tail-feather/CHANGELOG.md Secret

## README.md

      
                Raw

        
              README.md
            
          
    OpenCVの直線検知で流星群画像を仕分け
GUI版
Python環境を必要としない実行可能形式です。

v0.0.2

Windows
Mac
Ubuntu


CUI版使い方
Python環境がある方向け。
detect_meteor.pyの第一引数に.jpg画像の入ったフォルダパスを指定することで、フォルダ内の*.jpg画像に対して検知処理を走らせます。
pip install -r requirements.txt
python detect_meteor.py path/to/directory


## CHANGELOG.md

      
                Raw

        
              CHANGELOG.md
            
          
    2021-06-05

GUI版作成 https://github.com/tail-feather/MeteorDetector

2021-06-01

実行時引数の値が反映されていなかった問題の修正
--area-thresholdの値の調整

2021-05-31

ブログ公開


## detect_meteor.py
#!/usr/bin/env python3

"""
detect_meteor.py

Copyright (c) 2021, AstroArts Inc.

This software is released under the 3-clause BSD license, see LICENSE.
"""

import argparse
import math
import os
import sys
import typing

import cv2
import numpy
from tqdm import tqdm


def load_gray(filepath: str) -> numpy.array:
    """
    グレイスケール画像読み込み
    :param str filepath: 入力ファイルパス
    :return: グレイスケール画像データ
    """
    filepath = str(filepath)
    img = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
    return img


def detect_lines(img: numpy.array) -> typing.List[numpy.array]:
    """
    直線検出
    :param numpy.array img: 入力画像（グレイスケール）
    :return: 検出直線リスト
    """
    ret, thr = cv2.threshold(img, 127, 255, cv2.ADAPTIVE_THRESH_MEAN_C)
    lines = cv2.HoughLinesP(thr, rho=1, theta=math.pi/180, threshold=200, minLineLength=20)
    return lines


def detect_area(img: numpy.array, threshold: float = 0.0001) -> typing.List[numpy.array]:
    """
    閾値を超える面積を持つ輪郭の検出
    :param numpy.array img: 入力画像
    :param float threshold: 閾値（画像全体の何%を`(0, 1]`で指定）
    :return: 閾値を超えた面積の領域リスト
    """
    height, width = img.shape
    img_area = width * height
    ret, thr = cv2.threshold(img, 127, 255, cv2.ADAPTIVE_THRESH_MEAN_C)
    contours, hierarchy = cv2.findContours(thr, 1, 2)
    contours = [cnt for cnt in contours if (cv2.contourArea(cnt) / img_area) > threshold]
    return contours


T = typing.TypeVar("T")
def clamp(v: T, min_v: T, max_v: T) -> T:
    """
    clamp関数
    入力値を`[min_v, max_v]`の範囲に収める
    :param T v: 入力値
    :param T min_v: 最小値
    :param T max_v: 最大値
    :return: `[min_v, max_v]`内に収めた値
    """
    return min(max_v, max(v, min_v))


def fill_area(img: numpy.array, contours: typing.List[numpy.array], buffer_ratio: float = 0.01, color: typing.Optional[float] = None) -> numpy.array:
    """
    領域の外接矩形で塗りつぶす
    :param numpy.array img: 入力画像
    :param contours: 領域リスト
    :param float buffer_ratio: バッファ率 (e.g. 6000 * 0.01 => 60px)
    :param float color: 塗りつぶしの色（未指定の場合は入力画像の中央値で塗りつぶす）
    :return: 塗りつぶし後の画像
    """
    height, width = img.shape
    x_buffer = int(width * buffer_ratio)
    y_buffer = int(height * buffer_ratio)
    # detect fill color
    if color is None:
        color = numpy.median(img)
    # fill bounding rect
    for cnt in contours:
        x, y, w, h = cv2.boundingRect(cnt)
        left = clamp(x - x_buffer, 0, width)
        top = clamp(y - y_buffer, 0, height)
        right = clamp(x + w + x_buffer, 0, width)
        bottom = clamp(y + h + y_buffer, 0, height)
        pts = numpy.asarray([
            [left, top],
            [left, bottom],
            [right, bottom],
            [right, top],
        ])
        img = cv2.fillPoly(img, pts=[pts], color=(color,))
    return img


