OpenCV 断言失败：(-215:断言失败) npoints >= 0 && (depth == CV_32F || depth == CV_32S)
OpenCV Assertion failed: (-215:Assertion failed) npoints >= 0 && (depth == CV_32F || depth == CV_32S)
我在 this website 上找到了以下代码：
import os
import os.path
import cv2
import glob
import imutils
CAPTCHA_IMAGE_FOLDER = "generated_captcha_images"
OUTPUT_FOLDER = "extracted_letter_images"
# Get a list of all the captcha images we need to process
captcha_image_files = glob.glob(os.path.join(CAPTCHA_IMAGE_FOLDER, "*"))
counts = {}
# loop over the image paths
for (i, captcha_image_file) in enumerate(captcha_image_files):
print("[INFO] processing image {}/{}".format(i + 1, len(captcha_image_files)))
# Since the filename contains the captcha text (i.e. "2A2X.png" has the text "2A2X"),
# grab the base filename as the text
filename = os.path.basename(captcha_image_file)
captcha_correct_text = os.path.splitext(filename)[0]
# Load the image and convert it to grayscale
image = cv2.imread(captcha_image_file)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Add some extra padding around the image
gray = cv2.copyMakeBorder(gray, 8, 8, 8, 8, cv2.BORDER_REPLICATE)
# threshold the image (convert it to pure black and white)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
# find the contours (continuous blobs of pixels) the image
contours = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Hack for compatibility with different OpenCV versions
contours = contours[0] if imutils.is_cv2() else contours[1]
letter_image_regions = []
# Now we can loop through each of the four contours and extract the letter
# inside of each one
for contour in contours:
# Get the rectangle that contains the contour
(x, y, w, h) = cv2.boundingRect(contour)
# Compare the width and height of the contour to detect letters that
# are conjoined into one chunk
if w / h > 1.25:
# This contour is too wide to be a single letter!
# Split it in half into two letter regions!
half_width = int(w / 2)
letter_image_regions.append((x, y, half_width, h))
letter_image_regions.append((x + half_width, y, half_width, h))
else:
# This is a normal letter by itself
letter_image_regions.append((x, y, w, h))
# If we found more or less than 4 letters in the captcha, our letter extraction
# didn't work correcly. Skip the image instead of saving bad training data!
if len(letter_image_regions) != 4:
continue
# Sort the detected letter images based on the x coordinate to make sure
# we are processing them from left-to-right so we match the right image
# with the right letter
letter_image_regions = sorted(letter_image_regions, key=lambda x: x[0])
# Save out each letter as a single image
for letter_bounding_box, letter_text in zip(letter_image_regions, captcha_correct_text):
# Grab the coordinates of the letter in the image
x, y, w, h = letter_bounding_box
# Extract the letter from the original image with a 2-pixel margin around the edge
letter_image = gray[y - 2:y + h + 2, x - 2:x + w + 2]
# Get the folder to save the image in
save_path = os.path.join(OUTPUT_FOLDER, letter_text)
# if the output directory does not exist, create it
if not os.path.exists(save_path):
os.makedirs(save_path)
# write the letter image to a file
count = counts.get(letter_text, 1)
p = os.path.join(save_path, "{}.png".format(str(count).zfill(6)))
cv2.imwrite(p, letter_image)
# increment the count for the current key
counts[letter_text] = count + 1
当我尝试 运行 代码时，出现以下错误：
[INFO] processing image 1/9955
Traceback (most recent call last):
File "extract_single_letters_from_captchas.py", line 47, in <module>
(x, y, w, h) = cv2.boundingRect(contour)
cv2.error: OpenCV(4.0.0) /Users/travis/build/skvark/opencv-python/opencv/modules/imgproc/src/shapedescr.cpp:741: error: (-215:Assertion failed) npoints >= 0 && (depth == CV_32F || depth == CV_32S) in function 'pointSetBoundingRect'
我尝试在 Whosebug 上搜索解决方案，但没有找到任何类似的解决方案。
编辑（见评论）：
type(contour[0]) = <class 'numpy.ndarray'>
len(contour) = 4
这是错误的做法：
contours = contours[0] if imutils.is_cv2() else contours[1]
imutils.is_cv2() 正在 returning False，尽管它应该 return True。如果不介意去掉这个依赖，改成：
contours = contours[0]
我找到原因了。您正在学习的教程可能是在 OpenCV 4 发布之前发布的。 OpenCV 3 更改了 cv2.findContours(...) to return image, contours, hierarchy, while OpenCV 2's cv2.findContours(...) and OpenCV 4's cv2.findContours(...) return contours, hierarchy。因此，在 OpenCV 4 之前，如果你使用 OpenCV 2，它应该是 contours[0] else contours[1] 是正确的。如果你还想拥有这个"compatibility"，可以改成：
contours = contours[1] if imutils.is_cv3() else contours[0]
【OpenCV 3 将 cv2.findContours(...) 更改为 return image, contours, hierarchy】
这个内容对我很有帮助。我在前面添加了一个新变量并修复了所有错误..
这是因为opencv-python版本4.0.0。如果您想在不更改代码的情况下解决此问题，请将 opencv-python 降级到版本 3.4.9.31
卸载opencv-python
pip uninstall opencv-python
安装opencv-python==3.4.9.31
pip install opencv-python==3.4.9.31
如果函数 'pointSetBoundingRect' 出现问题，您需要安装 'opencv-python-headless'
pip install opencv-python-headless==3.4.9.31
在 OpenCV4 中，cv2.findContours 只有 2 个 return 值。
轮廓是第一个值
contours, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
请注意，我添加下划线是为了放弃 hierarchy
的另一个 return 值
我用以下方式编写了相同的代码：
_, contours, hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
并且我的代码有效。我认为以前它返回 2 个变量，现在我们必须解压缩为三个变量。如果这不起作用，请尝试以下操作：
_, contours, _ = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
这应该有效。
更多信息，您可以访问 OpenCV 文档页面：https://docs.opencv.org/3.1.0/d4/d73/tutorial_py_contours_begin.html
希望对您有所帮助。
(x, y, w, h) = cv2.boundingRect(contour.astype(np.int))
原因在于findContours()。
在 OpenCV 版本 3 中，我们写道：
_, contours, _ = cv.findContours()
在OpenCV第4版中，我们改为：
contours, _ = cv.findContours()
使用任何一个解决问题。
或者，我们可以使用这些命令稳定我们的 OpenCV 版本，假设您已经安装了 anaconda。
conda install -c conda-forge opencv=4.1.0
pip install opencv-contrib-python
我在 this website 上找到了以下代码：
import os
import os.path
import cv2
import glob
import imutils
CAPTCHA_IMAGE_FOLDER = "generated_captcha_images"
OUTPUT_FOLDER = "extracted_letter_images"
# Get a list of all the captcha images we need to process
captcha_image_files = glob.glob(os.path.join(CAPTCHA_IMAGE_FOLDER, "*"))
counts = {}
# loop over the image paths
for (i, captcha_image_file) in enumerate(captcha_image_files):
print("[INFO] processing image {}/{}".format(i + 1, len(captcha_image_files)))
# Since the filename contains the captcha text (i.e. "2A2X.png" has the text "2A2X"),
# grab the base filename as the text
filename = os.path.basename(captcha_image_file)
captcha_correct_text = os.path.splitext(filename)[0]
# Load the image and convert it to grayscale
image = cv2.imread(captcha_image_file)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Add some extra padding around the image
gray = cv2.copyMakeBorder(gray, 8, 8, 8, 8, cv2.BORDER_REPLICATE)
# threshold the image (convert it to pure black and white)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
# find the contours (continuous blobs of pixels) the image
contours = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Hack for compatibility with different OpenCV versions
contours = contours[0] if imutils.is_cv2() else contours[1]
letter_image_regions = []
# Now we can loop through each of the four contours and extract the letter
# inside of each one
for contour in contours:
# Get the rectangle that contains the contour
(x, y, w, h) = cv2.boundingRect(contour)
# Compare the width and height of the contour to detect letters that
# are conjoined into one chunk
if w / h > 1.25:
