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return (box[2]-box[0] + 1)*(box[3]-box[1] + 1)
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def intersection_over_union(box_a, box_b):
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# determine the (x, y)-coordinates of the intersection rectangle
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intersect = intersection(box_a, box_b)
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# compute the area of intersection rectangle
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inter_area = max(0, intersect[2] - intersect[0] + 1) * max(0, intersect[3] - intersect[1] + 1)
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if inter_area == 0:
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return 0.0
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# compute the area of both the prediction and ground-truth
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# rectangles
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box_a_area = (box_a[2] - box_a[0] + 1) * (box_a[3] - box_a[1] + 1)
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box_b_area = (box_b[2] - box_b[0] + 1) * (box_b[3] - box_b[1] + 1)
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# compute the intersection over union by taking the intersection
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# area and dividing it by the sum of prediction + ground-truth
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# areas - the interesection area
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iou = inter_area / float(box_a_area + box_b_area - inter_area)
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# return the intersection over union value
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return iou
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def clipped(obj, frame_shape):
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# if the object is within 5 pixels of the region border, and the region is not on the edge
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# consider the object to be clipped
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box = obj[2]
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region = obj[4]
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if ((region[0] > 5 and box[0]-region[0] <= 5) or
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(region[1] > 5 and box[1]-region[1] <= 5) or
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(frame_shape[1]-region[2] > 5 and region[2]-box[2] <= 5) or
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(frame_shape[0]-region[3] > 5 and region[3]-box[3] <= 5)):
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return True
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else:
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return False
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class EventsPerSecond:
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def __init__(self, max_events=1000):
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self._start = None
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self._max_events = max_events
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self._timestamps = []
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def start(self):
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self._start = datetime.datetime.now().timestamp()
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def update(self):
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if self._start is None:
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self.start()
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self._timestamps.append(datetime.datetime.now().timestamp())
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# truncate the list when it goes 100 over the max_size
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if len(self._timestamps) > self._max_events+100:
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self._timestamps = self._timestamps[(1-self._max_events):]
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def eps(self, last_n_seconds=10):
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if self._start is None:
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self.start()
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# compute the (approximate) events in the last n seconds
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now = datetime.datetime.now().timestamp()
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seconds = min(now-self._start, last_n_seconds)
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return len([t for t in self._timestamps if t > (now-last_n_seconds)]) / seconds
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def print_stack(sig, frame):
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traceback.print_stack(frame)
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def listen():
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signal.signal(signal.SIGUSR1, print_stack)
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class FrameManager(ABC):
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@abstractmethod
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def create(self, name, size) -> AnyStr:
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pass
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@abstractmethod
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def get(self, name, timeout_ms=0):
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pass
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@abstractmethod
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def close(self, name):
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pass
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@abstractmethod
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def delete(self, name):
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pass
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class DictFrameManager(FrameManager):
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def __init__(self):
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self.frames = {}
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def create(self, name, size) -> AnyStr:
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mem = bytearray(size)
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self.frames[name] = mem
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return mem
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def get(self, name, shape):
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mem = self.frames[name]
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return np.ndarray(shape, dtype=np.uint8, buffer=mem)
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def close(self, name):
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pass
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def delete(self, name):
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del self.frames[name]
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class SharedMemoryFrameManager(FrameManager):
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def __init__(self):
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self.shm_store = {}
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def create(self, name, size) -> AnyStr:
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shm = shared_memory.SharedMemory(name=name, create=True, size=size)
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self.shm_store[name] = shm
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return shm.buf
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def get(self, name, shape):
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if name in self.shm_store:
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shm = self.shm_store[name]
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else:
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shm = shared_memory.SharedMemory(name=name)
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self.shm_store[name] = shm
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return np.ndarray(shape, dtype=np.uint8, buffer=shm.buf)
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def close(self, name):
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if name in self.shm_store:
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self.shm_store[name].close()
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del self.shm_store[name]
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def delete(self, name):
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if name in self.shm_store:
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self.shm_store[name].close()
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self.shm_store[name].unlink()
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del self.shm_store[name]
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