Laboratorio 7

En este laboratorio se hablara sobre el preprocesamiento de la detección de agujeros.
Se mostraran los histogramas que se generaron.

	def binarizado(im, umbral):
	w, h = im.size
	pix = im.load()
	out = Image.new('RGB', (w, h))
	out_pix = out.load()
	for i in range(w):
	for j in range(h):
	r, g, b = pix[i, j]
	if r > umbral:
	out_pix[i, j] = (255, 255, 255)
	else:
	out_pix[i, j] = (0, 0, 0)
	out.save('imgbin.png', 'PNG')
	return out
	def histogram(im, orientation = VERTICAL):
	tmp = im.copy()
	pix = np.array(tmp.convert('L'))
	if orientation == VERTICAL:
	return [sum(x) for x in zip(*pix)]
	else:
	return [sum(x) for x in pix]
	if __name__ == "__main__":
	im = Image.open(argv[1]).convert('RGB')
	im = binarize(im, 90)
	vertical = histogram(im, VERTICAL)
	horizontal = histogram(im, HORIZONTAL)
	horizontal = list(smooth(np.array(horizontal)))
	vertical = list(smooth(np.array(vertical)))

view raw preprocesamiento.py hosted with ❤ by GitHub

Estos son los datos generados de forma Horizontal:

	0 21675
	1 21675
	2 21675
	3 21675
	4 21675
	5 21675
	6 21675
	7 21675
	8 21675
	9 21675
	10 21675
	11 21666
	12 21520
	13 21342
	14 21106
	15 20648
	16 20415
	17 20222
	18 20113
	19 20014
	20 19906
	21 19826
	22 19718
	23 19666
	24 19641
	25 19670
	26 19721
	27 19826
	28 19934
	29 20043
	30 20157
	31 20325
	32 20595
	33 21045
	34 21622
	35 21674
	36 21675
	37 21675
	38 21675
	39 21675
	40 21672
	41 21613
	42 21573
	43 21521
	44 21395
	45 21257
	46 21028
	47 20517
	48 20172
	49 19919
	50 19769
	51 19654
	52 19499
	53 19371
	54 19231
	55 19246
	56 19344
	57 19506
	58 19810
	59 20164
	60 20809
	61 21059
	62 21103
	63 21143
	64 21196
	65 21297
	66 21439
	67 21658
	68 21675
	69 21675
	70 21675
	71 21671
	72 21554
	73 21409
	74 21171
	75 20698
	76 20414
	77 20196
	78 20038
	79 19908
	80 19796
	81 19703
	82 19616
	83 19548
	84 19476
	85 19432
	86 19361
	87 19313
	88 19264
	89 19177
	90 19120
	91 19150
	92 19171
	93 19320
	94 19366
	95 19414
	96 19476
	97 19528
	98 19600
	99 19690
	100 19801
	101 19927
	102 20077
	103 20250
	104 20439
	105 20800
	106 21500
	107 21667
	108 21675
	109 21675
	110 21675
	111 21675
	112 21675
	113 21675
	114 21675
	115 21675
	116 21675
	117 21675
	118 21675
	119 21675
	120 21675
	121 21675
	122 21675
	123 21675
	124 21675
	125 21675
	126 21675
	127 21675

view raw horizontal.txt hosted with ❤ by GitHub

En Vertical:

	0 32640
	1 32640
	2 32640
	3 32640
	4 32640
	5 32640
	6 32640
	7 32640
	8 32631
	9 32509
	10 32460
	11 32340
	12 31871
	13 31462
	14 31204
	15 30901
	16 30618
	17 30243
	18 29838
	19 29450
	20 29183
	21 29325
	22 29902
	23 30094
	24 29998
	25 29905
	26 29778
	27 29681
	28 29648
	29 29589
	30 29509
	31 29422
	32 29414
	33 29393
	34 29375
	35 29284
	36 29256
	37 29236
	38 29289
	39 29369
	40 29542
	41 29541
	42 29416
	43 29394
	44 29436
	45 29492
	46 29622
	47 29795
	48 30062
	49 30418
	50 30500
	51 30591
	52 30754
	53 30960
	54 31285
	55 31606
	56 31600
	57 31732
	58 31858
	59 31910
	60 31948
	61 32019
	62 32081
	63 32181
	64 32310
	65 32564
	66 32637
	67 32640
	68 32640
	69 32640
	70 32640
	71 32640
	72 32640
	73 32640
	74 32640
	75 32640
	76 32640
	77 32640
	78 32640
	79 32640
	80 32640
	81 32640
	82 32640
	83 32640
	84 32640

view raw vertical.txt hosted with ❤ by GitHub

Imagen binarizada:

Imagen Final: