Python+OpenCV實(shí)現(xiàn)圖片及視頻中選定區(qū)域顏色識(shí)別

更新時(shí)間：2022年07月22日 15:41:09 作者：wydilearn

這篇文章主要為大家詳細(xì)介紹了如何利用Python+OpenCV實(shí)現(xiàn)圖片及視頻中選定區(qū)域顏色識(shí)別功能，文中的示例代碼講解詳細(xì)，感興趣的可以了解一下

近期，需要實(shí)現(xiàn)檢測(cè)攝像頭中指定坐標(biāo)區(qū)域內(nèi)的主體顏色，通過查閱大量相關(guān)的內(nèi)容，最終實(shí)現(xiàn)代碼及效果如下，具體的實(shí)現(xiàn)步驟在代碼中都詳細(xì)注釋，代碼還可以進(jìn)一步優(yōu)化，但提升有限。

主要實(shí)現(xiàn)過程：按不同顏色的取值范圍，對(duì)圖像進(jìn)行循環(huán)遍歷，轉(zhuǎn)換為灰度圖，將本次遍歷的顏色像素轉(zhuǎn)換為白色，對(duì)白色部分進(jìn)行膨脹處理，使其更加連續(xù)，計(jì)算白色部分外輪廓包圍的面積累加求和，比較每種顏色圍起來(lái)面積，保存最大值及其顏色，所有顏色遍歷完后，返回最大值對(duì)應(yīng)的顏色，顯示在圖像上

如果有類似的顏色識(shí)別的任務(wù)，可參考以下代碼修改后實(shí)現(xiàn)具體需求

colorList.py

import numpy as np
import collections

# 將rgb圖像轉(zhuǎn)換為hsv圖像后，確定不同顏色的取值范圍
def getColorList():
    dict = collections.defaultdict(list)

    # black
    lower_black = np.array([0, 0, 0])
    upper_black = np.array([180, 255, 46])
    color_list_black = []
    color_list_black.append(lower_black)
    color_list_black.append(upper_black)
    dict['black'] = color_list_black

    # gray
    lower_gray = np.array([0, 0, 46])
    upper_gray = np.array([180, 43, 220])
    color_list_gray= []
    color_list_gray.append(lower_gray)
    color_list_gray.append(upper_gray)
    dict['gray'] = color_list_gray

    # white
    lower_white = np.array([0, 0, 221])
    upper_white = np.array([180, 30, 255])
    color_list_white = []
    color_list_white.append(lower_white)
    color_list_white.append(upper_white)
    dict['white'] = color_list_white

    # red
    lower_red = np.array([156, 43, 46])
    upper_red = np.array([180, 255, 255])
    color_list_red = []
    color_list_red.append(lower_red)
    color_list_red.append(upper_red)
    dict['red'] = color_list_red

    # red2
    lower_red = np.array([0, 43, 46])
    upper_red = np.array([10, 255, 255])
    color_list_red2 = []
    color_list_red2.append(lower_red)
    color_list_red2.append(upper_red)
    dict['red2'] = color_list_red2

    # orange
    lower_orange = np.array([11, 43, 46])
    upper_orange = np.array([25, 255, 255])
    color_list_orange = []
    color_list_orange.append(lower_orange)
    color_list_orange.append(upper_orange)
    dict['orange'] = color_list_orange

    # yellow
    lower_yellow = np.array([26, 43, 46])
    upper_yellow = np.array([34, 255, 255])
    color_list_yellow = []
    color_list_yellow.append(lower_yellow)
    color_list_yellow.append(upper_yellow)
    dict['yellow'] = color_list_yellow

    # green
    lower_green = np.array([35, 43, 46])
    upper_green = np.array([77, 255, 255])
    color_list_green = []
    color_list_green.append(lower_green)
    color_list_green.append(upper_green)
    dict['green'] = color_list_green

    # cyan
    lower_cyan = np.array([78, 43, 46])
    upper_cyan = np.array([99, 255, 255])
    color_list_cyan = []
    color_list_cyan.append(lower_cyan)
    color_list_cyan.append(upper_cyan)
    dict['cyan'] = color_list_cyan

    # blue
    lower_blue = np.array([100, 43, 46])
    upper_blue = np.array([124, 255, 255])
    color_list_blue = []
    color_list_blue.append(lower_blue)
    color_list_blue.append(upper_blue)
    dict['blue'] = color_list_blue

