def do_filter(arr, filt): if filt == None: return arr elif filt == 'raw,sobel': i = ip.unflatten_rgb_image(arr, d, d) i = ip.sobel_scipy(i) i = ip.gray_as_rgb(i) return ip.flatten_rgb_image(i) raise Exception('unknown filter')
def docreate(job): l, f = job img = cv2.resize(f(newimg()), (32, 32)) return (l, "".join([chr(j) for j in flatten_rgb_image(img)]))
from tinydb import TinyDB from parallel import process import imageprocessing as ip import cv2, sys import numpy as np db = TinyDB(parse_args = False) db.arg_parser().add_argument('--image', required = True) db.arg_parser().add_argument('--filter', default = None) db.arg_parser().add_argument('--filterout', default = None) args = db.parse_args() d = 32 qi = ip.flatten_rgb_image(ip.read_rgb_image(args.image)) # ---------- filter ----------- def do_filter(arr, filt): if filt == None: return arr elif filt == 'raw,sobel': i = ip.unflatten_rgb_image(arr, d, d) i = ip.sobel_scipy(i) i = ip.gray_as_rgb(i) return ip.flatten_rgb_image(i) raise Exception('unknown filter') if args.filter == None: qi = np.int32(qi)
from tinydb import TinyDB from parallel import process import imageprocessing as ip import cv2, sys import numpy as np db = TinyDB(parse_args=False) db.arg_parser().add_argument('--image', required=True) db.arg_parser().add_argument('--filter', default=None) db.arg_parser().add_argument('--filterout', default=None) args = db.parse_args() d = 32 qi = ip.flatten_rgb_image(ip.read_rgb_image(args.image)) # ---------- filter ----------- def do_filter(arr, filt): if filt == None: return arr elif filt == 'raw,sobel': i = ip.unflatten_rgb_image(arr, d, d) i = ip.sobel_scipy(i) i = ip.gray_as_rgb(i) return ip.flatten_rgb_image(i) raise Exception('unknown filter')