alpha = 0
else:
alpha = 255
palette.append((entry.red, entry.green, entry.blue, alpha))
except IndexError: # pad with zeroes
palette.append((0, 0, 0, 0))
rows = []
img = []
for i in range(1, (int(options.width)) + 1):
rows.append(color_index)
for i in range(0, int(options.height)):
img.append(rows)
w = png.Writer(int(options.width),
int(options.height),
palette=palette,
bitdepth=8)
w.write(f, img)
else: # use RGBA
rows = []
img = []
for i in range(1, (int(options.width) * 4) + 1):
if i % 4 == 1:
rows.append(colormap_entry.red)
elif i % 4 == 2:
rows.append(colormap_entry.green)
elif i % 4 == 3:
rows.append(colormap_entry.blue)
elif i % 4 == 0:
for row in data[:, :, :, i]:
data_set = ()
for pixel in row:
#total=0
for value in pixel:
data_set += (value, )
#total+=value
input_pop_views[cnt].set('rate',
input_rate / (256) * value)
#print input_weights[cnt]
cnt += 1
png_data.append(data_set)
# write out a png for debugging
with open(basepath + '/generated/' + str(i) + '.png', 'wb') as f:
w = png.Writer(32, 32)
w.write(f, png_data)
print "[%d] Running simulation step %d" % (node, stop)
pynn.run(tstop)
# save final weights
with open("%s_final_weights.wgt" % (file_stem, ), 'wb') as f:
pickle.dump([
input_projection.getWeights(format='array'),
l1_projection.getWeights(format='array')
], f)
print "[%d] Writing spikes to disk" % node
l0_exc_population.printSpikes('%s_exc_0.ras' % (file_stem, ))
l1_exc_population.printSpikes('%s_exc_1.ras' % (file_stem, ))
def export_png_grid(table,
width,
height,
title='output',
pixel_size=16,
bitdepth=8,
alpha=True):
print('Started rendering image for table ', title)
#Takes a table from the database, and exports it into a png
#width and height are that of the model itself
#pixel_size is how many pixels represent one side of a patch (i.e., one small grid box)
#The tables are obtained from meta.tables (make use of keys() of this to get what you want)
initial_time = datetime.now()
#Getting all patched in the grid
s = table.select()
all_patches = conn.execute(s)
#If the alpha channel is used, 4 channels will be used, otherwise 3
channels = 4 if alpha else 3
#this_grid is an array that shall be used for holding the color info
#By default, it will hold rgb(0,0,0) values, that is, all pixels are black
#The png file is stored as a list of lists
#The inner lists represent rows in the image. They contain the channels of each pixel
#For example, [[0,0,0, 255,102,16],[123,21,23, 12,69,147]] has 2 pixels only in the rgb mode
this_grid = []
for i in range(height):
for j in range(pixel_size):
row = [0] * width * channels * pixel_size
this_grid.append(row)
#Looping through the patches and changing the colors appropriately
#The table here has 4 columns - id, x_coordinate, y_coordinate, energy (all are integers)
for patch in all_patches:
#Root condition for changing defaults (default values are rgb(0,0,0), i.e. black, everywhere)
energy = patch[3]
if energy > 5:
#Nested for loops enables scaling a patch to multiple pixels as per 'pixel_size'
for i in range(pixel_size):
for j in range(pixel_size):
#If the right parameters were not entered, out of bounds exception may occur
try:
#x_pos and y_pos are the indices in this_grid that represents a patch
#The following code makes sure scaling to 'pixel_size' is made possible
#Also, depending on presence of an alpha channel, the length can vary
x_pos = pixel_size * channels * patch[1]
y_pos = pixel_size * patch[2]
color = patch_color(energy)
this_grid[i + y_pos][j * channels + x_pos +
0] = color[0]
this_grid[i + y_pos][j * channels + x_pos +
1] = color[1]
this_grid[i + y_pos][j * channels + x_pos +
2] = color[2]
if alpha:
this_grid[i + y_pos][j * channels + x_pos +
3] = color[3]
except Exception as e:
print(e, patch)
w = png.Writer(
width=pixel_size * width,
height=pixel_size * height,
