sidgan/etci-2021-competition-on-flood-detection

Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training

Siddha Ganju

Currently, I am an Architect at Nvidia focusing on the Self-Driving initiative. I work towards stable and scalable training of neural networks on very large data centers, and utilize simulation to validate the neural networks.

In 2017 I led NASA's Long-Period Comets team within their AI accelerator, called Frontier Development Lab, where we use machine learning to develop meteor detectors. Recently this project was able to provide the first-ever instrumental evidence of an outburst of 5 meteors coming from a previously known comet, called C/1907 G1 (Grigg-Mellish). As a member of the NASA FDL AI Technical Committee, I'm working towards incorporating AI in many space science projects!

I have also authored a book on Practical Deep Learning for Cloud, Mobile & Edge - O'Reilly Publishers

	** Featured as a learning resource on the official Keras website**

[Online on Safari] | [Buy on Amazon] | [Online on Google Books] | [Book Website] | [Presentation on Slideshare]

etci-2021-competition-on-flood-detection's Issues

TypeError: Can't convert object of type 'numpy.float64' to 'str' for 'filename'

Unable to visualize images in Data_Viz notebook

I was going through your repository to understand visualization of data in ETCI20201 competition.And I have few queries
1.On executing the cells related to downloading the data,when i execute the below code the number of image paths comes out to be 66812.But in your text cell,the number of images is 33406.Any reason why this is happening?

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

Secondly,on executing the below code in the data_viz notebook

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 

Using random indices when you call show_all_four_images,the following error is encountered

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)

The issue can be resolved when I convert it to int,but then the visualization is not good.
As such,I feel that there is some issues in the all_image_path section,because the number of images must be 33406 according to torch-rs but when I execute your code it comes out to be 4 times that amount.
thanks

Hello, could you tell me how to get dataset?

I can't get the full dataset on codalab. I only can get the train part from Data_Viz.ipynb. could u tell me how to get valid part and test part? Much thanks!