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 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) elif args.filter == 'raw,sobel': qi = np.int32(do_filter(qi, args.filter)) else: print >> sys.stderr, "unknown filter" sys.exit(1) if args.filterout != None: ip.write_rgb_image(args.filterout, ip.unflatten_rgb_image(np.uint8(qi), d, d)) # ----------------------------- def compute_distance(datachunks): return [np.linalg.norm(qi - do_filter(np.fromstring(c, np.uint8), args.filter)) for c in datachunks] c = 0 for result in process(db.groups(400), compute_distance): for k in result: print k, c c += 1
i = ip.gray_as_rgb(i) return ip.flatten_rgb_image(i) raise Exception('unknown filter') if args.filter == None: qi = np.int32(qi) elif args.filter == 'raw,sobel': qi = np.int32(do_filter(qi, args.filter)) else: print >> sys.stderr, "unknown filter" sys.exit(1) if args.filterout != None: ip.write_rgb_image(args.filterout, ip.unflatten_rgb_image(np.uint8(qi), d, d)) # ----------------------------- def compute_distance(datachunks): return [ np.linalg.norm(qi - do_filter(np.fromstring(c, np.uint8), args.filter)) for c in datachunks ] c = 0 for result in process(db.groups(400), compute_distance): for k in result: print k, c