greyscale=False,
alpha=alpha,
bitdepth=bitdepth,
)
f = open(os.path.join(create_output_dir(), title + '.png'), 'wb')
w.write(f, this_grid)
f.close()
final_time = datetime.now()
print('Time taken to render ', title, (final_time - initial_time),
' for total pixels ', height * width * (pixel_size**2))
def _save_png(data: np.ndarray, dest: BinaryIO, colors=None):
w, h = data.shape
writer = png.Writer(w, h, bitdepth=8, alpha=False, palette=colors)
rows = (data[:, i].tobytes() for i in range(data.shape[1]))
writer.write(dest, rows)
def WritePngFile(self, path):
with open(path, "wb") as f:
png.Writer(**self.metadata).write_array(f, self.pixels)
def extract(args, action, extractpath, a):
codec = None
foundhh = None
ob = None
extracttype = dict(extractboth=-1,
extractcolor=oni.NODE_TYPE_IMAGE,
extractdepth=oni.NODE_TYPE_DEPTH,
extractir=oni.NODE_TYPE_IR)[action]
targetnid = None
seekframe = args.fseek
endframe = args.fduration < 0 and -1 or seekframe + args.fduration
# scan all and keep pre and last
r = oni.Reader(a)
while True:
h = r.next()
if h is None:
break
if h["rt"] == oni.RECORD_NODE_ADDED:
hh = oni.parseadded(a, h)
if hh["nodetype"] == extracttype:
targetnid = h["nid"]
codec = hh["codec"]
foundhh = hh
print "!!found matching for ", targetnid, codec
if codec == "16zt":
if xndec is None:
print "xndec is missing cannot decode to png"
sys.exit(-1)
if xndec.doXnStreamUncompressDepth16ZWithEmbTable is None:
print "xndec is doXnStreamUncompressDepth16ZWithEmbTable"
sys.exit(-1)
if png is None:
print "pypng is missing"
sys.exit(-1)
elif h["nid"] == targetnid:
if h["rt"] == oni.RECORD_NEW_DATA:
pd = oni.parsedatahead(a, h)
if pd["frameid"] >= seekframe and (endframe == -1 or
pd["frameid"] < endframe):
print "newdata", pd["frameid"], h["ps"], h["fs"], codec
q = r.streams[h["nid"]]
xres, yres = q["size"]
if codec == "jpeg":
ext = "jpeg"
elif codec == "16zt":
ext = "png"
if ob is None:
ob = xndec.allocoutput16(xres * yres)
else:
ext = "bin"
outfile = "%s%d.%s" % (extractpath, pd["frameid"], ext)
print outfile, codec
of = open(outfile, "wb")
if codec == "jpeg":
of.write(a.read(h["ps"]))
elif codec == "16zt":
code, size = xndec.doXnStreamUncompressDepth16ZWithEmbTable(
a.read(h["ps"]), ob)
aa = array.array("H")
aa.fromstring(ob)
rows = [
aa[i * xres:(i + 1) * xres]
for i in range(0, yres)
]
if args.coloreddepth:
# save content of ob to PNG 16bit with size xres,yres
w = png.Writer(width=xres,
height=yres,
greyscale=True,
bitdepth=8)
w.write(of, [[int(x * 255.0 / 8000.0) for x in y]
for y in rows])
else:
# save content of ob to PNG 16bit with size xres,yres
w = png.Writer(width=xres,
height=yres,
greyscale=True,
bitdepth=16)
w.write(of, rows)
else:
print "unsupported codec", foundhh
sys.exit(0)
of.close()
elif endframe != -1 and pd["frameid"] >= endframe:
break
scene_suzanne = bounding_box_hierarchy(
suzanne + [CheckeredSphere(0, -2 - MAX_RAY_LENGTH, 0, MAX_RAY_LENGTH, WHITE, 0.5)] + balls)
# scene_snowman = bounding_box_hierarchy(scene_snowman)
# scene_test = [CheckeredSphere(0, -2 - MAX_RAY_LENGTH, 0, MAX_RAY_LENGTH, WHITE, 0.5)]
pixelmap = [[(255, 0, 255) if (x // 8 + y // 8) % 2 else (0, 0, 0)
for x in range(WIDTH)] for y in range(HEIGHT)]
for y in tqdm(range(0, HEIGHT, 1), desc="Rendering", ascii=True):
thread_list = []
for x in range(0, WIDTH, 1):
t = threading.Thread(target=raytrace_screen, args=(
y, x, pixelmap, scene_suzanne, lights_sky))
thread_list.append(t)
for thread in thread_list:
thread.start()
for thread in thread_list:
thread.join()
pngmap = [[subpixel for x in range(WIDTH)
for subpixel in pixelmap[y][x]]
for y in range(HEIGHT)]
output_file = open(png_file_name, 'wb')
w = png.Writer(WIDTH, HEIGHT, alpha=False)
w.write(output_file, pngmap)
output_file.close()
def main(argv):
"""Run the PNG encoder with options from the command line."""
