mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-26 19:06:11 +01:00
045aac8933
* Add object ratio config parameters Issue: #2948 * Add config test for object filter ratios Issue: #2948 * Address review comments - Accept `ratio` default - Rename `bounds` to `box` for consistency - Add migration for new field Issue: #2948 * Fix logical errors - field migrations require default values - `clipped` referenced the wrong index for region, since it shifted - missed an inclusion of `ratio` for detections in `process_frames` - revert naming `o[2]` as `box` since it is out of scope! This has now been test-run against a video, so I believe the kinks are worked out. Issue: #2948 * Update contributing notes for `make` Issue: #2948 * Fix migration - Ensure that defaults match between Event and migration script - Deconflict migration script number (from rebase) Issue: #2948 * Filter objects out of ratio bounds Issue: #2948 * Update migration file to 009 Issue: #2948
693 lines
21 KiB
Python
Executable File
693 lines
21 KiB
Python
Executable File
import collections
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import copy
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import datetime
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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
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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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import os
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import psutil
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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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"""
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:param dct1: First dict to merge
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:param dct2: Second dict to merge
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:param override: if same key exists in both dictionaries, should override? otherwise ignore. (default=True)
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:return: The merge dictionary
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"""
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merged = copy.deepcopy(dct1)
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for k, v2 in dct2.items():
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if k in merged:
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v1 = merged[k]
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if isinstance(v1, dict) and isinstance(v2, collections.Mapping):
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merged[k] = deep_merge(v1, v2, override)
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elif isinstance(v1, list) and isinstance(v2, list):
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if merge_lists:
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merged[k] = v1 + v2
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else:
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if override:
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merged[k] = copy.deepcopy(v2)
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else:
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merged[k] = copy.deepcopy(v2)
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return merged
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def draw_timestamp(
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frame,
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timestamp,
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timestamp_format,
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font_effect=None,
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font_thickness=2,
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font_color=(255, 255, 255),
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position="tl",
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):
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time_to_show = datetime.datetime.fromtimestamp(timestamp).strftime(timestamp_format)
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# calculate a dynamic font size
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size = cv2.getTextSize(
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time_to_show,
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cv2.FONT_HERSHEY_SIMPLEX,
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fontScale=1.0,
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thickness=font_thickness,
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)
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text_width = size[0][0]
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desired_size = max(150, 0.33 * frame.shape[1])
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font_scale = desired_size / text_width
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# calculate the actual size with the dynamic scale
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size = cv2.getTextSize(
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time_to_show,
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cv2.FONT_HERSHEY_SIMPLEX,
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fontScale=font_scale,
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thickness=font_thickness,
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)
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image_width = frame.shape[1]
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image_height = frame.shape[0]
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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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if position == "tl":
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text_offset_x = 0
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text_offset_y = 0 if 0 < line_height else 0 - (line_height + 8)
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elif position == "tr":
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text_offset_x = image_width - text_width
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text_offset_y = 0 if 0 < line_height else 0 - (line_height + 8)
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elif position == "bl":
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text_offset_x = 0
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text_offset_y = image_height - (line_height + 8)
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elif position == "br":
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text_offset_x = image_width - text_width
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text_offset_y = image_height - (line_height + 8)
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if font_effect == "solid":
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# make the coords of the box with a small padding of two pixels
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timestamp_box_coords = np.array(
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[
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[text_offset_x, text_offset_y],
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[text_offset_x + text_width, text_offset_y],
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[text_offset_x + text_width, text_offset_y + line_height + 8],
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[text_offset_x, text_offset_y + line_height + 8],
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]
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)
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cv2.fillPoly(
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frame,
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[timestamp_box_coords],