def line_length(line: numpy.array) -> float:
    """
    直線の長さの算出
    `cv2.HoughLinesP()`の返り値は`[ [ [start_x, start_y, end_x, end_y] ], ... ]`形式になっている
    :param line: `[ [start_x, start_y, end_x, end_y] ]`であること
    :return: 直線の長さ
    """
    assert len(line) == 1
    sx, sy, ex, ey = line[0]
    dx = ex - sx
    dy = ey - sy
    return math.sqrt(dx * dx + dy * dy)


def detect_meteor(filepath: str, area_threshold: float = 0.0001, line_threshold: float = 100) -> typing.Optional[typing.Tuple[str, typing.List[numpy.array]]]:
    """
    流星の検出
    :param str filepath: 入力画像ファイルパス
    :param float area_threshold: 面積のある領域検知用閾値（`detect_area()`関数`threshold`参照）
    :param float line_threshold: 検出した直線を流星と判定する最小の長さ
    :return: (画像ファイルパス, 検出した直線) or None
    """
    img = load_gray(filepath)
    area_contours = detect_area(img, area_threshold)
    if area_contours:
        img = fill_area(img, area_contours)
    lines = detect_lines(img)
    if lines is not None:
        length = max([line_length(x) for x in lines])
        if length > line_threshold:
            return lines
    return None


def main(argv: typing.List[str]) -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("directory")
    parser.add_argument("--area-threshold", type=float, default=0.0001)
    parser.add_argument("--line-threshold", type=float, default=100)

    args = parser.parse_args(argv[1:])

    # 拡張子が`.jpg`の画像リストを作成
    image_list = []
    for dirname, _, filenames in os.walk(args.directory):
        image_list.extend([os.path.join(dirname, x) for x in filenames if x.lower().endswith(".jpg") or x.lower().endswith(".jpeg")])
    image_list.sort()

    # 流星の写っていると思われる画像を抽出
    result = []
    for filepath in tqdm(image_list):
        filepath = str(filepath)
        lines = detect_meteor(filepath, args.area_threshold, args.line_threshold)
        if lines is not None:
            result.append((filepath, lines))
    print("detected: {}/{}".format(len(result), len(image_list)))
    if result:
        print("files:")
        for filepath, lines in result:
            print(filepath)

    return 0


if __name__ == "__main__":
    sys.exit(main(sys.argv))

## LICENSE
BSD 3-Clause License

Copyright (c) 2021, AstroArts Inc.
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its
   contributors may be used to endorse or promote products derived from
   this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE US
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

## requirements.txt
numpy
opencv-python
tqdm
	#!/usr/bin/env python3

	"""
	detect_meteor.py

	Copyright (c) 2021, AstroArts Inc.

	This software is released under the 3-clause BSD license, see LICENSE.
	"""

	import argparse
	import math
	import os
	import sys
	import typing

	import cv2
	import numpy
	from tqdm import tqdm


	def load_gray(filepath: str) -> numpy.array:
	"""
	グレイスケール画像読み込み
	:param str filepath: 入力ファイルパス
	:return: グレイスケール画像データ
	"""
	filepath = str(filepath)
	img = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
	return img


	def detect_lines(img: numpy.array) -> typing.List[numpy.array]:
	"""
	直線検出
	:param numpy.array img: 入力画像（グレイスケール）
	:return: 検出直線リスト
	"""
	ret, thr = cv2.threshold(img, 127, 255, cv2.ADAPTIVE_THRESH_MEAN_C)
	lines = cv2.HoughLinesP(thr, rho=1, theta=math.pi/180, threshold=200, minLineLength=20)
	return lines


	def detect_area(img: numpy.array, threshold: float = 0.0001) -> typing.List[numpy.array]:
	"""
	閾値を超える面積を持つ輪郭の検出
	:param numpy.array img: 入力画像
	:param float threshold: 閾値（画像全体の何%を`(0, 1]`で指定）
	:return: 閾値を超えた面積の領域リスト
	"""
	height, width = img.shape
	img_area = width * height
	ret, thr = cv2.threshold(img, 127, 255, cv2.ADAPTIVE_THRESH_MEAN_C)
	contours, hierarchy = cv2.findContours(thr, 1, 2)
	contours = [cnt for cnt in contours if (cv2.contourArea(cnt) / img_area) > threshold]
	return contours