(options, infilename, infile, outfile) = parse_options(argv[1:])
if options.read_png:
# Encode PNG to PPM
pngObj = png.Reader(file=infile)
width, height, pixels, meta = pngObj.asDirect()
write_pnm(outfile, width, height, pixels, meta)
else:
# Encode PNM to PNG
mode, width, height, depth, maxval = \
read_pnm_header(infile, ('P1', 'P2', 'P3', 'P4', 'P5', 'P6', 'P7'))
# When it comes to the variety of input formats, we do something
# rather rude. Observe that L, LA, RGB, RGBA are the 4 colour
# types supported by PNG and that they correspond to 1, 2, 3, 4
# channels respectively. So we use the number of channels in
# the source image to determine which one we have. We do not
# care about TUPLTYPE.
greyscale = depth <= 2
pamalpha = depth in (2, 4)
supported = [2**x - 1 for x in range(1, 17)]
try:
bitdepth = supported.index(maxval) + 1
except ValueError:
raise NotImplementedError(
'your maxval (%s) not in supported list %s' %
(maxval, str(supported)))
writer = png.Writer(width,
height,
greyscale=greyscale,
bitdepth=bitdepth,
interlace=options.interlace,
transparent=options.transparent,
background=options.background,
alpha=bool(pamalpha or options.alpha),
gamma=options.gamma,
compression=options.compression)
if mode == png.strtobytes('P4'):
rows = pbmb_scanlines(infile, width, height)
elif mode in (png.strtobytes('P1'), png.strtobytes('P2'),
png.strtobytes('P3')):
rows = ascii_scanlines(infile, width, height, depth, bitdepth)
else:
rows = file_scanlines(infile, width, height, depth, bitdepth)
if options.alpha:
apgmfile = open(options.alpha, 'rb')
_, awidth, aheight, adepth, amaxval = \
read_pnm_header(apgmfile, ('P5', ))
if amaxval != maxval:
raise NotImplementedError(
'maxval %s of alpha channel mismatch %s maxval %s' %
(amaxval, infilename, maxval))
if adepth != 1:
raise ValueError("alpha image should have 1 channel")
if (awidth, aheight) != (width, height):
raise ValueError("alpha channel image size mismatch"
" (%s has %sx%s but %s has %sx%s)" %
(infilename, width, height, options.alpha,
awidth, aheight))
arows = file_scanlines(apgmfile, width, height, 1, bitdepth)
merged = png.MergedPlanes(rows, depth, arows, 1, bitdepth)
writer.write(outfile, merged)
apgmfile.close()
else:
writer.write(outfile, rows)
if infilename != '-':
# if open - then close
infile.close()
# print(f"Emit RLE of {rep}")
c = fb[ptr]
ptr = ptr + 1
for _ in range(rep):
o.append(c)
if len(o) != w * h:
raise Exception(f"{f}: output {len(o)}, expected {w*h}")
oa = np.array(o, dtype=np.uint8)
oa = np.reshape(oa, (h, w))
oa = np.flipud(oa)
return oa, palette
if __name__ == "__main__":
import png
f = sys.argv[1]
try:
oa, palette = read_ibg(f)
h, w = oa.shape
print(f"{f}: format {w} x {h}")
with open(f.replace(".ibg", ".png"), "wb") as g:
pw = png.Writer(width=w, height=h, palette=palette[:, 0:3])
pw.write(g, oa)
except Exception as e:
print(f"{f}: failed: {e}")
def get_writer(width, height):
return png.Writer(width, height, greyscale=False, alpha=True)
def saveUint16(z, path):
# Use pypng to write zgray as a grayscale PNG.
with open(path, 'wb') as f:
writer = png.Writer(width=z.shape[1], height=z.shape[0], bitdepth=16, greyscale=True)
zgray2list = z.tolist()
writer.write(f, zgray2list)
def extract(self):
if self.verbose:
print('Extracting...')
