getting error : contours is not defined for my hand-web-browser project
getting error : contours is not defined for my hand-web-browser project
我正在尝试构建一个项目“hand_web_browser”，该项目的主要 objective 是使用手势打开网页。但是，我在第 55 行收到一个错误
cnt = max(contours, key=lambda x: cv2.contourArea(x))
NameError: name 'contours' is not defined
谁能帮我解决这个问题？？？
import cv2
import numpy as np
import math
import webbrowser as wb
import os
print("Enter full website for")
print("\n2 fingers")
fingers2 = input()
print("\n3 fingers")
fingers3 = input()
print("\n4 fingers")
fingers4 = input()
tabs = 0
count = 0
cap = cv2.VideoCapture(0)
while (cap.isOpened()):
# read image
ret, img = cap.read()
# get hand data from the rectangle sub window on the screen
cv2.rectangle(img, (400, 400), (100, 100), (0, 255, 0), 0)
crop_img = img[100:400, 100:400]
# convert to grayscale
grey = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY)
# applying gaussian blur
value = (35, 35)
blurred = cv2.GaussianBlur(grey, value, 0)
# thresholdin: Otsu's Binarization method
_, thresh1 = cv2.threshold(blurred, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
# show thresholded image, not necessary and can be skipped
cv2.imshow('Thresholded', thresh1)
# check OpenCV version to avoid unpacking error
(version, _, _) = cv2.__version__.split('.')
if version == '3':
image, contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
elif version == '2':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# find contour with max area
cnt = max(contours, key=lambda x: cv2.contourArea(x))
# create bounding rectangle around the contour (can skip below two lines)
x, y, w, h = cv2.boundingRect(cnt)
cv2.rectangle(crop_img, (x, y), (x + w, y + h), (0, 0, 255), 0)
# finding convex hull
hull = cv2.convexHull(cnt)
# drawing contours
drawing = np.zeros(crop_img.shape, np.uint8)
cv2.drawContours(drawing, [cnt], 0, (0, 255, 0), 0)
cv2.drawContours(drawing, [hull], 0, (0, 0, 255), 0)
# finding convex hull
hull = cv2.convexHull(cnt, returnPoints=False) # return point false to find convexity defects
# finding convexity defects
defects = cv2.convexityDefects(cnt, hull)
count_defects = 0
cv2.drawContours(thresh1, contours, -1, (0, 255, 0), 3) # to draw all contours pass -1
# applying Cosine Rule to find angle for all defects (between fingers)
# with angle > 90 degrees and ignore defects
for i in range(defects.shape[0]):
s, e, f, d = defects[i, 0] # [ start point, end point, farthest point, approximate distance to farthest point ]
start = tuple(cnt[s][0])
end = tuple(cnt[e][0])
far = tuple(cnt[f][0])
# find length of all sides of triangle
a = math.sqrt((end[0] - start[0]) ** 2 + (end[1] - start[1]) ** 2)
b = math.sqrt((far[0] - start[0]) ** 2 + (far[1] - start[1]) ** 2)
c = math.sqrt((end[0] - far[0]) ** 2 + (end[1] - far[1]) ** 2)
# apply cosine rule here
angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c)) * 57
# ignore angles > 90 and highlight rest with red dots
if angle <= 90:
count_defects += 1
cv2.circle(crop_img, far, 1, [0, 0, 255], -1)
# dist = cv2.pointPolygonTest(cnt,far,True)
# draw a line from start to end i.e. the convex points (finger tips)
# (can skip this part)
cv2.line(crop_img, start, end, [0, 255, 0], 2)
# cv2.circle(crop_img,far,5,[0,0,255],-1)
if count == 0:
cv2.putText(img, "Wait for it :p", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
# define actions required
if count_defects == 1 and count != 2 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers2 + '.com')
tabs = tabs + 1
cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
count = 2
elif count_defects == 2 and count != 3 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers3 + '.com')
tabs = tabs + 1
cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
count = 3
elif count_defects == 3 and count != 4 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers4 + '.com')
cv2.putText(img, "4." + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
tabs = tabs + 1
count = 4
elif count_defects == 4 and count != 5:
cv2.putText(img, "5.Close Web browser", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
os.system("taskkill /im chrome.exe /f")
tabs = 0
count = 5
else:
cv2.putText(img, "", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
if count == 2:
cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
elif count == 3:
cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
elif count == 4:
cv2.putText(img, "4." + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
elif count == 5:
cv2.putText(img, "5.WebBrowser close", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
# show appropriate images in windows
cv2.imshow('Gesture', img)
all_img = np.hstack((drawing, crop_img))
# not necessary to show contours and can be skipped
cv2.imshow('Contours', all_img)
k = cv2.waitKey(10)
if k == 27:
break
我假设您使用的是最新版本的 OpenCV。如果您使用的是 4.x.x 之类的东西，请尝试以下代码。
if version == '4':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
elif version == '2':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
错误的原因是您的代码根本没有提取轮廓，因为语句 (version, _, _) = cv2.__version__.split('.') returns 4 和您的“if and else”都失败了。
请同时注意以下代码行。
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
这已更改，因为
Since OpenCV 3.2, findContours() no longer modifies the source image.
