小编Sap*_*shi的帖子

我在 .pro 文件中有以下配置

TEMPLATE = app
CONFIG += console c++11
CONFIG -= app_bundle
CONFIG -= qt
CONFIG += thread

SOURCES += main.cpp

INCLUDEPATH += /usr/local/include/opencv4
LIBS += -L/usr/local/lib/
LIBS += -lopencv_core
LIBS += -lopencv_highgui
LIBS += -lopencv_imgproc
LIBS += -lopencv_videoio

QMAKE_CXXFLAGS += -D_GLIBCXX_USE_CXX11_ABI=0

INCLUDEPATH += /path/to/libtorch/include
INCLUDEPATH += /path/to/libtorch/include/torch/csrc/api/include
LIBS += -L/path/to/libtorch/lib
LIBS += -ltorch -lc10

OpenCV 在没有“QMAKE_CXXFLAGS += -D_GLIBCXX_USE_CXX11_ABI= 0 ”的情况下工作得很好。但是，有了这个，我得到了以下错误：

OpenCV 也适用于“QMAKE_CXXFLAGS += -D_GLIBCXX_USE_CXX11_ABI= 1 ”。但它引发了一组不同的错误：

大多数论坛都建议为 Libtorch设置“QMAKE_CXXFLAGS += -D_GLIBCXX_USE_CXX11_ABI= 0 ”以避免上述错误。 …

我正在尝试使用无服务器在 AWS 中部署 REST API。节点版本 14.17.5。

我的目录结构：

当我成功部署上述内容时，我在尝试访问 api 时收到以下错误。

2021-09-28T18:32:27.576Z    undefined   ERROR   Uncaught Exception  {
    "errorType": "Error",
    "errorMessage": "Must use import to load ES Module: /var/task/lambda.js\nrequire() of ES modules is not supported.\nrequire() of /var/task/lambda.js from /var/runtime/UserFunction.js is an ES module file as it is a .js file whose nearest parent package.json contains \"type\": \"module\" which defines all .js files in that package scope as ES modules.\nInstead rename lambda.js to end in .cjs, change the requiring code to use import(), …

我一直在尝试实现以下提供的白平衡算法:https: //pippin.gimp.org/image-processing/chapter-automaticadjustments.html

我用python和opencv来实现它们.我无法产生与网站相同的结果.

例如,在灰色世界的假设中,我使用以下代码:

import cv2 as cv
import numpy as np

def show(final):
    print 'display'
    cv.imshow("Temple", final)
    cv.waitKey(0)
    cv.destroyAllWindows()

def saveimg(final):
    print 'saving'
    cv.imwrite("result.jpg", final)

# Insert any filename with path
img = cv.imread("grayworld_assumption_0.png")
res = img
final = cv.cvtColor(res, cv.COLOR_BGR2LAB)

avg_a = -np.average(final[:,:,1])
avg_b = -np.average(final[:,:,2])

for x in range(final.shape[0]):
    for y in range(final.shape[1]):
        l,a,b = final[x][y]
        shift_a = avg_a * (l/100.0) * 1.1
        shift_b = avg_b * (l/100.0) * 1.1
        final[x][y][1] = a + shift_a …