basename_ = os.path.splitext(os.path.basename(self.filename))[0]
glyph_widths = {}
for cwdh in self.cwdh_sections:
for index in range(cwdh['start'], cwdh['end'] + 1):
glyph_widths[index] = cwdh['data'][index - cwdh['start']]
glyph_mapping = {}
for cmap in self.cmap_sections:
if cmap['type'] == MAPPING_DIRECT:
for code in range(cmap['start'], cmap['end']):
try: #Python2
glyph_mapping[unichr(code)] = code - cmap['start'] + cmap['indexOffset']
except:
glyph_mapping[chr(code)] = code - cmap['start'] + cmap['indexOffset']
elif cmap['type'] == MAPPING_TABLE:
for code in range(cmap['start'], cmap['end']):
index = cmap['indexTable'][code - cmap['start']]
if index != 0xFFFF:
try: #Python2
glyph_mapping[unichr(code)] = index
except:
glyph_mapping[chr(code)] = index
elif cmap['type'] == MAPPING_SCAN:
for code in cmap['entries'].keys():
glyph_mapping[code] = cmap['entries'][code]
# save JSON manifest
json_file_ = open('%s_manifest.json' % basename_, 'w')
json_file_.write(json.dumps({
'version': self.version,
'fileType': self.filetype,
'fontInfo': self.font_info,
'textureInfo': {
'glyph': self.tglp['glyph'],
'sheetCount': self.tglp['sheetCount'],
'sheetInfo': {
'cols': self.tglp['sheet']['cols'],
'rows': self.tglp['sheet']['rows'],
'width': self.tglp['sheet']['width'],
'height': self.tglp['sheet']['height'],
'colorFormat': PIXEL_FORMATS[self.tglp['sheet']['format']]
}
},
'glyphWidths': glyph_widths,
'glyphMap': glyph_mapping
}, indent=2, sort_keys=True))
json_file_.close()
# save sheet bitmaps
for i in range(self.tglp['sheetCount']):
sheet = self.tglp['sheets'][i]
width = sheet['width']
height = sheet['height']
png_data = []
for y in range(height):
row = []
for x in range(width):
for color in sheet['data'][x + (y * width)]:
row.append(color)
png_data.append(row)
file_ = open('%s_sheet%d.png' % (basename_, i), 'wb')
writer = png.Writer(width, height, alpha=True)
writer.write(file_, png_data)
file_.close()
print('Done')
import png, array, sys
# this script adds a red dot waypoint grid to the existing map image
# for a better optimized waypoint distribution see script block_img.py
def my_range(start, end, step):
while start <= end:
yield start
start += step
f = open('node_map.png', 'wb') # binary mode is important
w = png.Writer(551, 384)
reader = png.Reader(filename='phibian_map_1.png')
l = reader.read()
#width, height, pixels, metadata = reader.read()
#print width,height,pixels,metadata
pixels = list(l[2])
#print pixels[0]
pix_list = [[0 for col in range(2200)] for row in range(384)]
for y in range(0, 383):
p_row = []
for x in my_range(0, 2200, 4):
if pixels[y][x] == 57 and pixels[y][x +
1] == 57 and pixels[y][x +
2] == 54:
p_row.append(0)
l = list(r.read()[2])
image2d = np.vstack(itertools.imap(np.uint16, l))
image3d = np.reshape(image2d, (651, 651, 3))
filter_edge = np.array([[0, 0, 0], [-1, 1, 0], [0, 0, 0]])
modified = []
for i in range(3):
modified.append(sig.convolve2d(image3d[:, :, i], filter_edge,
mode='valid'))
output = np.abs(np.reshape(np.dstack(modified), (649, (649) * 3)))
f = open('file.png', 'wb')
w = png.Writer(649, 649)
w.write(f, output)
f.close()
r = png.Reader('ascii-dos.png')
l = list(r.read()[2])
asc = np.vstack(itertools.imap(np.uint16, l))
# make a training vector to hold the ascii values
train_data = np.zeros((12 * 8, 16 * 16))
for row in range(np.shape(asc)[0]):