希望这能解决您的问题。
我正在尝试构建一个项目“hand_web_browser”，该项目的主要 objective 是使用手势打开网页。但是，我在第 55 行收到一个错误
cnt = max(contours, key=lambda x: cv2.contourArea(x))
NameError: name 'contours' is not defined
谁能帮我解决这个问题？？？
import cv2
import numpy as np
import math
import webbrowser as wb
import os
print("Enter full website for")
print("\n2 fingers")
fingers2 = input()
print("\n3 fingers")
fingers3 = input()
print("\n4 fingers")
fingers4 = input()
tabs = 0
count = 0
cap = cv2.VideoCapture(0)
while (cap.isOpened()):
# read image
ret, img = cap.read()
# get hand data from the rectangle sub window on the screen
cv2.rectangle(img, (400, 400), (100, 100), (0, 255, 0), 0)
crop_img = img[100:400, 100:400]
# convert to grayscale
grey = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY)
# applying gaussian blur
value = (35, 35)
blurred = cv2.GaussianBlur(grey, value, 0)
# thresholdin: Otsu's Binarization method
_, thresh1 = cv2.threshold(blurred, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
# show thresholded image, not necessary and can be skipped
cv2.imshow('Thresholded', thresh1)
# check OpenCV version to avoid unpacking error
(version, _, _) = cv2.__version__.split('.')
if version == '3':
image, contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
elif version == '2':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# find contour with max area
cnt = max(contours, key=lambda x: cv2.contourArea(x))
# create bounding rectangle around the contour (can skip below two lines)
x, y, w, h = cv2.boundingRect(cnt)
cv2.rectangle(crop_img, (x, y), (x + w, y + h), (0, 0, 255), 0)
# finding convex hull
hull = cv2.convexHull(cnt)
# drawing contours
drawing = np.zeros(crop_img.shape, np.uint8)
cv2.drawContours(drawing, [cnt], 0, (0, 255, 0), 0)
cv2.drawContours(drawing, [hull], 0, (0, 0, 255), 0)
# finding convex hull
hull = cv2.convexHull(cnt, returnPoints=False) # return point false to find convexity defects
# finding convexity defects
defects = cv2.convexityDefects(cnt, hull)
count_defects = 0
cv2.drawContours(thresh1, contours, -1, (0, 255, 0), 3) # to draw all contours pass -1
# applying Cosine Rule to find angle for all defects (between fingers)
# with angle > 90 degrees and ignore defects
for i in range(defects.shape[0]):
s, e, f, d = defects[i, 0] # [ start point, end point, farthest point, approximate distance to farthest point ]
start = tuple(cnt[s][0])
end = tuple(cnt[e][0])
far = tuple(cnt[f][0])
# find length of all sides of triangle
a = math.sqrt((end[0] - start[0]) ** 2 + (end[1] - start[1]) ** 2)
b = math.sqrt((far[0] - start[0]) ** 2 + (far[1] - start[1]) ** 2)
c = math.sqrt((end[0] - far[0]) ** 2 + (end[1] - far[1]) ** 2)
# apply cosine rule here
angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c)) * 57
# ignore angles > 90 and highlight rest with red dots
if angle <= 90:
count_defects += 1
cv2.circle(crop_img, far, 1, [0, 0, 255], -1)
# dist = cv2.pointPolygonTest(cnt,far,True)
# draw a line from start to end i.e. the convex points (finger tips)
# (can skip this part)
cv2.line(crop_img, start, end, [0, 255, 0], 2)
# cv2.circle(crop_img,far,5,[0,0,255],-1)
if count == 0:
cv2.putText(img, "Wait for it :p", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
# define actions required
if count_defects == 1 and count != 2 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers2 + '.com')
tabs = tabs + 1
cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
count = 2
elif count_defects == 2 and count != 3 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers3 + '.com')
tabs = tabs + 1
cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
count = 3
elif count_defects == 3 and count != 4 and tabs <= 8:
wb.open_new_tab('http://www.' + fingers4 + '.com')
cv2.putText(img, "4." + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
tabs = tabs + 1
count = 4
elif count_defects == 4 and count != 5:
cv2.putText(img, "5.Close Web browser", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
os.system("taskkill /im chrome.exe /f")
tabs = 0
count = 5
else:
cv2.putText(img, "", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
if count == 2:
cv2.putText(img, "2." + fingers2, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 3)
elif count == 3:
cv2.putText(img, "3." + fingers3, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (0, 0, 255), 3)
elif count == 4:
cv2.putText(img, "4." + fingers4, (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 165, 0), 3)
elif count == 5:
cv2.putText(img, "5.WebBrowser close", (50, 100), cv2.FONT_HERSHEY_SIMPLEX, 3, 3)
# show appropriate images in windows
cv2.imshow('Gesture', img)
all_img = np.hstack((drawing, crop_img))
# not necessary to show contours and can be skipped
cv2.imshow('Contours', all_img)
k = cv2.waitKey(10)
if k == 27:
break
我假设您使用的是最新版本的 OpenCV。如果您使用的是 4.x.x 之类的东西，请尝试以下代码。
if version == '4':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
elif version == '2':
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
错误的原因是您的代码根本没有提取轮廓，因为语句 (version, _, _) = cv2.__version__.split('.') returns 4 和您的“if and else”都失败了。
请同时注意以下代码行。
contours, hierarchy = cv2.findContours(thresh1.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
这已更改，因为
Since OpenCV 3.2, findContours() no longer modifies the source image.
希望这能解决您的问题。