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# 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]),
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)
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elif font_effect == "shadow":
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cv2.putText(
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frame,
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time_to_show,
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(text_offset_x + 3, text_offset_y + line_height),
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cv2.FONT_HERSHEY_SIMPLEX,
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fontScale=font_scale,
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color=(255 - font_color[0], 255 - font_color[1], 255 - font_color[2]),
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thickness=font_thickness,
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)
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cv2.putText(
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frame,
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time_to_show,
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(text_offset_x, text_offset_y + line_height - 3),
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cv2.FONT_HERSHEY_SIMPLEX,
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fontScale=font_scale,
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color=font_color,
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thickness=font_thickness,
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)
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def draw_box_with_label(
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frame,
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x_min,
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y_min,
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x_max,
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y_max,
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label,
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info,
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thickness=2,
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color=None,
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position="ul",
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):
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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 = (
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(text_offset_x, text_offset_y),
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(text_offset_x + text_width + 2, text_offset_y + line_height),
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)
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cv2.rectangle(frame, textbox_coords[0], textbox_coords[1], color, cv2.FILLED)
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cv2.putText(
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frame,
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display_text,
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(text_offset_x, text_offset_y + line_height - 3),
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font,
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fontScale=font_scale,
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color=(0, 0, 0),
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thickness=2,
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)
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def calculate_region(frame_shape, xmin, ymin, xmax, ymax, model_size, multiplier=2):
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# size is the longest edge and divisible by 4
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size = int((max(xmax - xmin, ymax - ymin) * multiplier) // 4 * 4)
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# dont go any smaller than the model_size
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if size < model_size:
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size = model_size
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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 = 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)
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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 = max(0, (frame_shape[0] - size))
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return (x_offset, y_offset, x_offset + size, y_offset + size)
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def get_yuv_crop(frame_shape, crop):
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# crop should be (x1,y1,x2,y2)
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frame_height = frame_shape[0] // 3 * 2
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frame_width = frame_shape[1]
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# compute the width/height of the uv channels
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uv_width = frame_width // 2 # width of the uv channels
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uv_height = frame_height // 4 # height of the uv channels
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# 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
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uv_y_offset = crop[1] // 4 # y offset of the uv channels
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# 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
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uv_crop_height = (crop[3] - crop[1]) // 4 # height of the cropped uv channels
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# 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)
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u1 = (
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0 + uv_x_offset,
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frame_height + uv_y_offset,
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0 + uv_x_offset + uv_crop_width,
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frame_height + uv_y_offset + uv_crop_height,
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)
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u2 = (
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uv_width + uv_x_offset,
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frame_height + uv_y_offset,
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uv_width + uv_x_offset + uv_crop_width,
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frame_height + uv_y_offset + uv_crop_height,
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)
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v1 = (
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0 + uv_x_offset,
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frame_height + uv_height + uv_y_offset,
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0 + uv_x_offset + uv_crop_width,
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frame_height + uv_height + uv_y_offset + uv_crop_height,
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)
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v2 = (
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uv_width + uv_x_offset,
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frame_height + uv_height + uv_y_offset,
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uv_width + uv_x_offset + uv_crop_width,
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frame_height + uv_height + uv_y_offset + uv_crop_height,
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)
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return y, u1, u2, v1, v2
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def yuv_crop_and_resize(frame, region, height=None):