for column in range(np.shape(asc)[1]):
train_data[(row % 12) * 8 + column % 8,
((row / 12) * 16) + (column / 8) / 2] = asc[row, column]
"""
cutouts = np.zeros((96, 4374))
im = image3d[3:, 3:, :]
def savePNG(self, data, palette):
print "Saving file"
file = open(self.out_filename, 'wb')
writer = png.Writer(data.shape[1], data.shape[0],palette=palette)
writer.write(file, data)
file.close()
train_img = array('B', train_imgs.read()) # 无符号字节array数组类型
train_lab = array('b', train_labs.read()) # 有符号字节array数据类型
# test_img = array('B', test_imgs.read())
# test_lab = array('b', test_labs.read())
train_imgs.close() # 关闭文件
train_labs.close()
# test_imgs.close()
# test_imgs.close()
# 保存图像
for (i, label) in enumerate(train_lab):
filename = os.path.join(train_folders[label], str(i) + '.png')
print('writing ' + filename)
with open(filename, 'wb') as img:
image = png.Writer(28, 28, greyscale=True)
data = [
train_img[(i * 28 * 28 + j * 28):(i * 28 * 28 + (j + 1) * 28)]
for j in range(28)
]
image.write(img, data) # 保存训练图像
"""
for (i, label) in enumerate(test_lab):
filename = os.path.join(test_folders[label], str(i) + '.png')
print('writing ' + filename)
with open(filename, 'wb') as img:
image = png.Writer(28, 28, greyscale=True)
data = [test_img[(i*28*28 + j*28) : (i*28*28 + (j+1)*28)] for j in range(28)]
image.write(img, data) # 保存测试图像
"""
def exportToImageFile(cls, texture, outputFilePath):
binaryFileData = bytes()
if texture.encoding == RAW:
binaryFileData = texture.buffer
else:
width, height = texture.width, texture.height
targetBitDepth = 8
flatPixelArray = cls.unpackPixels(texture, targetBitDepth)
if texture.encoding.hasAlpha:
if cls.trimmingEnabled:
width, height, flatPixelArray = cls.trimTransparentEdges(
flatPixelArray, width, height,
texture.encoding.channels)
if cls.blackeningEnabled:
flatPixelArray = cls.blackenTransparentPixels(
flatPixelArray, width, height,
texture.encoding.channels)
if any(flatPixelArray):
# Create an in-memory stream to which we can write the png data.
pngStream = io.BytesIO()
# Attempt to create a palette
channelsPerPixel = len(texture.encoding.channels)
pixels = list(
zip(*(flatPixelArray[i::channelsPerPixel]
for i in range(channelsPerPixel))))
palette = list(set(pixels))
# Palettes cannot contain more than 256 colors. Also, using palettes for greyscale images typically takes more memory, not less.
if len(palette) <= (2**8) and not texture.encoding.isGreyscale:
getAlphaValue = lambda color: color[channelsPerPixel - 1]
palette.sort(key=getAlphaValue)
colorToIndex = dict(
(color, paletteIndex)
for paletteIndex, color in enumerate(palette))
paletteIndexArray = [
colorToIndex[color] for color in pixels
]
# Remove alpha from opaque pixels
if texture.encoding.hasAlpha:
palette = [(color if getAlphaValue(color) < 0xFF else
color[:-1]) for color in palette]
elif texture.encoding.isGreyscale:
palette = [(color[0], ) * 3 for color in palette]
# Write the png data to the stream.
pngWriter = png.Writer(width,
height,
palette=palette,
bitdepth=targetBitDepth)
pngWriter.write_array(pngStream, paletteIndexArray)
else:
# Write the png data to the stream.
pngWriter = png.Writer(
width,
height,
alpha=texture.encoding.hasAlpha,
greyscale=texture.encoding.isGreyscale,
bitdepth=targetBitDepth,
planes=len(texture.encoding.channels))
pngWriter.write_array(pngStream, flatPixelArray)