    # purple
    lower_purple = np.array([125, 43, 46])
    upper_purple = np.array([155, 255, 255])
    color_list_purple = []
    color_list_purple.append(lower_purple)
    color_list_purple.append(upper_purple)
    dict['purple'] = color_list_purple

    return dict

if __name__ == '__main__':
    color_dict = getColorList()
    print(color_dict)

    num = len(color_dict)
    print('num=', num)

    for d in color_dict:
        print('key=', d)
        print('value=', color_dict[d][1])

image_color_realize.py

import cv2
import colorList

# 實(shí)現(xiàn)對(duì)圖片中目標(biāo)區(qū)域顏色的識(shí)別
def get_color(frame):
    print('go in get_color')
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    maxsum = 0
    color = None
    color_dict = colorList.getColorList()

    # count = 0

    for d in color_dict:
        mask = cv2.inRange(hsv, color_dict[d][0], color_dict[d][1])  # 在后兩個(gè)參數(shù)范圍內(nèi)的值變成255
        binary = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)[1]  # 在灰度圖片中，像素值大于127的都變成255，[1]表示調(diào)用圖像，也就是該函數(shù)第二個(gè)返回值

        # cv2.imshow("0",binary)
        # cv2.waitKey(0)
        # count+=1

        binary = cv2.dilate(binary, None, iterations=2)  # 使用默認(rèn)內(nèi)核進(jìn)行膨脹操作，操作兩次，使縫隙變小，圖像更連續(xù)
        cnts = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]  # 獲取該函數(shù)倒數(shù)第二個(gè)返回值輪廓
        sum = 0
        for c in cnts:
            sum += cv2.contourArea(c)  # 獲取該顏色所有輪廓圍成的面積的和
        # print("%s  , %d" %(d, sum ))
        if sum > maxsum:
            maxsum = sum
            color = d
            if color == 'red2':
                color = 'red'
            elif color == 'orange':
                color = 'yellow'
            elif color == 'purple' or color == 'blue' or color == 'cyan' or color == 'white' or color == 'green':
                color = 'normal'
    return color

if __name__ == '__main__':
    filename = "C:/Users/admin/Desktop/water_samples/live01.jpg"
    frame = cv2.imread(filename)
    # frame = frame[180:280, 180:380]  # [y:y+h, x:x+w] 注意x,y順序
    color = get_color(frame)

    # 繪制文本
    cv2.putText(img=frame,text=color,org=(20,50),fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                fontScale=1.0,color=(0,255,0),thickness=2)

    # cv2.namedWindow('frame',cv2.WINDOW_NORMAL)  # 設(shè)置顯示窗口可調(diào)節(jié)
    cv2.imshow('frame',frame)
    cv2.waitKey(0)

video_color_realize.py

import cv2
import xf_color


# 對(duì)視頻或攝像頭獲取的影像目標(biāo)區(qū)域顏色進(jìn)行識(shí)別

cap = cv2.VideoCapture("C:/Users/admin/Desktop/water_samples/01.mp4")
# cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1100)  # 這里窗口大小調(diào)節(jié)只對(duì)攝像頭有效
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 750)

while cap.isOpened():
    ret, frame0 = cap.read()
    # 對(duì)圖像幀進(jìn)行翻轉(zhuǎn)（因?yàn)閛pencv圖像和我們正常是反著的） 視頻是正常的，攝像頭是反轉(zhuǎn)的
    # frame0 = cv2.flip(src=frame0, flipCode=2)

    # frame = frame[180:280, 180:380]  # [y:y+h, x:x+w]
    # frame = frame0[200:400, 100:300]  # 設(shè)置檢測(cè)顏色的區(qū)域，四個(gè)頂點(diǎn)坐標(biāo)
    frame = frame0

    # frame=cv2.resize(src=frame,dsize=(750,600))
    hsv_frame = cv2.cvtColor(src=frame, code=cv2.COLOR_BGR2HSV)
    # 獲取讀取的幀的高寬
    height, width, channel = frame.shape
    color = xf_color.get_color(hsv_frame)
    # 繪制文本
    cv2.putText(img=frame0, text=color, org=(20, 50), fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                fontScale=1.0, color=(0, 255, 0), thickness=2)
    cv2.imshow('frame', frame0)
    key = cv2.waitKey(1)
    if key == 27:
        break

cap.release()
cv2.destroyAllWindows()


if __name__ == '__main__':
    print('Pycharm')

效果如下：

示例圖片1

示例圖片2

示例圖片3

到此這篇關(guān)于Python+OpenCV實(shí)現(xiàn)圖片及視頻中選定區(qū)域顏色識(shí)別的文章就介紹到這了,更多相關(guān)Python OpenCV顏色識(shí)別內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！

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