問題描述

我有一張帶有橙色蓋子位置的咖啡罐的圖像，我想找到它.這是 .

I have an image of a coffee can with an orange lid position of which I want to find. Here is it .

gcolor2 實用程序顯示蓋子中心的 HSV 為 (22, 59, 100).問題是如何選擇顏色的界限呢?我嘗試了 min = (18, 40, 90) 和 max = (27, 255, 255)，但得到了意外

gcolor2 utility shows HSV at the center of the lid to be (22, 59, 100). The question is how to choose the limits of the color then? I tried min = (18, 40, 90) and max = (27, 255, 255), but have got unexpected

這是 Python 代碼:

Here is the Python code:

import cv

in_image = 'kaffee.png'
out_image = 'kaffee_out.png'
out_image_thr = 'kaffee_thr.png'

ORANGE_MIN = cv.Scalar(18, 40, 90)
ORANGE_MAX = cv.Scalar(27, 255, 255)
COLOR_MIN = ORANGE_MIN
COLOR_MAX = ORANGE_MAX

def test1():
    frame = cv.LoadImage(in_image)
    frameHSV = cv.CreateImage(cv.GetSize(frame), 8, 3)
    cv.CvtColor(frame, frameHSV, cv.CV_RGB2HSV)
    frame_threshed = cv.CreateImage(cv.GetSize(frameHSV), 8, 1)
    cv.InRangeS(frameHSV, COLOR_MIN, COLOR_MAX, frame_threshed)
    cv.SaveImage(out_image_thr, frame_threshed)

if __name__ == '__main__':
    test1()

推薦答案

問題一: 不同的應用程序對 HSV 使用不同的尺度.例如 gimp 使用 H = 0-360, S = 0-100 和 V = 0-100.但是 OpenCV 使用 H: 0-179, S: 0-255, V: 0-255.在這里，我在 gimp 中得到了 22 的色調值.所以我拿了一半，11，并為此定義了范圍.即(5,50,50) - (15,255,255).

Problem 1 : Different applications use different scales for HSV. For example gimp uses H = 0-360, S = 0-100 and V = 0-100. But OpenCV uses H: 0-179, S: 0-255, V: 0-255. Here i got a hue value of 22 in gimp. So I took half of it, 11, and defined range for that. ie (5,50,50) - (15,255,255).

問題 2: 而且，OpenCV 使用 BGR 格式，而不是 RGB.因此，如下更改將 RGB 轉換為 HSV 的代碼:

Problem 2: And also, OpenCV uses BGR format, not RGB. So change your code which converts RGB to HSV as follows:

cv.CvtColor(frame, frameHSV, cv.CV_BGR2HSV)

現在運行它.我得到如下輸出:

Now run it. I got an output as follows:

希望這是您想要的.有一些錯誤檢測，但它們很小，因此您可以選擇最大的輪廓即您的蓋子.

Hope that is what you wanted. There are some false detections, but they are small, so you can choose biggest contour which is your lid.

正如 Karl Philip 在他的評論中所說，添加新代碼會很好.但是只有一行的變化.因此，我想在新的 cv2 模塊中添加相同的代碼，以便用戶可以比較新的 cv2 模塊的易用性和靈活性.

As Karl Philip told in his comment, it would be good to add new code. But there is change of only a single line. So, I would like to add the same code implemented in new cv2 module, so users can compare the easiness and flexibility of new cv2 module.

import cv2
import numpy as np

img = cv2.imread('sof.jpg')

ORANGE_MIN = np.array([5, 50, 50],np.uint8)
ORANGE_MAX = np.array([15, 255, 255],np.uint8)

hsv_img = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)

frame_threshed = cv2.inRange(hsv_img, ORANGE_MIN, ORANGE_MAX)
cv2.imwrite('output2.jpg', frame_threshed)

它給出與上面相同的結果.但是代碼要簡單得多.

It gives the same result as above. But code is much more simpler.

這篇關于使用 cv::inRange (OpenCV) 為顏色檢測選擇正確的 HSV 上下邊界的文章就介紹到這了，希望我們推薦的答案對大家有所幫助，也希望大家多多支持html5模板網！