mirror of
https://github.com/blakeblackshear/frigate.git
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15e4f5c771
* Handle zones and masks as relative coords * Ensure that zone coords are saved as relative * Get motion mask working with relative coordinates * Rewrite object mask to use relative coordinates as well * Formatting * Fix always trying to convert * fix mask logic
749 lines
23 KiB
Python
749 lines
23 KiB
Python
"""Utilities for creating and manipulating image frames."""
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import datetime
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import logging
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from abc import ABC, abstractmethod
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from multiprocessing import shared_memory
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from string import printable
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from typing import AnyStr, Optional
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import cv2
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import numpy as np
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from unidecode import unidecode
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logger = logging.getLogger(__name__)
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def transliterate_to_latin(text: str) -> str:
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"""
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Transliterate a given text to Latin.
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This function uses the unidecode library to transliterate the input text to Latin.
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It is useful for converting texts with diacritics or non-Latin characters to a
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Latin equivalent.
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Args:
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text (str): The text to be transliterated.
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Returns:
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str: The transliterated text.
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Example:
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>>> transliterate_to_latin('frégate')
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'fregate'
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"""
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return unidecode(text)
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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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try:
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display_text = transliterate_to_latin("{}: {}".format(label, info))
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except Exception:
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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 is_label_printable(label) -> bool:
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"""Check if label is printable."""
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return not bool(set(label) - set(printable))
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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 calculate_16_9_crop(frame_shape, xmin, ymin, xmax, ymax, multiplier=1.25):
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min_size = 200
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# size is the longest edge and divisible by 4
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x_size = int((xmax - xmin) * multiplier)
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if x_size < min_size:
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x_size = min_size
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y_size = int((ymax - ymin) * multiplier)
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if y_size < min_size:
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y_size = min_size
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if frame_shape[1] / frame_shape[0] > 16 / 9 and x_size / y_size > 4:
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return None
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# calculate 16x9 using height
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aspect_y_size = int(9 / 16 * x_size)
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# if 16:9 by height is too small
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if aspect_y_size < y_size or aspect_y_size > frame_shape[0]:
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x_size = int((16 / 9) * y_size) // 4 * 4
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if x_size / y_size > 1.8:
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return None
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else:
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y_size = aspect_y_size // 4 * 4
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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 - x_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] - x_size):
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x_offset = max(0, (frame_shape[1] - x_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 - y_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] - y_size):
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y_offset = max(0, (frame_shape[0] - y_size))
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return (x_offset, y_offset, x_offset + x_size, y_offset + y_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 + 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 + size // 4 + 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 + size // 4 + 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 + 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 yuv_to_3_channel_yuv(yuv_frame):
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height = yuv_frame.shape[0] // 3 * 2
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width = yuv_frame.shape[1]
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# flatten the image into array
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yuv_data = yuv_frame.ravel()
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# create a numpy array to hold all the 3 channel yuv data
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all_yuv_data = np.empty((height, width, 3), dtype=np.uint8)
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y_count = height * width
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uv_count = y_count // 4
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# copy the y_channel
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all_yuv_data[:, :, 0] = yuv_data[0:y_count].reshape((height, width))
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# copy the u channel doubling each dimension
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all_yuv_data[:, :, 1] = np.repeat(
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np.reshape(
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np.repeat(yuv_data[y_count : y_count + uv_count], repeats=2, axis=0),
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(height // 2, width),
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),
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repeats=2,
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axis=0,
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)
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# copy the v channel doubling each dimension
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all_yuv_data[:, :, 2] = np.repeat(
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np.reshape(
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np.repeat(
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yuv_data[y_count + uv_count : y_count + uv_count + uv_count],
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repeats=2,
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axis=0,
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),
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(height // 2, width),
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),
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repeats=2,
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axis=0,
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)
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return all_yuv_data
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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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interpolation=cv2.INTER_LINEAR,
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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 source_frame is not 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:
|
|
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
|
|
|
|
# resize/copy y channel
|
|
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(
|
|
source_frame[
|
|
source_channel_dim["y"][1] : source_channel_dim["y"][3],
|
|
source_channel_dim["y"][0] : source_channel_dim["y"][2],
|
|
],
|
|
dsize=(y_resize_width, y_resize_height),
|
|
interpolation=interpolation,
|
|
)
|
|
|
|
# resize/copy u1
|
|
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(
|
|
source_frame[
|
|
source_channel_dim["u1"][1] : source_channel_dim["u1"][3],
|
|
source_channel_dim["u1"][0] : source_channel_dim["u1"][2],
|
|
],
|
|
dsize=(uv_resize_width, uv_resize_height),
|
|
interpolation=interpolation,
|
|
)
|
|
# resize/copy u2
|
|
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(
|
|
source_frame[
|
|
source_channel_dim["u2"][1] : source_channel_dim["u2"][3],
|
|
source_channel_dim["u2"][0] : source_channel_dim["u2"][2],
|
|
],
|
|
dsize=(uv_resize_width, uv_resize_height),
|
|
interpolation=interpolation,
|
|
)
|
|
# resize/copy v1
|
|
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(
|
|
source_frame[
|
|
source_channel_dim["v1"][1] : source_channel_dim["v1"][3],
|
|
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_yuv(frame, region):
|
|
try:
|
|
# TODO: does this copy the numpy array?
|
|
yuv_cropped_frame = yuv_crop_and_resize(frame, region)
|
|
return yuv_to_3_channel_yuv(yuv_cropped_frame)
|
|
except:
|
|
print(f"frame.shape: {frame.shape}")
|
|
print(f"region: {region}")
|
|
raise
|
|
|
|
|
|
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 yuv_region_2_bgr(frame, region):
|
|
try:
|
|
yuv_cropped_frame = yuv_crop_and_resize(frame, region)
|
|
return cv2.cvtColor(yuv_cropped_frame, cv2.COLOR_YUV2BGR_I420)
|
|
except:
|
|
print(f"frame.shape: {frame.shape}")
|
|
print(f"region: {region}")
|
|
raise
|
|
|
|
|
|
def intersection(box_a, box_b) -> Optional[list[int]]:
|
|
"""Return intersection box or None if boxes do not intersect."""
|
|
if (
|
|
box_a[2] < box_b[0]
|
|
or box_a[0] > box_b[2]
|
|
or box_a[1] > box_b[3]
|
|
or box_a[3] < box_b[1]
|
|
):
|
|
return None
|
|
|
|
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)
|
|
|
|
if intersect is None:
|
|
return 0.0
|
|
|
|
# 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 intersection 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
|
|
|
|
|
|
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]
|
|
|
|
|
|
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: str, mask_img: np.ndarray):
|
|
points = mask.split(",")
|
|
|
|
# masks and zones are saved as relative coordinates
|
|
# we know if any points are > 1 then it is using the
|
|
# old native resolution coordinates
|
|
if any(x > "1.0" for x in points):
|
|
raise Exception("add mask expects relative coordinates only")
|
|
|
|
contour = np.array(
|
|
[
|
|
[
|
|
int(float(points[i]) * mask_img.shape[1]),
|
|
int(float(points[i + 1]) * mask_img.shape[0]),
|
|
]
|
|
for i in range(0, len(points), 2)
|
|
]
|
|
)
|
|
cv2.fillPoly(mask_img, pts=[contour], color=(0))
|