NOAA RIDGE Radar fringe remover

process.py

import numpy
import requests
import StringIO

# Use Pillow
from PIL import Image

# Get the latest radar image
request = requests.get('http://radar.weather.gov/ridge/Conus/RadarImg/latest_radaronly.gif')

# Get the binary content from the HTTP response
image_data = request.content

# Convert the response data into an image, then feed that into numpy
im = Image.open(StringIO.StringIO(image_data))
im = im.convert('RGBA')
data = numpy.array(im)

# These are all the RGB colors we want to strip
noisy_colors = (
    (255, 255, 255), # White
    (225, 225, 225), # Light Gray
    (227, 227, 227), # Light Gray
    (230, 230, 230), # Light Gray
    (232, 232, 232), # Light Gray
    (235, 235, 235), # Light Gray
    (238, 238, 238), # Light Gray
    (240, 240, 240), # Light Gray
    (004, 233, 231), # Cyan
    (001, 159, 244), # Light Blue
    (000, 034, 240), # Dark Blue
    (003, 000, 244), # Dark Blue
)

# Loop through the noisy colors and find any pixels with that 
# color value. When found, turn the alpha channel to zero 
# to make that pixel transparent
for color in noisy_colors:

    # Get the R,G,B values for the current noisy color. Create a 
    # set of R,G,B,A values to convert it to if found. (The A is 
    # the alpha channel and we set it to zero to make it transparent)
    r1, g1, b1 = color
    r2, g2, b2, a2 = r1, g1, b1, 0

    # This is numpy voodoo that I don't claim to understand yet. Thanks, SO:
    # http://stackoverflow.com/questions/6483489/change-the-color-of-all-pixels-with-another-color
    red, green, blue, alpha = data[:,:,0], data[:,:,1], data[:,:,2], data[:,:,3]
    mask = (red == r1) & (green == g1) & (blue == b1)
    data[:,:,:4][mask] = [r2, g2, b2, a2]    

# Save the modified pixels back out to an image
im = Image.fromarray(data)
im.save('radar.png', 'PNG')