Type conversion
Using opencv-python to add object-detection rectangle for the image:

import cv2

import matplotlib.pyplot as plt
import numpy as np

img = cv2.imread("./birds/Martens's Warbler/martens's_warbler.638x520+0+0.999.200x200.0.o_0014.jpg")

cv2.rectangle(img, (21, 34), (185, 158), (255, 0, 0), 1)

The result looks like this

But in a more complicated program, I processed a image from float32 type. Therefore the code looks like:

img = img.astype('int')
cv2.rectangle(img, (21, 34), (185, 158), (255, 0, 0), 1)

But this time, the rectangle disappeared.

The reason is opencv-python use numpy array for image in type of ‘uint8’, not ‘int’! The correct code should be

img = img.astype('uint8')

Check source of image

img = somefunc()
cv2.resize(img, (100, 200))

This code snippet reported error:

TypeError: Expected cv::UMat for argument 'src'

Seems the argument ‘img’ is not a correcttype. So I blindly changed the code to convert ‘img’ to ‘UMat’.

img = somefunc()
cv2.resize(cv2.UMat(img), (100, 200))

It also reported another more inexplicable error:

TypeError: Required argument 'ranges' (pos 2) not found

After long time searching, I finally get the cause: the function ‘somefunc()’ returned a tuple ‘(img, target)’ instead of only ‘img’…
I should look more closely into argument ‘img’ before changing the code.