blakeblackshear.frigate/frigate/util.py

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import collections
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import copy
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import datetime
import hashlib
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import json
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import logging
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import math
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import signal
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import subprocess as sp
import threading
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import time
import traceback
from abc import ABC, abstractmethod
from multiprocessing import shared_memory
from typing import AnyStr
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import cv2
import matplotlib.pyplot as plt
import numpy as np
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logger = logging.getLogger(__name__)
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def deep_merge(dct1: dict, dct2: dict, override=False, merge_lists=False) -> dict:
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"""
:param dct1: First dict to merge
:param dct2: Second dict to merge
:param override: if same key exists in both dictionaries, should override? otherwise ignore. (default=True)
:return: The merge dictionary
"""
merged = copy.deepcopy(dct1)
for k, v2 in dct2.items():
if k in merged:
v1 = merged[k]
if isinstance(v1, dict) and isinstance(v2, collections.Mapping):
merged[k] = deep_merge(v1, v2, override)
elif isinstance(v1, list) and isinstance(v2, list):
if merge_lists:
merged[k] = v1 + v2
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else:
if override:
merged[k] = copy.deepcopy(v2)
else:
merged[k] = copy.deepcopy(v2)
return merged
def draw_timestamp(
frame,
timestamp,
timestamp_format,
font_effect=None,
font_scale=1.0,
font_thickness=2,
font_color=(255, 255, 255),
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position="tl",
):
time_to_show = datetime.datetime.fromtimestamp(timestamp).strftime(timestamp_format)
size = cv2.getTextSize(
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time_to_show,
cv2.FONT_HERSHEY_SIMPLEX,
fontScale=font_scale,
thickness=font_thickness,
)
image_width = frame.shape[1]
image_height = frame.shape[0]
text_width = size[0][0]
text_height = size[0][1]
line_height = text_height + size[1]
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if position == "tl":
text_offset_x = 0
text_offset_y = 0 if 0 < line_height else 0 - (line_height + 8)
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elif position == "tr":
text_offset_x = image_width - text_width
text_offset_y = 0 if 0 < line_height else 0 - (line_height + 8)
elif position == "bl":
text_offset_x = 0
text_offset_y = image_height - (line_height + 8)
elif position == "br":
text_offset_x = image_width - text_width
text_offset_y = image_height - (line_height + 8)
if font_effect == "solid":
# make the coords of the box with a small padding of two pixels
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timestamp_box_coords = np.array(
[
[text_offset_x, text_offset_y],
[text_offset_x + text_width, text_offset_y],
[text_offset_x + text_width, text_offset_y + line_height + 8],
[text_offset_x, text_offset_y + line_height + 8],
]
)
cv2.fillPoly(
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frame,
[timestamp_box_coords],
# inverse color of text for background for max. contrast
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(255 - font_color[0], 255 - font_color[1], 255 - font_color[2]),
)
elif font_effect == "shadow":
cv2.putText(
frame,
time_to_show,
(text_offset_x + 3, text_offset_y + line_height),
cv2.FONT_HERSHEY_SIMPLEX,
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fontScale=font_scale,
color=(255 - font_color[0], 255 - font_color[1], 255 - font_color[2]),
thickness=font_thickness,
)
cv2.putText(
frame,
time_to_show,
(text_offset_x, text_offset_y + line_height - 3),
cv2.FONT_HERSHEY_SIMPLEX,
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fontScale=font_scale,
color=font_color,
thickness=font_thickness,
)
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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)
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
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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)
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":
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text_offset_x = x_min
text_offset_y = y_max
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elif position == "br":
text_offset_x = x_max - (text_width + 8)
