def get_color(filepath, minimum, maximum):
"""
Get a color image.
"""
fpath = os.path.join(DATA_DIR, filepath)
if not os.path.exists(fpath):
return jsonify({'error': 'File does not exist'})
with rasterio.drivers():
with rasterio.open(fpath) as src:
def get_band(index):
band = src.read_band(index)
zoom = 600.0 / band.shape[1]
return ndimage.interpolation.zoom(band, zoom)
count = src.meta["count"]
bands = map(get_band, get_color_bands(count))
arr = np.dstack(bands)
minimum, maximum = arr.min(), arr.max()
output = scale_image(arr, float(minimum), float(maximum))
return send_file(output, mimetype='image/png')
def get_sigmoidal_contrast(band_index, alpha, beta, minimum, maximum):
"""
( 1 / (1 + exp(b * (a - u))) - 1 / (1 + exp(b)) ) / ( 1 / (1 + exp(b * (a - 1))) - 1 / (1 + exp(b * a)))
"""
if band_index == 0:
count = len(BANDS)
color_bands = get_color_bands(count)
bands = [band for index, band in enumerate(BANDS) if index in color_bands]
bands.reverse()
arr = np.dstack(bands)
else:
arr = BANDS[band_index - 1]
alpha, beta = 0.01 * float(alpha), float(beta)
print alpha, beta
# minimum, maximum = float(minimum), float(maximum)
minimum, maximum = arr.min(), arr.max()
# Normalize the array
extent = float(maximum - minimum)
arr = np.clip(arr, minimum, maximum)
arr = (arr - minimum) / extent
arr = ( 1.0 / (1.0 + np.exp(beta * (alpha - arr))) - 1.0 / (1.0 + np.exp(beta)) ) / ( 1.0 / (1.0 + np.exp(beta * (alpha - 1.0))) - 1.0 / (1.0 + np.exp(beta * alpha)))
# numerator = 1.0 / (1.0 + np.exp(beta * (alpha - arr))) - 1.0 / (1.0 + np.exp(beta))
# denominator = 1.0 / (1.0 + np.exp(beta * (alpha - 1.0))) - 1.0 / (1.0 + np.exp(beta * alpha))
# arr = numerator / denominator
arr *= 255.0
arr = np.round(arr).astype('uint8')
output = StringIO.StringIO()
img = Image.fromarray(arr)
img.save(output, format='PNG')
output.seek(0)
return send_file(output, mimetype='image/png')