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# Crops and resizes a YUV frame while maintaining aspect ratio
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# https://stackoverflow.com/a/57022634
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height = frame.shape[0] // 3 * 2
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width = frame.shape[1]
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# get the crop box if the region extends beyond the frame
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crop_x1 = max(0, region[0])
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crop_y1 = max(0, region[1])
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# ensure these are a multiple of 4
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crop_x2 = min(width, region[2])
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crop_y2 = min(height, region[3])
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crop_box = (crop_x1, crop_y1, crop_x2, crop_y2)
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y, u1, u2, v1, v2 = get_yuv_crop(frame.shape, crop_box)
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# if the region starts outside the frame, indent the start point in the cropped frame
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y_channel_x_offset = abs(min(0, region[0]))
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y_channel_y_offset = abs(min(0, region[1]))
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uv_channel_x_offset = y_channel_x_offset // 2
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uv_channel_y_offset = y_channel_y_offset // 4
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# create the yuv region frame
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# make sure the size is a multiple of 4
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# TODO: this should be based on the size after resize now
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size = (region[3] - region[1]) // 4 * 4
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yuv_cropped_frame = np.zeros((size + size // 2, size), np.uint8)
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# fill in black
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yuv_cropped_frame[:] = 128
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yuv_cropped_frame[0:size, 0:size] = 16
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# copy the y channel
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yuv_cropped_frame[
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y_channel_y_offset : y_channel_y_offset + y[3] - y[1],
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y_channel_x_offset : y_channel_x_offset + y[2] - y[0],
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] = frame[y[1] : y[3], y[0] : y[2]]
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uv_crop_width = u1[2] - u1[0]
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uv_crop_height = u1[3] - u1[1]
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# copy u1
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yuv_cropped_frame[
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size + uv_channel_y_offset : size + uv_channel_y_offset + uv_crop_height,
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0 + uv_channel_x_offset : 0 + uv_channel_x_offset + uv_crop_width,
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] = frame[u1[1] : u1[3], u1[0] : u1[2]]
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# copy u2
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yuv_cropped_frame[
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size + uv_channel_y_offset : size + uv_channel_y_offset + uv_crop_height,
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size // 2
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+ uv_channel_x_offset : size // 2
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+ uv_channel_x_offset
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+ uv_crop_width,
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] = frame[u2[1] : u2[3], u2[0] : u2[2]]
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# copy v1
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yuv_cropped_frame[
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size
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+ size // 4
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+ uv_channel_y_offset : size
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+ size // 4
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+ uv_channel_y_offset
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+ uv_crop_height,
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0 + uv_channel_x_offset : 0 + uv_channel_x_offset + uv_crop_width,
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] = frame[v1[1] : v1[3], v1[0] : v1[2]]
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# copy v2
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yuv_cropped_frame[
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size
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+ size // 4
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+ uv_channel_y_offset : size
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+ size // 4
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+ uv_channel_y_offset
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+ uv_crop_height,
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size // 2
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+ uv_channel_x_offset : size // 2
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+ uv_channel_x_offset
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+ uv_crop_width,
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] = frame[v2[1] : v2[3], v2[0] : v2[2]]
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return yuv_cropped_frame
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def copy_yuv_to_position(
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destination_frame,
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destination_offset,
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destination_shape,
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source_frame=None,
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source_channel_dim=None,
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):
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# get the coordinates of the channels for this position in the layout
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y, u1, u2, v1, v2 = get_yuv_crop(
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destination_frame.shape,
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(
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destination_offset[1],
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destination_offset[0],
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destination_offset[1] + destination_shape[1],
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destination_offset[0] + destination_shape[0],
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),
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)
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# clear y
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destination_frame[
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y[1] : y[3],
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y[0] : y[2],
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] = 16
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# clear u1
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destination_frame[u1[1] : u1[3], u1[0] : u1[2]] = 128
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# clear u2
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destination_frame[u2[1] : u2[3], u2[0] : u2[2]] = 128