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text_offset_y = y_max
# 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):
# size is the longest edge and divisible by 4
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size = int(max(xmax - xmin, ymax - ymin) // 4 * 4 * multiplier)
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# dont go any smaller than 300
if size < 300:
size = 300
# 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)
# if outside the image
if x_offset < 0:
x_offset = 0
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elif x_offset > (frame_shape[1] - size):
x_offset = max(0, (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)
# # if outside the image
if y_offset < 0:
y_offset = 0
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elif y_offset > (frame_shape[0] - size):
y_offset = max(0, (frame_shape[0] - size))
return (x_offset, y_offset, x_offset + size, y_offset + size)
def get_yuv_crop(frame_shape, crop):
# crop should be (x1,y1,x2,y2)
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frame_height = frame_shape[0] // 3 * 2
frame_width = frame_shape[1]
# compute the width/height of the uv channels
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uv_width = frame_width // 2 # width of the uv channels
uv_height = frame_height // 4 # height of the uv channels
# compute the offset for upper left corner of the uv channels
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uv_x_offset = crop[0] // 2 # x offset of the uv channels
uv_y_offset = crop[1] // 4 # y offset of the uv channels
# compute the width/height of the uv crops
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uv_crop_width = (crop[2] - crop[0]) // 2 # width of the cropped uv channels
uv_crop_height = (crop[3] - crop[1]) // 4 # height of the cropped uv channels
# ensure crop dimensions are multiples of 2 and 4
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y = (crop[0], crop[1], crop[0] + uv_crop_width * 2, crop[1] + uv_crop_height * 4)
u1 = (
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0 + uv_x_offset,
frame_height + uv_y_offset,
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0 + uv_x_offset + uv_crop_width,
frame_height + uv_y_offset + uv_crop_height,
)
u2 = (
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uv_width + uv_x_offset,
frame_height + uv_y_offset,
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uv_width + uv_x_offset + uv_crop_width,
frame_height + uv_y_offset + uv_crop_height,
)
v1 = (
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0 + uv_x_offset,
frame_height + uv_height + uv_y_offset,
0 + uv_x_offset + uv_crop_width,
frame_height + uv_height + uv_y_offset + uv_crop_height,
)
v2 = (
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uv_width + uv_x_offset,
frame_height + uv_height + uv_y_offset,
uv_width + uv_x_offset + uv_crop_width,
frame_height + uv_height + uv_y_offset + uv_crop_height,
)
return y, u1, u2, v1, v2
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def yuv_crop_and_resize(frame, region, height=None):
# Crops and resizes a YUV frame while maintaining aspect ratio
# https://stackoverflow.com/a/57022634
height = frame.shape[0] // 3 * 2
width = frame.shape[1]
# get the crop box if the region extends beyond the frame
crop_x1 = max(0, region[0])
crop_y1 = max(0, region[1])
# ensure these are a multiple of 4
crop_x2 = min(width, region[2])
crop_y2 = min(height, region[3])
crop_box = (crop_x1, crop_y1, crop_x2, crop_y2)
y, u1, u2, v1, v2 = get_yuv_crop(frame.shape, crop_box)
# if the region starts outside the frame, indent the start point in the cropped frame
y_channel_x_offset = abs(min(0, region[0]))
y_channel_y_offset = abs(min(0, region[1]))
uv_channel_x_offset = y_channel_x_offset // 2
uv_channel_y_offset = y_channel_y_offset // 4
# create the yuv region frame
# make sure the size is a multiple of 4
# TODO: this should be based on the size after resize now
size = (region[3] - region[1]) // 4 * 4
yuv_cropped_frame = np.zeros((size + size // 2, size), np.uint8)
# fill in black
yuv_cropped_frame[:] = 128
yuv_cropped_frame[0:size, 0:size] = 16
# copy the y channel
yuv_cropped_frame[
y_channel_y_offset : y_channel_y_offset + y[3] - y[1],
y_channel_x_offset : y_channel_x_offset + y[2] - y[0],
] = frame[y[1] : y[3], y[0] : y[2]]
uv_crop_width = u1[2] - u1[0]
uv_crop_height = u1[3] - u1[1]
# copy u1
yuv_cropped_frame[
size + uv_channel_y_offset : size + uv_channel_y_offset + uv_crop_height,
0 + uv_channel_x_offset : 0 + uv_channel_x_offset + uv_crop_width,
] = frame[u1[1] : u1[3], u1[0] : u1[2]]
# copy u2
yuv_cropped_frame[
size + uv_channel_y_offset : size + uv_channel_y_offset + uv_crop_height,
size // 2
+ uv_channel_x_offset : size // 2
+ uv_channel_x_offset
+ uv_crop_width,
