sidgan / etci-2021-competition-on-flood-detection Goto Github PK

all_image_paths = list(paths.list_images("train"))
print(f"Total images: {int(len(all_image_paths)/2)}")

def show_all_four_images(filenames, titles):
    plt.figure(figsize=(20, 10))
    images = []
    for filename in filenames:
        images.append(mpimg.imread(filename))
        
    plt.suptitle(get_image_id(filenames[0]), size=16)
    columns = 4
    
    for i, image in enumerate(images):
        ax = plt.subplot(len(images)/ columns + 1, columns, i + 1)
        ax.set_title(titles[i])
        plt.imshow(image)

    plt.show()
`
import random

titles = ["V V","V H" , "Land or water before flood/Water body image" ,"After Flood/flood image"]

random_index =  random.sample(range(0, len(vv_image_paths)), 10) 
for i in random_index:
    # The assertions make sure we are operating on the right pairs
    assert  get_intensity(vv_image_paths[i]) == get_intensity(flood_image_paths[i])
    assert  get_intensity(vh_image_paths[i]) == get_intensity(water_body_label_paths[i])
    show_all_four_images([vv_image_paths[i], vh_image_paths[i],  
                          water_body_label_paths[i], flood_image_paths[i] ] , titles  throws exception error 

Number of rows must be positive integer not 2.0 
the exception is raised in show_alL_four_images when you run ax.subplot(len(images)/columns+1,columns,i+1)