# Add the penultimate chunk.
finalChunkSize = 12
pngFileByteArray = bytearray(pngStream.getvalue())
binaryFileData = bytes(pngFileByteArray[:-finalChunkSize]
) + cls.penultimateChunk + bytes(
pngFileByteArray[-finalChunkSize:])
if any(binaryFileData):
outputDirectory = os.path.dirname(outputFilePath)
if not os.path.isdir(outputDirectory):
os.makedirs(outputDirectory)
with open(outputFilePath, 'wb') as outputFileHandle:
outputFileHandle.write(binaryFileData)
def write_aln_to_fig(seqs,
outfilename,
sizeincrease=10,
sizexincrease=5,
sizeyincrease=20,
breakup=1):
#all amb are grey, a red, t blue, c yellow, g green
position = {
"A": 1,
"C": 2,
"G": 3,
"T": 4,
"-": 0,
"N": 0,
"Y": 5,
"R": 5,
"W": 5,
"M": 5,
"B": 5,
"V": 5,
"S": 5,
"K": 5,
"H": 5
}
order = {}
count = 0
for i in seqs:
order[i.name] = count
count += 1
array = [''] * len(order)
palette = [(0xff, 0xff, 0xff), (0xff, 0x00, 0x00), (0xff, 0xff, 0x00),
(0x00, 0xff, 0x00), (0x00, 0xff, 0xff), (0x80, 0x80, 0x80)]
for i in seqs:
#duplicateit
std = ""
for j in i.seq:
for k in range(sizexincrease):
std += str(position[j.upper()])
array[order[i.name]] = "".join(std)
start = 0
end = 0
for i in range(breakup):
nend = end
start = nend
end = min(start + (len(array) / breakup), len(array)) + 1
#size increase in blocks
order2 = []
for j in array[start:end]:
for k in range(sizeyincrease):
order2.append(j)
tarray = map(lambda x: map(int, x), order2)
outfile = None
if breakup == 1:
outfile = open(outfilename + ".png", "wb")
else:
outfile = open(outfilename + "." + str(i) + ".png", "wb")
w = png.Writer(len(tarray[0]),
len(tarray),
palette=palette,
bitdepth=4)
w.write(outfile, tarray)
outfile.close()
def finish_image(self):
f = open('images/output/test.png', 'wb')
w = png.Writer(width=WIDTH * SCALE, height=HEIGHT * SCALE, bitdepth=8, greyscale=False)
w.write(f, self.pixels)
return f.name
last = now
dev.wait_for_frames()
c = dev.color
c = cv2.cvtColor(c, cv2.COLOR_RGB2BGR)
d = dev.dac
# Visualize count down
if time.time() - T_start > 5:
filecad = folder + "JPEGImages/%s.jpg" % FileName
filedepth = folder + "depth/%s.png" % FileName
cv2.imwrite(filecad, c)
with open(filedepth, 'wb') as f:
writer = png.Writer(width=d.shape[1],
height=d.shape[0],
bitdepth=16,
greyscale=True)
zgray2list = d.tolist()
writer.write(f, zgray2list)
FileName += 1
if time.time() - T_start > RECORD_LENGTH + 5:
dev.stop()
serv.stop()
break
if time.time() - T_start < 5:
cv2.putText(c, str(5 - int(time.time() - T_start)),
(240, 320), cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, 4,
(0, 0, 255), 2, cv2.LINE_AA)
def write(self):
w = png.Writer(width=self.width, height=self.height, greyscale=True)
with open(self.outfile, 'wb') as f:
w.write(f, self.image)
import os
import pydicom
import matplotlib.pyplot as plt
np.set_printoptions(threshold=sys.maxsize)
dcm_dir = "/home/lin/Desktop/test/patient/"
png_dir = "/home/lin/Desktop/test/png"
for dcm_name in os.listdir(dcm_dir)[:20]:
if dcm_name.endswith("dcm"):
print(os.path.join(dcm_dir, dcm_name))
img = pydicom.dcmread(os.path.join(dcm_dir, dcm_name))
img = img.pixel_array
wl, wh = (100, 150.0)
img = img.astype("float32").clip(wl, wh)
img = (img - wl) / (wh - wl) * 256
img = img.astype("uint8")
# plt.imshow(img)
# plt.show()
writer = png.Writer(width=img.shape[1], height=img.shape[0], bitdepth=8, greyscale=True)
img = img.tolist()
img_path = os.path.join(png_dir, os.path.basename(dcm_name).replace("dcm", "png"))
with open(img_path, "wb") as f:
writer.write(f, img)
def save_ora(size: Tuple[int, int],
layers: List["Layer"],
colors: List[Tuple[int, int, int, int]],
merged: np.ndarray,
path: str,
**kwargs):
"""
An ORA file is basically a zip archive containing an XML manifest and a bunch of PNGs.
