error: (-215:Assertion failed) !ssize.empty() in function 'cv::resize' OpenCV - opencv

Question

I have this old code that is used to run fine in Python 2.7 a while ago. I just updated the code to run in Python 3.8, but when I try to execute it code in Python 3.8 and OpenCV 3.4 I get a resize error and a warning (below)!
Here is the link to the two tif images that are required to run this code.
It's worth noting that both tif images are in the same folder as the Python code
import cv2
import matplotlib.pyplot as plt
import numpy as np
## Code for C_preferred Mask and C_images##
## There are three outputs to this code:
#"Block_order_C.PNG"
#"Out_img.PNG"
#"Output_C.txt"
## Change the image name here
filename_image = '2.tif'
filename_mask = '1.tif'
## OpenCV verison Checking
#print 'OpenCV version used', cv2.__version__
filename = open("Output_C.txt","w")
filename.write("Processing Image : " + str(filename_image) + '\n\n')
## Function to sort the contours : Parameters that you can tune : tolerance_factor and size 0f the image.Here, I have used a fix size of
## (800,800)
def get_contour_precedence(contour, cols):
tolerance_factor = 10
origin = cv2.boundingRect(contour)
return ((origin[1] // tolerance_factor) * tolerance_factor) * cols + origin[0]
## Loading the colored mask, resizing it to (800,800) and converting it from RGB to HSV space, so that the color values are emphasized
p_mask_c = cv2.cvtColor(cv2.resize(cv2.imread(filename_mask),(800,800)),cv2.COLOR_RGB2HSV);
# Loading the original Image
b_image_1 = cv2.resize(cv2.imread(filename_image),(800,800));
cv2.imshow("c_mask_preferred",p_mask_c)
cv2.waitKey();
# convert the target color to HSV, As our target mask portion to be considered is green. So I have chosen target color to be green
b = 0;
g = 255;
r = 0;
# Converting target color to HSV space
target_color = np.uint8([[[b, g, r]]])
target_color_hsv = cv2.cvtColor(target_color, cv2.COLOR_BGR2HSV)
# boundaries for Hue define the proper color boundaries, saturation and values can vary a lot
target_color_h = target_color_hsv[0,0,0]
tolerance = 20
lower_hsv = np.array([max(0, target_color_h - tolerance), 10, 10])
upper_hsv = np.array([min(179, target_color_h + tolerance), 250, 250])
# apply threshold on hsv image
mask = cv2.inRange(p_mask_c, lower_hsv, upper_hsv)
cv2.imshow("mask",mask)
cv2.waitKey()
# Eroding the binary mask, such that every white portion (grids) are seperated from each other, to avoid overlapping and mixing of
# adjacent grids
b_mask = mask;
kernel = np.ones((5,5))
#kernel = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))
sharp = cv2.erode(b_mask,kernel, iterations=2)
# Finding all the grids (from binary image)
contours, hierarchy = cv2.findContours(sharp,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
print (' Number of contours', len(contours))
# Sorting contours
contours.sort(key=lambda x:get_contour_precedence(x, np.shape(b_mask)[0]))
#cv2.drawContours(b_image_1, contours, -1, (0,255,0), 1)
# Label variable for each grid/panel
label = 1;
b_image = b_image_1.copy();
temp =np.zeros(np.shape(b_image_1),np.uint8)
print (' size of temp',np.shape(temp), np.shape(b_image))
out_img = b_image_1.copy()
# Processing in each contour/label one by one
for cnt in contours:
cv2.drawContours(b_image_1,[cnt],0,(255,255,0), 1)
## Just to draw labels in the center of each grid
((x, y), r) = cv2.minEnclosingCircle(cnt)
x = int(x)
y = int(y)
r = int(r)
cv2.putText(b_image_1, "#{}".format(label), (int(x) - 10, int(y)),cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
##
cv2.drawContours(temp,[cnt],0,(255,255,255), -1)
#crop_img = np.bitwise_and(b_image,temp)
r = cv2.boundingRect(cnt)
crop_img = b_image[r[1]:r[1]+r[3], r[0]:r[0]+r[2]]
mean = cv2.mean(crop_img);
mean = np.array(mean).reshape(-1,1)
print (' Mean color', mean, np.shape(mean))
if mean[1] < 50:
cv2.putText(out_img, "M", (int(x) - 10, int(y)),cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 1)
filename.write("Block number #"+ str(label)+ ' is : ' + 'Magenta'+'\n');
else:
cv2.putText(out_img, "G", (int(x) - 10, int(y)),cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 1)
filename.write("Block number #"+ str(label)+ ' is : ' +'Gray'+'\n');
label = label+1;
cv2.imwrite("Block_order_C.PNG",b_image_1)
cv2.imwrite("Out_img.PNG",out_img)
filename.close()
cv2.imshow("preferred",b_image_1)
cv2.waitKey()
Error
[ WARN:0] global C:\projects\opencv-python\opencv\modules\imgcodecs\src\grfmt_tiff.cpp (449) cv::TiffDecoder::readData OpenCV TIFF: TIFFRGBAImageOK: Sorry, can not handle images with IEEE floating-point samples
Traceback (most recent call last):
File "Processing_C_preferred.py", line 32, in
p_mask_c = cv2.cvtColor(cv2.resize(cv2.imread(filename_mask),(800,800)),cv2.COLOR_RGB2HSV);
cv2.error: OpenCV(4.2.0) C:\projects\opencv-python\opencv\modules\imgproc\src\resize.cpp:4045: error: (-215:Assertion failed) !ssize.empty() in function 'cv::resize'

Answer 1

When you read in the image pass the cv::IMREAD_ANYDEPTH = 2 parameter as the second parameter in cv2.imread().
Changing your lines to
p_mask_c = cv2.cvtColor(cv2.resize(cv2.imread(filename_mask, 2),(800,800)),cv2.COLOR_RGB2HSV);
and
b_image_1 = cv2.resize(cv2.imread(filename_image, 2),(800,800));
removes the resize error you're seeing.
But you get another error when changing the color since your TIFF image apparently has only one channel so cv2.COLOR_RGB2HSV won't work..
You could also use multiple flags like cv::IMREAD_COLOR = 1,
p_mask_c = cv2.cvtColor(cv2.resize(cv2.imread(filename_mask, 2 | 1),(800,800)),cv2.COLOR_BGR2HSV);
to read in a color image. But you get a different error. Perhaps you understand this image better than I do and can solve the problem from here on out.