	T = typing.TypeVar("T")
	def clamp(v: T, min_v: T, max_v: T) -> T:
	"""
	clamp関数
	入力値を`[min_v, max_v]`の範囲に収める
	:param T v: 入力値
	:param T min_v: 最小値
	:param T max_v: 最大値
	:return: `[min_v, max_v]`内に収めた値
	"""
	return min(max_v, max(v, min_v))


	def fill_area(img: numpy.array, contours: typing.List[numpy.array], buffer_ratio: float = 0.01, color: typing.Optional[float] = None) -> numpy.array:
	"""
	領域の外接矩形で塗りつぶす
	:param numpy.array img: 入力画像
	:param contours: 領域リスト
	:param float buffer_ratio: バッファ率 (e.g. 6000 * 0.01 => 60px)
	:param float color: 塗りつぶしの色（未指定の場合は入力画像の中央値で塗りつぶす）
	:return: 塗りつぶし後の画像
	"""
	height, width = img.shape
	x_buffer = int(width * buffer_ratio)
	y_buffer = int(height * buffer_ratio)
	# detect fill color
	if color is None:
	color = numpy.median(img)
	# fill bounding rect
	for cnt in contours:
	x, y, w, h = cv2.boundingRect(cnt)
	left = clamp(x - x_buffer, 0, width)
	top = clamp(y - y_buffer, 0, height)
	right = clamp(x + w + x_buffer, 0, width)
	bottom = clamp(y + h + y_buffer, 0, height)
	pts = numpy.asarray([
	[left, top],
	[left, bottom],
	[right, bottom],
	[right, top],
	])
	img = cv2.fillPoly(img, pts=[pts], color=(color,))
	return img


	def line_length(line: numpy.array) -> float:
	"""
	直線の長さの算出
	`cv2.HoughLinesP()`の返り値は`[ [ [start_x, start_y, end_x, end_y] ], ... ]`形式になっている
	:param line: `[ [start_x, start_y, end_x, end_y] ]`であること
	:return: 直線の長さ
	"""
	assert len(line) == 1
	sx, sy, ex, ey = line[0]
	dx = ex - sx
	dy = ey - sy
	return math.sqrt(dx * dx + dy * dy)


	def detect_meteor(filepath: str, area_threshold: float = 0.0001, line_threshold: float = 100) -> typing.Optional[typing.Tuple[str, typing.List[numpy.array]]]:
	"""
	流星の検出
	:param str filepath: 入力画像ファイルパス
	:param float area_threshold: 面積のある領域検知用閾値（`detect_area()`関数`threshold`参照）
	:param float line_threshold: 検出した直線を流星と判定する最小の長さ
	:return: (画像ファイルパス, 検出した直線) or None
	"""
	img = load_gray(filepath)
	area_contours = detect_area(img, area_threshold)
	if area_contours:
	img = fill_area(img, area_contours)
	lines = detect_lines(img)
	if lines is not None:
	length = max([line_length(x) for x in lines])
	if length > line_threshold:
	return lines
	return None


	def main(argv: typing.List[str]) -> int:
	parser = argparse.ArgumentParser()
	parser.add_argument("directory")
	parser.add_argument("--area-threshold", type=float, default=0.0001)
	parser.add_argument("--line-threshold", type=float, default=100)

	args = parser.parse_args(argv[1:])

	# 拡張子が`.jpg`の画像リストを作成
	image_list = []
	for dirname, _, filenames in os.walk(args.directory):
	image_list.extend([os.path.join(dirname, x) for x in filenames if x.lower().endswith(".jpg") or x.lower().endswith(".jpeg")])
	image_list.sort()

	# 流星の写っていると思われる画像を抽出
	result = []
	for filepath in tqdm(image_list):
	filepath = str(filepath)
	lines = detect_meteor(filepath, args.area_threshold, args.line_threshold)
	if lines is not None:
	result.append((filepath, lines))
	print("detected: {}/{}".format(len(result), len(image_list)))
	if result:
	print("files:")
	for filepath, lines in result:
	print(filepath)

	return 0


	if __name__ == "__main__":
	sys.exit(main(sys.argv))
	BSD 3-Clause License

	Copyright (c) 2021, AstroArts Inc.
	All rights reserved.

	Redistribution and use in source and binary forms, with or without
	modification, are permitted provided that the following conditions are met:

	1. Redistributions of source code must retain the above copyright notice, this
	list of conditions and the following disclaimer.

	2. Redistributions in binary form must reproduce the above copyright notice,
	this list of conditions and the following disclaimer in the documentation
	and/or other materials provided with the distribution.

	3. Neither the name of the copyright holder nor the names of its
	contributors may be used to endorse or promote products derived from
	this software without specific prior written permission.

	THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
	AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
	IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
	DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
	FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
	DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
	SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
	CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
	OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE US
	OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.