mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-12-23 19:11:14 +01:00
244 lines
8.1 KiB
Python
Executable File
244 lines
8.1 KiB
Python
Executable File
from abc import ABC, abstractmethod
|
|
import datetime
|
|
import time
|
|
import signal
|
|
import traceback
|
|
import collections
|
|
import numpy as np
|
|
import cv2
|
|
import threading
|
|
import matplotlib.pyplot as plt
|
|
import hashlib
|
|
from multiprocessing import shared_memory
|
|
from typing import AnyStr
|
|
|
|
def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label, info, thickness=2, color=None, position='ul'):
|
|
if color is None:
|
|
color = (0,0,255)
|
|
display_text = "{}: {}".format(label, info)
|
|
cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, thickness)
|
|
font_scale = 0.5
|
|
font = cv2.FONT_HERSHEY_SIMPLEX
|
|
# get the width and height of the text box
|
|
size = cv2.getTextSize(display_text, font, fontScale=font_scale, thickness=2)
|
|
text_width = size[0][0]
|
|
text_height = size[0][1]
|
|
line_height = text_height + size[1]
|
|
# set the text start position
|
|
if position == 'ul':
|
|
text_offset_x = x_min
|
|
text_offset_y = 0 if y_min < line_height else y_min - (line_height+8)
|
|
elif position == 'ur':
|
|
text_offset_x = x_max - (text_width+8)
|
|
text_offset_y = 0 if y_min < line_height else y_min - (line_height+8)
|
|
elif position == 'bl':
|
|
text_offset_x = x_min
|
|
text_offset_y = y_max
|
|
elif position == 'br':
|
|
text_offset_x = x_max - (text_width+8)
|
|
text_offset_y = y_max
|
|
# make the coords of the box with a small padding of two pixels
|
|
textbox_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y + line_height))
|
|
cv2.rectangle(frame, textbox_coords[0], textbox_coords[1], color, cv2.FILLED)
|
|
cv2.putText(frame, display_text, (text_offset_x, text_offset_y + line_height - 3), font, fontScale=font_scale, color=(0, 0, 0), thickness=2)
|
|
|
|
def calculate_region(frame_shape, xmin, ymin, xmax, ymax, multiplier=2):
|
|
# size is larger than longest edge
|
|
size = int(max(xmax-xmin, ymax-ymin)*multiplier)
|
|
# dont go any smaller than 300
|
|
if size < 300:
|
|
size = 300
|
|
# if the size is too big to fit in the frame
|
|
if size > min(frame_shape[0], frame_shape[1]):
|
|
size = min(frame_shape[0], frame_shape[1])
|
|
|
|
# x_offset is midpoint of bounding box minus half the size
|
|
x_offset = int((xmax-xmin)/2.0+xmin-size/2.0)
|
|
# if outside the image
|
|
if x_offset < 0:
|
|
x_offset = 0
|
|
elif x_offset > (frame_shape[1]-size):
|
|
x_offset = (frame_shape[1]-size)
|
|
|
|
# y_offset is midpoint of bounding box minus half the size
|
|
y_offset = int((ymax-ymin)/2.0+ymin-size/2.0)
|
|
# if outside the image
|
|
if y_offset < 0:
|
|
y_offset = 0
|
|
elif y_offset > (frame_shape[0]-size):
|
|
y_offset = (frame_shape[0]-size)
|
|
|
|
return (x_offset, y_offset, x_offset+size, y_offset+size)
|
|
|
|
def yuv_region_2_rgb(frame, region):
|
|
height = frame.shape[0]//3*2
|
|
width = frame.shape[1]
|
|
# make sure the size is a multiple of 4
|
|
size = (region[3] - region[1])//4*4
|
|
|
|
x1 = region[0]
|
|
y1 = region[1]
|
|
|
|
uv_x1 = x1//2
|
|
uv_y1 = y1//4
|
|
|
|
uv_width = size//2
|
|
uv_height = size//4
|
|
|
|
u_y_start = height
|
|
v_y_start = height + height//4
|
|
two_x_offset = width//2
|
|
|
|
yuv_cropped_frame = np.zeros((size+size//2, size), np.uint8)
|
|
# y channel
|
|
yuv_cropped_frame[0:size, 0:size] = frame[y1:y1+size, x1:x1+size]
|
|
# u channel
|
|
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]
|
|
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]
|
|
# v channel
|
|
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]
|
|
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]
|
|
|
|
return cv2.cvtColor(yuv_cropped_frame, cv2.COLOR_YUV2RGB_I420)
|
|
|
|
def intersection(box_a, box_b):
|
|
return (
|
|
max(box_a[0], box_b[0]),
|
|
max(box_a[1], box_b[1]),
|
|
min(box_a[2], box_b[2]),
|
|
min(box_a[3], box_b[3])
|
|
)
|
|
|
|
def area(box):