] = frame[u2[1] : u2[3], u2[0] : u2[2]]
# copy v1
yuv_cropped_frame[
size
+ size // 4
+ uv_channel_y_offset : size
+ size // 4
+ uv_channel_y_offset
+ uv_crop_height,
0 + uv_channel_x_offset : 0 + uv_channel_x_offset + uv_crop_width,
] = frame[v1[1] : v1[3], v1[0] : v1[2]]
# copy v2
yuv_cropped_frame[
size
+ size // 4
+ uv_channel_y_offset : size
+ size // 4
+ uv_channel_y_offset
+ uv_crop_height,
size // 2
+ uv_channel_x_offset : size // 2
+ uv_channel_x_offset
+ uv_crop_width,
] = frame[v2[1] : v2[3], v2[0] : v2[2]]
return yuv_cropped_frame
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def copy_yuv_to_position(
destination_frame,
destination_offset,
destination_shape,
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source_frame=None,
source_channel_dim=None,
):
# get the coordinates of the channels for this position in the layout
y, u1, u2, v1, v2 = get_yuv_crop(
destination_frame.shape,
(
destination_offset[1],
destination_offset[0],
destination_offset[1] + destination_shape[1],
destination_offset[0] + destination_shape[0],
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),
)
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# clear y
destination_frame[
y[1] : y[3],
y[0] : y[2],
] = 16
# clear u1
destination_frame[u1[1] : u1[3], u1[0] : u1[2]] = 128
# clear u2
destination_frame[u2[1] : u2[3], u2[0] : u2[2]] = 128
# clear v1
destination_frame[v1[1] : v1[3], v1[0] : v1[2]] = 128
# clear v2
destination_frame[v2[1] : v2[3], v2[0] : v2[2]] = 128
if not source_frame is None:
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# calculate the resized frame, maintaining the aspect ratio
source_aspect_ratio = source_frame.shape[1] / (source_frame.shape[0] // 3 * 2)
dest_aspect_ratio = destination_shape[1] / destination_shape[0]
if source_aspect_ratio <= dest_aspect_ratio:
y_resize_height = int(destination_shape[0] // 4 * 4)
y_resize_width = int((y_resize_height * source_aspect_ratio) // 4 * 4)
else:
y_resize_width = int(destination_shape[1] // 4 * 4)
y_resize_height = int((y_resize_width / source_aspect_ratio) // 4 * 4)
uv_resize_width = int(y_resize_width // 2)
uv_resize_height = int(y_resize_height // 4)
y_y_offset = int((destination_shape[0] - y_resize_height) / 4 // 4 * 4)
y_x_offset = int((destination_shape[1] - y_resize_width) / 2 // 4 * 4)
uv_y_offset = y_y_offset // 4
uv_x_offset = y_x_offset // 2
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interpolation = cv2.INTER_LINEAR
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# resize/copy y channel
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destination_frame[
y[1] + y_y_offset : y[1] + y_y_offset + y_resize_height,
y[0] + y_x_offset : y[0] + y_x_offset + y_resize_width,
] = cv2.resize(
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source_frame[
source_channel_dim["y"][1] : source_channel_dim["y"][3],
source_channel_dim["y"][0] : source_channel_dim["y"][2],
],
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dsize=(y_resize_width, y_resize_height),
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interpolation=interpolation,
)
# resize/copy u1
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destination_frame[
u1[1] + uv_y_offset : u1[1] + uv_y_offset + uv_resize_height,
u1[0] + uv_x_offset : u1[0] + uv_x_offset + uv_resize_width,
] = cv2.resize(
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source_frame[
source_channel_dim["u1"][1] : source_channel_dim["u1"][3],
source_channel_dim["u1"][0] : source_channel_dim["u1"][2],
],
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dsize=(uv_resize_width, uv_resize_height),
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interpolation=interpolation,
)
# resize/copy u2
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destination_frame[
u2[1] + uv_y_offset : u2[1] + uv_y_offset + uv_resize_height,
u2[0] + uv_x_offset : u2[0] + uv_x_offset + uv_resize_width,
] = cv2.resize(
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source_frame[
source_channel_dim["u2"][1] : source_channel_dim["u2"][3],
source_channel_dim["u2"][0] : source_channel_dim["u2"][2],
],
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dsize=(uv_resize_width, uv_resize_height),
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interpolation=interpolation,
)
# resize/copy v1
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destination_frame[
v1[1] + uv_y_offset : v1[1] + uv_y_offset + uv_resize_height,
v1[0] + uv_x_offset : v1[0] + uv_x_offset + uv_resize_width,
] = cv2.resize(
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source_frame[
source_channel_dim["v1"][1] : source_channel_dim["v1"][3],
source_channel_dim["v1"][0] : source_channel_dim["v1"][2],
],
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dsize=(uv_resize_width, uv_resize_height),
