def black_points(image, thresh=127):
points = []
image = as_greyscale(image)
data = np.array(image.getdata())
data.shape = image.size[:2]
width, height = image.size[:2]
for x in range(width):
for y in range(height):
if data[x][y] < thresh:
points.append((y, x))
return points
stats_writer.writerow(row)
def filename_or_file_at(file_path, default_name):
if not file_path:
return default_name
elif os.path.isdir(file_path):
return os.path.join(file_path, default_name)
else:
return file_path
if __name__ == "__main__":
try:
args = parse_args()
image = as_greyscale(Image.open(args.image))
image_name = base_name_no_ext(args.image)
filters = read_filters(args.filters)
except Exception as e:
print e
sys.exit(1)
file_name = image_name + "-" + "-".join(map(base_name_no_ext, args.filters)) + ".csv"
csv_out = sys.stdout if not args.output else open(filename_or_file_at(args.output, file_name), "w")
yaml_out = None if not args.yaml else open(args.yaml, "w")
main(image, image_name, args.rows, args.columns, filters, csv_out,
yaml_out, args.save_cell_images,
filter_image_name=args.filtered_image)
if csv_out != sys.stdout:
csv_out.close()
def as_black_and_white(image, split_point=128, contrast=False):
image = as_greyscale(image)
if contrast:
image = ImageOps.autocontrast(image)
image = Image.eval(image, lambda px: 0 if px < split_point else 255)
return image.convert('1', dither=Image.NONE)