[BUG] - Info messages appearing as warnings in Jupyter notebooks #109

from cucim import CuImage
from dask.distributed import as_completed
from dask.distributed import Client, LocalCluster
import os
import numpy as np

cluster = LocalCluster(dashboard_address= 8789, processes=True)
client = Client(cluster)

# iterate over a set of regions from which to threshold
def process_chunk(params):
    start_loc_list = params[0]
    inp_file = params[1]
    patch_size = params[2]
    slide = CuImage(inp_file)
    res = []
    for start_loc in start_loc_list:
        region = np.array(slide.read_region(start_loc, [patch_size, patch_size], 0))
        if region.flatten().var() > 100:
            res.append(start_loc)
        
    return res

# As the results are processed, put them into a list
def compile_results(futures):
    patches = []

    for future in as_completed(futures):
        res1 = future.result()
        if res1:
            for patch in res1:
                patches.append(patch)
                
    return patches

input_file = "patient_100_node_0.tif"
wsi = CuImage(input_file)
sizes=wsi.metadata["cucim"]["resolutions"]
w = sizes["level_dimensions"][0][0]
h = sizes["level_dimensions"][0][1]
patch_size = 256
num_processes = os.cpu_count()

# compute the coordinates of the image patches
start_loc_data = [(sx, sy)
    for sy in range(0, h, patch_size)
        for sx in range(0, w, patch_size)]

# calculate the number of patches per process/thread
chunk_size = len(start_loc_data) // num_processes

# create list of patches to process
start_loc_list_iter = [(start_loc_data[i:i+chunk_size],input_file,patch_size)  for i in range(0, len(start_loc_data), chunk_size)]

# Threshold each patch asynchronously and return a future
future_result1 = list(client.map(process_chunk, start_loc_list_iter))
patches = compile_results(future_result1)`

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