pythonopencvdeep-learningneural-networkimread

How to use a picture from a plot for the further code

I tried to use a plot as image for my further code. I load an image in my pretrained model and my output is a tensor variable. In the next step I plot it with Image(img_hr).show(figsize=(18,15)). And after this I would like to use the picture from the plot to convert the colors. But the problem is, I cant use the variable img_hr because the type is tensor.

My idea was in the third last line to read the plot. The input for imagehsv = cv2.cvtColor(img_hr, cv2.COLOR_BGR2HSV) need to be an array and I dont know how to convert the plot.

Here is the error:

imagehsv = cv2.cvtColor(img_hr, cv2.COLOR_BGR2HSV) error: OpenCV(4.5.2) :-1: error: (-5:Bad argument) in function 'cvtColor' Overload resolution failed:

  • src is not a numpy array, neither a scalar
  • Expected Ptr<cv::UMat> for argument 'src'

I am new in python so please forgive me for any bad description or wrong vocabulary. I hope everything is clear otherwise feel free to ask.

Here is the picture of the plot:plot

Does anyone have an idea? Thanks a lot

   from fastai import *
from fastai.vision import *
from fastai.callbacks.hooks import *
from fastai.utils.mem import *
import numpy as np
import cv2 as cv2
import matplotlib as mpl
import matplotlib.pyplot as plt 



def acc_camvid(input, target):
        target = target.squeeze(1)
        mask = target != void_code
        return (input.argmax(dim=1)[mask]==target[mask]).float().mean()

learn=load_learner(r'C:\pretrained_model')


image= r"C:\image.png"

img = open_image(image); img.shape
_,img_hr,b = learn.predict(img)
Image(img_hr).show(figsize=(18,15))    

#image = cv2.imread(Image(img_hr))

imagehsv = cv2.cvtColor(img_hr, cv2.COLOR_BGR2HSV)
plt.imshow(fixColor(imagehsv))
Solution

  • fastai works with PIL Image types. So your variable img_hr is an Image.

    OpenCV uses NumPy ndarray types. You need to convert your Image to a ndarray:

    _, img_hr, b = learn.predict(img)
img_hr = np.array(img_hr)

# PIL uses RGB channel order, not BGR like OpenCV default
imagehsv = cv2.cvtColor(img_hr, cv2.COLOR_RGB2HSV)

# Display your result in HSV color space
cv2.imshow("Image HSV", imagehsv)
cv2.waitKey()