246 lines
6.7 KiB
Python
246 lines
6.7 KiB
Python
from functools import lru_cache
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from pathlib import Path
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from typing import Literal
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import cv2
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import numpy as np
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from PIL import Image
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from mower.utils import typealias as tp
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from mower.utils.log import logger, save_screenshot
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from mower.utils.path import get_path
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def bytes2img(
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img_data: bytes,
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gray: bool = False,
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bg: tuple[int, int, int, int] | str = "BLACK",
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) -> tp.Image | tp.GrayImage:
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"""解码图片
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Args:
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img_data (bytes): 图片的数据
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gray (bool, optional): 返回灰图. Defaults to False.
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bg (tuple[int, int, int, int] | str, optional): 读取透明PNG时设置的背景颜色. Defaults to "BLACK".
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Returns:
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tp.Image | tp.GrayImage: 图片
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"""
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img = cv2.imdecode(np.frombuffer(img_data, np.uint8), cv2.IMREAD_UNCHANGED)
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if len(img.shape) == 2: # 灰图
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if gray:
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return img
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else:
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return cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
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elif img.shape[2] == 4: # 彩色PNG
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pim = Image.fromarray(img)
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pbg = Image.new("RGBA", pim.size, bg)
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pbg.paste(pim, (0, 0), pim)
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if gray:
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return np.array(pbg.convert("L"))
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else:
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return cv2.cvtColor(np.array(pbg.convert("RGB")), cv2.COLOR_BGR2RGB)
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else: # 彩色JPG
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if gray:
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return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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else:
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return cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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def img2bytes(
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img: tp.Image | tp.GrayImage,
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format: Literal["png", "jpg"] = "jpg",
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quality: int = 75,
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) -> bytes:
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"""编码图片
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Args:
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img (tp.Image | tp.GrayImage): 图片
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format (Literal["png", "jpg"], optional): 图片格式. Defaults to "jpg".
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quality (int, optional): JPG质量. Defaults to 75.
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Returns:
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bytes: 图片数据
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"""
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if len(img.shape) == 3:
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img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
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if format == "jpg":
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data = cv2.imencode(".jpg", img, (cv2.IMWRITE_JPEG_QUALITY, quality))[1]
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else:
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data = cv2.imencode(".png", img)[1]
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return data
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@lru_cache(maxsize=256)
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def read_file(filename: str | Path) -> bytes:
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"""读取图片数据，使用LRU Cache缓存
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Args:
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filename (str | Path): 文件名
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Returns:
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bytes: 图片数据
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"""
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filename = Path(filename)
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try:
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filename = filename.relative_to(get_path("@install"))
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except ValueError:
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pass
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logger.debug(filename)
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return np.fromfile(filename, dtype=np.uint8)
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def loadimg(
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filename: str,
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gray: bool = False,
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bg: tuple[int, int, int, int] | str = "BLACK",
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cache: bool = False,
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) -> tp.Image | tp.GrayImage:
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"""加载图片
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Args:
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filename (str): 文件名
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gray (bool, optional): 返回灰图. Defaults to False.
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bg (tuple[int, int, int, int] | str, optional): 透明PNG的背景颜色. Defaults to "BLACK".
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cache (bool, optional): 使用LRU Cache缓存图片数据. Defaults to True.
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Returns:
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tp.Image | tp.GrayImage: 图片
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"""
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func = read_file if cache else read_file.__wrapped__
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return bytes2img(func(filename), gray, bg)
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def loadres(res: tp.Res, gray: bool = False) -> tp.Image | tp.GrayImage:
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"""加载resources目录下的图片
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Args:
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res (tp.Res): 资源名
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gray (bool, optional): 返回灰图. Defaults to False.
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Returns:
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tp.Image | tp.GrayImage: 图片
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"""
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res = f"@install/mower/resources/{res}"
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if not res.endswith(".jpg"):
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res += ".png"
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return loadimg(get_path(res), gray, cache=True)
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def load_static(name: str, gray: bool = False) -> tp.Image | tp.GrayImage:
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"""加载static目录下的图片
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Args:
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name (str): 资源名
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gray (bool, optional): 返回灰图. Defaults to False.
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Returns:
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tp.Image | tp.GrayImage: 图片
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"""
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name = f"@install/mower/static/{name}"
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if not name.endswith(".jpg"):
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name += ".png"
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return loadimg(get_path(name), gray, cache=False)
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def load_static_dir(
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subdir: str, gray: bool = True, str2int: bool = True
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) -> dict[str, tp.Image | tp.GrayImage]:
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"""加载static的一个子文件夹下的所有图片
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Args:
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subdir (str): 子文件夹
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gray (bool, optional): 返回灰图. Defaults to False.
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str2int (bool, optional): 字典键名转化为数字. Defaults to False.
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Returns:
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dict[str, tp.Image | tp.GrayImage]: 图片字典
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"""
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result = {}
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for p in get_path(f"@install/mower/static/{subdir}").iterdir():
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key = p.stem
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if str2int:
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try:
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key = int(key)
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except ValueError:
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pass
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result[key] = loadimg(p, gray)
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return result
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def thres2(img: tp.GrayImage, thresh: int) -> tp.GrayImage:
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"""二值化
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Args:
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img (tp.GrayImage): 彩图
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thresh (int): 阈值
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Returns:
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tp.GrayImage: 灰图
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"""
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return cv2.threshold(img, thresh, 255, cv2.THRESH_BINARY)[1]
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def scope2slice(scope: tp.Scope) -> tp.Slice:
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"""((x0, y0), (x1, y1)) -> ((y0, y1), (x0, x1))"""
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if scope is None:
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return slice(None), slice(None)
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return slice(scope[0][1], scope[1][1]), slice(scope[0][0], scope[1][0])
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def cropimg(img: tp.Image, scope: tp.Scope) -> tp.Image:
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"""crop image"""
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return img[scope2slice(scope)]
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def saveimg(img: tp.Image, folder):
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del folder # 兼容2024.05旧版接口
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save_screenshot(img2bytes(img))
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def cmatch(
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img1: tp.Image, img2: tp.Image, thresh: int = 10, draw: bool = False
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) -> bool:
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"比较平均色"
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h, w, _ = img1.shape
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ca = cv2.mean(img1)[:3]
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cb = cv2.mean(img2)[:3]
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diff = np.array(ca).astype(int) - np.array(cb).astype(int)
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diff = np.max(np.maximum(diff, 0)) - np.min(np.minimum(diff, 0))
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if draw:
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board = np.zeros([h + 5, w * 2, 3], dtype=np.uint8)
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board[:h, :w, :] = img1
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board[h:, :w, :] = ca
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board[:h, w:, :] = img2
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board[h:, w:, :] = cb
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from matplotlib import pyplot as plt
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plt.imshow(board)
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plt.show()
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return diff <= thresh
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def diff_ratio(
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img1: tp.GrayImage,
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img2: tp.GrayImage,
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thresh: int = 0,
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ratio: float = 0.05,
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) -> bool:
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"""计算两张灰图之间不同的像素所占比例
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Args:
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img1 (tp.GrayImage): 一张灰图
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img2 (tp.GrayImage): 另一张灰图
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thresh (int, optional): 认为像素有差别的阈值. Defaults to 0.
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ratio (float, optional): 判定有差别的比例阈值. Defaults to 0.05.
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Returns:
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bool: 两张灰图是否有差异
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"""
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h, w = img1.shape
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diff = cv2.absdiff(img1, img2)
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diff = thres2(diff, thresh)
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return cv2.countNonZero(diff) > ratio * w * h
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