|
|
return (box[2]-box[0] + 1)*(box[3]-box[1] + 1)
|
|
|
|
def intersection_over_union(box_a, box_b):
|
|
# determine the (x, y)-coordinates of the intersection rectangle
|
|
intersect = intersection(box_a, box_b)
|
|
|
|
# compute the area of intersection rectangle
|
|
inter_area = max(0, intersect[2] - intersect[0] + 1) * max(0, intersect[3] - intersect[1] + 1)
|
|
|
|
if inter_area == 0:
|
|
return 0.0
|
|
|
|
# compute the area of both the prediction and ground-truth
|
|
# rectangles
|
|
box_a_area = (box_a[2] - box_a[0] + 1) * (box_a[3] - box_a[1] + 1)
|
|
box_b_area = (box_b[2] - box_b[0] + 1) * (box_b[3] - box_b[1] + 1)
|
|
|
|
# compute the intersection over union by taking the intersection
|
|
# area and dividing it by the sum of prediction + ground-truth
|
|
# areas - the interesection area
|
|
iou = inter_area / float(box_a_area + box_b_area - inter_area)
|
|
|
|
# return the intersection over union value
|
|
return iou
|
|
|
|
def clipped(obj, frame_shape):
|
|
# if the object is within 5 pixels of the region border, and the region is not on the edge
|
|
# consider the object to be clipped
|
|
box = obj[2]
|
|
region = obj[4]
|
|
if ((region[0] > 5 and box[0]-region[0] <= 5) or
|
|
(region[1] > 5 and box[1]-region[1] <= 5) or
|
|
(frame_shape[1]-region[2] > 5 and region[2]-box[2] <= 5) or
|
|
(frame_shape[0]-region[3] > 5 and region[3]-box[3] <= 5)):
|
|
return True
|
|
else:
|
|
return False
|
|
|
|
class EventsPerSecond:
|
|
def __init__(self, max_events=1000):
|
|
self._start = None
|
|
self._max_events = max_events
|
|
self._timestamps = []
|
|
|
|
def start(self):
|
|
self._start = datetime.datetime.now().timestamp()
|
|
|
|
def update(self):
|
|
if self._start is None:
|
|
self.start()
|
|
self._timestamps.append(datetime.datetime.now().timestamp())
|
|
# truncate the list when it goes 100 over the max_size
|
|
if len(self._timestamps) > self._max_events+100:
|
|
self._timestamps = self._timestamps[(1-self._max_events):]
|
|
|
|
def eps(self, last_n_seconds=10):
|
|
if self._start is None:
|
|
self.start()
|
|
# compute the (approximate) events in the last n seconds
|
|
now = datetime.datetime.now().timestamp()
|
|
seconds = min(now-self._start, last_n_seconds)
|
|
return len([t for t in self._timestamps if t > (now-last_n_seconds)]) / seconds
|
|
|
|
def print_stack(sig, frame):
|
|
traceback.print_stack(frame)
|
|
|
|
def listen():
|
|
signal.signal(signal.SIGUSR1, print_stack)
|
|
|
|
class FrameManager(ABC):
|
|
@abstractmethod
|
|
def create(self, name, size) -> AnyStr:
|
|
pass
|
|
|
|
@abstractmethod
|
|
def get(self, name, timeout_ms=0):
|
|
pass
|
|
|
|
@abstractmethod
|
|
def close(self, name):
|
|
pass
|
|
|
|
@abstractmethod
|
|
def delete(self, name):
|
|
pass
|
|
|
|
class DictFrameManager(FrameManager):
|
|
def __init__(self):
|
|
self.frames = {}
|
|
|
|
def create(self, name, size) -> AnyStr:
|
|
mem = bytearray(size)
|
|
self.frames[name] = mem
|
|
return mem
|
|
|
|
def get(self, name, shape):
|
|
mem = self.frames[name]
|
|
return np.ndarray(shape, dtype=np.uint8, buffer=mem)
|
|
|
|
def close(self, name):
|
|
pass
|
|
|
|
def delete(self, name):
|
|
del self.frames[name]
|
|
|
|
class SharedMemoryFrameManager(FrameManager):
|
|
def __init__(self):
|
|
self.shm_store = {}
|
|
|
|
def create(self, name, size) -> AnyStr:
|
|
shm = shared_memory.SharedMemory(name=name, create=True, size=size)
|
|
self.shm_store[name] = shm
|
|
return shm.buf
|
|
|
|
def get(self, name, shape):
|
|
if name in self.shm_store:
|
|
shm = self.shm_store[name]
|
|
else:
|
|
shm = shared_memory.SharedMemory(name=name)
|
|
self.shm_store[name] = shm
|
|
return np.ndarray(shape, dtype=np.uint8, buffer=shm.buf)
|
|
|
|
def close(self, name):
|
|
if name in self.shm_store:
|
|
self.shm_store[name].close()
|
|
del self.shm_store[name]
|
|
|
|
def delete(self, name):
|
|
if name in self.shm_store:
|
|
self.shm_store[name].close()
|
|
self.shm_store[name].unlink()
|
|
del self.shm_store[name] |