It can however contain any other application specific data too.
"""
w, h = size
# Build "stack.xml" that specifies the structure of the drawing
image_el = ET.Element("image", version="0.0.3", w=str(w), h=str(h))
stack_el = ET.SubElement(image_el, "stack")
has_empty_frame = False
for i, layer in reversed(list(enumerate(layers))):
visibility = "visible" if layer.visible else "hidden"
if len(layer.frames) == 1:
# Non-animated layer
ET.SubElement(stack_el, "layer", name=f"layer{i}_frame{0}",
src=f"data/layer{i}_frame{0}.png")
else:
# Animated layer
layer_el = ET.SubElement(stack_el, "stack", name=f"layer{i}",
visibility=visibility)
for j, frame in reversed(list(enumerate(layer.frames))):
if frame is not None:
ET.SubElement(layer_el, "layer", name=f"layer{i}_frame{j}",
src=f"data/layer{i}_frame{j}.png")
else:
ET.SubElement(layer_el, "layer", name=f"layer{i}_frame{j}",
src=f"data/empty.png")
has_empty_frame = True
stack_xml = b"<?xml version='1.0' encoding='UTF-8'?>" + ET.tostring(image_el)
# Create ZIP archive
with zipfile.ZipFile(path, mode="w", compression=zipfile.ZIP_DEFLATED) as orafile:
orafile.writestr("mimetype", "image/openraster", compress_type=zipfile.ZIP_STORED)
orafile.writestr("stack.xml", stack_xml)
for i, layer in reversed(list(enumerate(layers))):
for j, frame in reversed(list(enumerate(layer.frames))):
if frame is not None:
with io.BytesIO() as f:
_save_png(frame, f, colors=colors)
f.seek(0)
orafile.writestr(f"data/layer{i}_frame{j}.png", f.read())
if has_empty_frame:
empty_frame = np.zeros(size, dtype=np.uint8)
with io.BytesIO() as f:
_save_png(empty_frame, f, colors=colors)
f.seek(0)
orafile.writestr(f"data/empty.png", f.read())
# Thumbnail
# Can be max 256 pixels in either dimension.
aspect = w / h
if aspect >= 1:
wt = min(w, 256)
ht = int(wt / aspect)
else:
ht = min(h, 256)
wt = int(ht * aspect)
thumbnail = scale(merged, wt, ht)
rgba_thumbnail = make_rgba_image(thumbnail, colors)
with io.BytesIO() as f:
writer = png.Writer(width=wt, height=ht, bitdepth=8, greyscale=False, alpha=True)
rows = (rgba_thumbnail[:, i].tobytes() for i in range(ht))
writer.write(f, rows)
f.seek(0)
orafile.writestr(f"Thumbnails/thumbnail.png", f.read())
# Merged image
rgba_merged = make_rgba_image(merged, colors)
with io.BytesIO() as f:
writer = png.Writer(width=w, height=h, bitdepth=8, greyscale=False, alpha=True)
rows = (rgba_merged[:, i].tobytes() for i in range(h))
writer.write(f, rows)
f.seek(0)
orafile.writestr(f"mergedimage.png", f.read())
# Other data (not part of ORA standard)
orafile.writestr("oldpaint.json", json.dumps(kwargs))
def _png(code, version, file, scale=1, module_color=None, background=None):
"""See: pyqrcode.QRCode.png()
This function was abstracted away from QRCode to allow for the output of
QR codes during the build process, i.e. for debugging. It works
just the same except you must specify the code's version. This is needed
to calculate the PNG's size.