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# clear v1
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destination_frame[v1[1] : v1[3], v1[0] : v1[2]] = 128
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# clear v2
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destination_frame[v2[1] : v2[3], v2[0] : v2[2]] = 128
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if not source_frame is None:
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# calculate the resized frame, maintaining the aspect ratio
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source_aspect_ratio = source_frame.shape[1] / (source_frame.shape[0] // 3 * 2)
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dest_aspect_ratio = destination_shape[1] / destination_shape[0]
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if source_aspect_ratio <= dest_aspect_ratio:
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y_resize_height = int(destination_shape[0] // 4 * 4)
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y_resize_width = int((y_resize_height * source_aspect_ratio) // 4 * 4)
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else:
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y_resize_width = int(destination_shape[1] // 4 * 4)
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y_resize_height = int((y_resize_width / source_aspect_ratio) // 4 * 4)
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uv_resize_width = int(y_resize_width // 2)
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uv_resize_height = int(y_resize_height // 4)
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y_y_offset = int((destination_shape[0] - y_resize_height) / 4 // 4 * 4)
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y_x_offset = int((destination_shape[1] - y_resize_width) / 2 // 4 * 4)
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uv_y_offset = y_y_offset // 4
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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[
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y[1] + y_y_offset : y[1] + y_y_offset + y_resize_height,
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y[0] + y_x_offset : y[0] + y_x_offset + y_resize_width,
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] = cv2.resize(
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source_frame[
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source_channel_dim["y"][1] : source_channel_dim["y"][3],
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source_channel_dim["y"][0] : source_channel_dim["y"][2],
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],
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dsize=(y_resize_width, y_resize_height),
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interpolation=interpolation,
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)
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# resize/copy u1
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destination_frame[
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u1[1] + uv_y_offset : u1[1] + uv_y_offset + uv_resize_height,
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u1[0] + uv_x_offset : u1[0] + uv_x_offset + uv_resize_width,
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] = cv2.resize(
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source_frame[
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source_channel_dim["u1"][1] : source_channel_dim["u1"][3],
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source_channel_dim["u1"][0] : source_channel_dim["u1"][2],
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],
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dsize=(uv_resize_width, uv_resize_height),
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interpolation=interpolation,
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)
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# resize/copy u2
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destination_frame[
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u2[1] + uv_y_offset : u2[1] + uv_y_offset + uv_resize_height,
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u2[0] + uv_x_offset : u2[0] + uv_x_offset + uv_resize_width,
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] = cv2.resize(
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source_frame[
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source_channel_dim["u2"][1] : source_channel_dim["u2"][3],
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source_channel_dim["u2"][0] : source_channel_dim["u2"][2],
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],
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dsize=(uv_resize_width, uv_resize_height),
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interpolation=interpolation,
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)
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# resize/copy v1
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destination_frame[
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v1[1] + uv_y_offset : v1[1] + uv_y_offset + uv_resize_height,
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v1[0] + uv_x_offset : v1[0] + uv_x_offset + uv_resize_width,
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] = cv2.resize(
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source_frame[
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source_channel_dim["v1"][1] : source_channel_dim["v1"][3],
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|
source_channel_dim["v1"][0] : source_channel_dim["v1"][2],
|
|
],
|
|
dsize=(uv_resize_width, uv_resize_height),
|
|
interpolation=interpolation,
|
|
)
|
|
# resize/copy v2
|
|
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(
|
|
source_frame[
|
|
source_channel_dim["v2"][1] : source_channel_dim["v2"][3],
|
|
source_channel_dim["v2"][0] : source_channel_dim["v2"][2],
|
|
],
|
|
dsize=(uv_resize_width, uv_resize_height),
|
|
interpolation=interpolation,
|
|
)
|
|
|
|
|
|
def yuv_region_2_rgb(frame, region):
|
|
try:
|
|
# 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
|
|
|
|
|
|
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[5]
|
|
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
|
|
|
|
|
|
def restart_frigate():
|
|
proc = psutil.Process(1)
|
|
# if this is running via s6, sigterm pid 1
|
|
if proc.name() == "s6-svscan":
|
|
proc.terminate()
|
|
# otherwise, just try and exit frigate
|
|
else:
|
|
os.kill(os.getpid(), signal.SIGTERM)
|
|
|
|
|
|
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)
|
|
# avoid divide by zero
|
|
if seconds == 0:
|
|
seconds = 1
|
|
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)
|
|
|
|
|
|
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
|
|
|
|
|
|
def add_mask(mask, mask_img):
|
|
points = mask.split(",")
|
|
contour = np.array(
|
|
[[int(points[i]), int(points[i + 1])] for i in range(0, len(points), 2)]
|
|
)
|
|
cv2.fillPoly(mask_img, pts=[contour], color=(0))
|
|
|
|
|
|
def load_labels(path, encoding="utf-8"):
|
|
"""Loads labels from file (with or without index numbers).
|
|
Args:
|
|
path: path to label file.
|
|
encoding: label file encoding.
|
|
Returns:
|
|
Dictionary mapping indices to labels.
|
|
"""
|
|
with open(path, "r", encoding=encoding) as f:
|
|
lines = f.readlines()
|
|
if not lines:
|
|
return {}
|
|
|
|
if lines[0].split(" ", maxsplit=1)[0].isdigit():
|
|
pairs = [line.split(" ", maxsplit=1) for line in lines]
|
|
return {int(index): label.strip() for index, label in pairs}
|
|
else:
|
|
return {index: line.strip() for index, line in enumerate(lines)}
|
|
|
|
|
|
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]
|