Revision of fulldisk2jpg.py

Lucas Teske revisou este gist 9 years ago. Ir para a revisão

1 file changed, 15 insertions, 2 deletions

fulldisk2jpg.py

			@@ -40,12 +40,14 @@ for i in lritfiles:
40	40		curColumns = 0
41	41		curImageId = 0
42	42		pixelAspect = 1
	43	+	coff = 0
43	44		for header in headers:
44	45		if header["type"] == 1:
45	46		curLines += header["lines"]
46	47		curColumns = header["columns"]
47	48		elif header["type"] == 2:
48	49		pixelAspect = float(header["cfac"]) / header["lfac"]
	50	+	coff = header["coff"]
49	51		elif header["type"] == 128: # Segment Identification Header
50	52		imageId = header["imageid"]
51	53		segmentId = header["sequence"]
			@@ -58,10 +60,21 @@ for i in lritfiles:
58	60		grouped[imageId]["lines"] += curLines
59	61		grouped[imageId]["columns"] = curColumns
60	62		grouped[imageId]["pixelAspect"] = pixelAspect
	63	+	grouped[imageId]["startColumn"] = coff
61	64
62	65		for i in grouped:
63	66		print "Processing image %s" %i
64	67		d = grouped[i]
	68	+
	69	+	# Crop Left
	70	+	sc = d["startColumn"]
	71	+	hw = min(d["columns"] - sc, sc)
	72	+	cl = d["startColumn"] - hw
	73	+
	74	+	# Crop Right
	75	+	cf = cl + 2 * hw
	76	+
	77	+	print " Crop Marks: %s %s" % (cl, cf)
65	78		img = Image.new("L", (d["columns"], d["lines"]))
66	79		pixels = np.array([], dtype=np.uint8)
67	80		for z in d["segments"]:
			@@ -71,6 +84,6 @@ for i in grouped:
71	84		img.putdata(pixels)
72	85		newheight = img.size[1] * d["pixelAspect"]
73	86		newheight = int(math.ceil(newheight))
74		-
	87	+	img = img.crop((cl, 0, cf, img.size[1]))
75	88		img = img.resize((img.size[0], newheight))
76		-	img.save("%s.jpg" % i, "JPEG")
	89	+	img.save("%s-crop.jpg" % i, "JPEG")

Lucas Teske revisou este gist 9 years ago. Ir para a revisão

1 file changed, 76 insertions

fulldisk2jpg.py(arquivo criado)

		@@ -0,0 +1,76 @@
1	+	#!/usr/bin/env python
2	+
3	+	'''
4	+	Needs Pillow, xrit and numpy
5	+	pip install xrit Pillow
6	+
7	+	Numpy is better to be installed using distro packages.
8	+	'''
9	+
10	+	import os, math
11	+	import numpy as np
12	+	from PIL import Image
13	+	from xrit import packetmanager
14	+
15	+
16	+	folder = "."
17	+
18	+	lritfiles = [f for f in os.listdir(folder) if os.path.isfile(os.path.join(folder, f)) and ".lrit" in f]
19	+
20	+	grouped = {}
21	+
22	+	def headersFromFile(filename):
23	+	f = open(filename, "rb")
24	+	try:
25	+	k = packetmanager.readHeader(f)
26	+	type, filetypecode, headerlength, datalength = k
27	+	except Exception,e:
28	+	print(" Header 0 is corrupted for file %s" %filename)
29	+	return None
30	+	f.seek(0, 0)
31	+	data = f.read(headerlength)
32	+	headers = packetmanager.getHeaderData(data)
33	+	f.close()
34	+	return headers
35	+
36	+
37	+	for i in lritfiles:
38	+	headers = headersFromFile(i)
39	+	curLines = 0
40	+	curColumns = 0
41	+	curImageId = 0
42	+	pixelAspect = 1
43	+	for header in headers:
44	+	if header["type"] == 1:
45	+	curLines += header["lines"]
46	+	curColumns = header["columns"]
47	+	elif header["type"] == 2:
48	+	pixelAspect = float(header["cfac"]) / header["lfac"]
49	+	elif header["type"] == 128: # Segment Identification Header
50	+	imageId = header["imageid"]
51	+	segmentId = header["sequence"]
52	+	curImageId = imageId
53	+	if not imageId in grouped:
54	+	grouped[imageId] = { "segments": {}, "lines": 0 }
55	+
56	+	grouped[imageId]["segments"][segmentId] = i
57	+
58	+	grouped[imageId]["lines"] += curLines
59	+	grouped[imageId]["columns"] = curColumns
60	+	grouped[imageId]["pixelAspect"] = pixelAspect
61	+
62	+	for i in grouped:
63	+	print "Processing image %s" %i
64	+	d = grouped[i]
65	+	img = Image.new("L", (d["columns"], d["lines"]))
66	+	pixels = np.array([], dtype=np.uint8)
67	+	for z in d["segments"]:
68	+	data = packetmanager.loadData(d["segments"][z])
69	+	data = np.fromstring(data, dtype=np.uint8)
70	+	pixels = np.concatenate((pixels, data))
71	+	img.putdata(pixels)
72	+	newheight = img.size[1] * d["pixelAspect"]
73	+	newheight = int(math.ceil(newheight))
74	+
75	+	img = img.resize((img.size[0], newheight))
76	+	img.save("%s.jpg" % i, "JPEG")

Próximo Anterior