# This contour is too wide to be a single letter!
# Split it in half into two letter regions!
half_width = int(w / 2)
letter_image_regions.append((x, y, half_width, h))
letter_image_regions.append((x + half_width, y, half_width, h))
else:
# This is a normal letter by itself
letter_image_regions.append((x, y, w, h))
# If we found more or less than 4 letters in the captcha, our letter extraction
# didn't work correcly. Skip the image instead of saving bad training data!
if len(letter_image_regions) != 4:
continue
# Sort the detected letter images based on the x coordinate to make sure
# we are processing them from left-to-right so we match the right image
# with the right letter
letter_image_regions = sorted(letter_image_regions, key=lambda x: x[0])
# Save out each letter as a single image
for letter_bounding_box, letter_text in zip(letter_image_regions, captcha_correct_text):
# Grab the coordinates of the letter in the image
x, y, w, h = letter_bounding_box
# Extract the letter from the original image with a 2-pixel margin around the edge
letter_image = gray[y - 2:y + h + 2, x - 2:x + w + 2]
# Get the folder to save the image in
save_path = os.path.join(OUTPUT_FOLDER, letter_text)
# if the output directory does not exist, create it
if not os.path.exists(save_path):
os.makedirs(save_path)
# write the letter image to a file
count = counts.get(letter_text, 1)
p = os.path.join(save_path, "{}.png".format(str(count).zfill(6)))
cv2.imwrite(p, letter_image)
# increment the count for the current key
counts[letter_text] = count + 1
当我尝试 运行 代码时，出现以下错误：
[INFO] processing image 1/9955
Traceback (most recent call last):
File "extract_single_letters_from_captchas.py", line 47, in <module>
(x, y, w, h) = cv2.boundingRect(contour)
cv2.error: OpenCV(4.0.0) /Users/travis/build/skvark/opencv-python/opencv/modules/imgproc/src/shapedescr.cpp:741: error: (-215:Assertion failed) npoints >= 0 && (depth == CV_32F || depth == CV_32S) in function 'pointSetBoundingRect'
我尝试在 Whosebug 上搜索解决方案，但没有找到任何类似的解决方案。
编辑（见评论）：
type(contour[0])=<class 'numpy.ndarray'>len(contour)=4
这是错误的做法：
contours = contours[0] if imutils.is_cv2() else contours[1]
imutils.is_cv2() 正在 returning False，尽管它应该 return True。如果不介意去掉这个依赖，改成：
contours = contours[0]
我找到原因了。您正在学习的教程可能是在 OpenCV 4 发布之前发布的。 OpenCV 3 更改了 cv2.findContours(...) to return image, contours, hierarchy, while OpenCV 2's cv2.findContours(...) and OpenCV 4's cv2.findContours(...) return contours, hierarchy。因此，在 OpenCV 4 之前，如果你使用 OpenCV 2，它应该是 contours[0] else contours[1] 是正确的。如果你还想拥有这个"compatibility"，可以改成：
contours = contours[1] if imutils.is_cv3() else contours[0]
【OpenCV 3 将 cv2.findContours(...) 更改为 return image, contours, hierarchy】 这个内容对我很有帮助。我在前面添加了一个新变量并修复了所有错误..
这是因为opencv-python版本4.0.0。如果您想在不更改代码的情况下解决此问题，请将 opencv-python 降级到版本 3.4.9.31
卸载opencv-python
pip uninstall opencv-python
安装opencv-python==3.4.9.31
pip install opencv-python==3.4.9.31
如果函数 'pointSetBoundingRect' 出现问题，您需要安装 'opencv-python-headless'
pip install opencv-python-headless==3.4.9.31
在 OpenCV4 中，cv2.findContours 只有 2 个 return 值。 轮廓是第一个值
contours, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
请注意，我添加下划线是为了放弃 hierarchy
的另一个 return 值我用以下方式编写了相同的代码：
_, contours, hierarchy = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
并且我的代码有效。我认为以前它返回 2 个变量，现在我们必须解压缩为三个变量。如果这不起作用，请尝试以下操作：
_, contours, _ = cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
这应该有效。
更多信息，您可以访问 OpenCV 文档页面：https://docs.opencv.org/3.1.0/d4/d73/tutorial_py_contours_begin.html
希望对您有所帮助。
(x, y, w, h) = cv2.boundingRect(contour.astype(np.int))
原因在于findContours()。
在 OpenCV 版本 3 中，我们写道：
_, contours, _ = cv.findContours()
在OpenCV第4版中，我们改为：
contours, _ = cv.findContours()
使用任何一个解决问题。
或者，我们可以使用这些命令稳定我们的 OpenCV 版本，假设您已经安装了 anaconda。
conda install -c conda-forge opencv=4.1.0
pip install opencv-contrib-python