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interpolation=interpolation,
)
# resize/copy v2
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destination_frame[
v2[1] + uv_y_offset : v2[1] + uv_y_offset + uv_resize_height,
v2[0] + uv_x_offset : v2[0] + uv_x_offset + uv_resize_width,
] = cv2.resize(
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source_frame[
source_channel_dim["v2"][1] : source_channel_dim["v2"][3],
source_channel_dim["v2"][0] : source_channel_dim["v2"][2],
],
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dsize=(uv_resize_width, uv_resize_height),
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interpolation=interpolation,
)
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def yuv_region_2_rgb(frame, region):
try:
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# TODO: does this copy the numpy array?
yuv_cropped_frame = yuv_crop_and_resize(frame, region)
return cv2.cvtColor(yuv_cropped_frame, cv2.COLOR_YUV2RGB_I420)
except:
print(f"frame.shape: {frame.shape}")
print(f"region: {region}")
raise
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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]),
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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:
return 0.0
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# compute the area of both the prediction and ground-truth
# rectangles
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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)
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# 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
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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]
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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)
):
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return True
else:
return False
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class EventsPerSecond:
def __init__(self, max_events=1000):
self._start = None
self._max_events = max_events
self._timestamps = []
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def start(self):
self._start = datetime.datetime.now().timestamp()
def update(self):
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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
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if len(self._timestamps) > self._max_events + 100:
self._timestamps = self._timestamps[(1 - self._max_events) :]
def eps(self, last_n_seconds=10):
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if self._start is None:
self.start()
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# compute the (approximate) events in the last n seconds
now = datetime.datetime.now().timestamp()
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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)
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def listen():
signal.signal(signal.SIGUSR1, print_stack)
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def create_mask(frame_shape, mask):
mask_img = np.zeros(frame_shape, np.uint8)
mask_img[:] = 255
if isinstance(mask, list):
for m in mask:
add_mask(m, mask_img)
elif isinstance(mask, str):
add_mask(mask, mask_img)
return mask_img
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def add_mask(mask, mask_img):
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points = mask.split(",")
contour = np.array(
[[int(points[i]), int(points[i + 1])] for i in range(0, len(points), 2)]
)
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cv2.fillPoly(mask_img, pts=[contour], color=(0))
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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
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class DictFrameManager(FrameManager):
def __init__(self):
self.frames = {}
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def create(self, name, size) -> AnyStr:
mem = bytearray(size)
self.frames[name] = mem
return mem
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def get(self, name, shape):
mem = self.frames[name]
return np.ndarray(shape, dtype=np.uint8, buffer=mem)
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def close(self, name):
pass
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def delete(self, name):
del self.frames[name]
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class SharedMemoryFrameManager(FrameManager):
def __init__(self):
self.shm_store = {}
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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()
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del self.shm_store[name]