OpenCV threshold函数(-215)报错：src.type()不匹配问题求助

Hey there! Let’s break down this error and get your code working again, step by step.

What the Error Actually Means #

That scary-looking OpenCV error is just an assertion failure—it’s telling you the image you’re feeding to cv2.threshold() doesn’t meet the function’s requirements. Translating the jargon:

OpenCV(3.4.1) C:\projects\opencv-python\opencv\modules\imgproc\src\thresh.cpp:1406: error: (-215) src.type() == (((0) & ((1 << 3) - 1)) + (((1)-1) << 3)) in function cv::threshold

This simply means: "The input image isn’t an 8-bit single-channel grayscale image"—the only format cv2.threshold() accepts for this binary + Otsu operation. Your blur image (derived from img) is almost certainly a 3-channel color image, or a non-8-bit format like float.

How to Fix It #

You just need to ensure your input image is converted to grayscale before running the thresholding. Here’s the corrected version of your code, with key fixes and standard Python conventions:

import numpy as np
from matplotlib import pyplot as plt
import pandas as pd
import math
from sklearn import preprocessing
from sklearn import svm
import cv2

# Step 1: Get your image into grayscale format
# Option 1: Load directly as grayscale (replace with your image path)
img = cv2.imread("your_image_file.jpg", 0)  # The '0' flag forces grayscale loading

# Option 2: If you already have a color image, convert it
# img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Step 2: Run your existing processing pipeline
blur = cv2.GaussianBlur(img, (5, 5), 0)
ret3, th3 = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
image = np.invert(th3)

plt.imshow(image, 'gray')
plt.show()

Quick Extra Tips #

• I adjusted your import aliases to match common Python norms (np for numpy, plt for pyplot, pd for pandas)—this makes your code easier to read for other developers.
• If your img comes from a source that outputs float values (like some ML preprocessing steps), convert it to 8-bit first before processing: img = img.astype(np.uint8)

内容的提问来源于stack exchange，提问作者SidAvenger