This method will write the given file out as a PNG file. Note, it
depends on the PyPNG module to do this.
"""
import png
#Coerce scale parameter into an integer
try:
scale = int(scale)
except ValueError:
raise ValueError('The scale parameter must be an integer')
def scale_code(code):
"""To perform the scaling we need to inflate the number of bits.
The PNG library expects all of the bits when it draws the PNG.
Effectively, we double, tripple, etc. the number of columns and
the number of rows.
"""
#This is the row to show up at the top and bottom border
border_module = [1] * scale
border_row = [1] * _get_png_size(version, scale)
border = [border_row] * scale
#This is one row's worth of each possible module
#PNG's use 0 for black and 1 for white, this is the
#reverse of the QR standard
black = [0] * scale
white = [1] * scale
#This will hold the final PNG's bits
bits = []
#Add scale rows before the code as a border,
#as per the standard
bits.extend(border)
#Add each row of the to the final PNG bits
for row in code:
tmp_row = []
#Add one all white module to the beginning
#to create the vertical border
tmp_row.extend(border_module)
#Go through each bit in the code
for item in row:
#Add one scaled module
if item == 0:
tmp_row.extend(white)
else:
tmp_row.extend(black)
#Add one all white module to the end
#to create the vertical border
tmp_row.extend(border_module)
#Copy each row scale times
for n in range(scale):
bits.append(tmp_row)
#Add the bottom border
bits.extend(border)
return bits
def png_pallete_color(color):
"""This creates a palette color from a list or tuple. The list or
tuple must be of length 3 (for rgb) or 4 (for rgba). The values
must be between 0 and 255. Note rgb colors will be given an added
alpha component set to 255.
The pallete color is represented as a list, this is what is returned.
"""
if color:
rgba = []
if not (3 <= len(color) <= 4):
raise ValueError('Colors must be a list or tuple of length '
' 3 or 4. You passed in '
'"{}".'.format(color))
for c in color:
c = int(c)
if 0 <= c <= 255:
rgba.append(int(c))
else:
raise ValueError('Color components must be between '
' 0 and 255')
#Make all all colors have an alpha channel
if len(rgba) == 3:
rgba.append(255)
return rgba
#If the user passes in one parameter, then they must pass in both or neither
#Note, this is a logical xor
if (not module_color) != (not background):
raise ValueError('If you specify either the black or white parameter, '
'then you must specify both.')
#Create the pallete, or set greyscale to True
if module_color:
palette = [
png_pallete_color(module_color),
png_pallete_color(background)
]
greyscale = False
else:
palette = None
greyscale = True
#The size of the PNG
size = _get_png_size(version, scale)
#We need to increase the size of the code to match up to the
#scale parameter.
code = scale_code(code)
#Write out the PNG
with _get_file(file, 'wb') as f:
w = png.Writer(width=size,
height=size,
greyscale=greyscale,
palette=palette,
bitdepth=1)
w.write(f, code)
def compress(data, *args, **kwargs):
'''PNG compression
'''
TMPFOLDER = tempfile.mkdtemp()
compressed_data = ''
sizes = []
for iz in range(0, data.shape[0]):
img = data[iz, :, :]
colorized = np.zeros((3, img.shape[0], img.shape[1]),
dtype=np.uint16)
# for every value split into three 16 bit samples
colorized[0, :, :] = img % (2**16)
img = img >> 16
colorized[1, :, :] = img % (2**16)
img = img >> 16
colorized[2, :, :] = img % (2**16)
colorized = colorized.swapaxes(0, 1).swapaxes(1, 2)
row_count, column_count, plane_count = colorized.shape
pngfile = open(TMPFOLDER + '/tmp_' + str(iz) + '.png', 'wb')
pngWriter = png.Writer(column_count,
row_count,
greyscale=False,
alpha=False,
bitdepth=16)
pngWriter.write(
pngfile, np.reshape(colorized,
(-1, column_count * plane_count)))
pngfile.close()
with open(TMPFOLDER + '/tmp_' + str(iz) + '.png', 'rb') as fd:
c_data = fd.read()
compressed_data += c_data
sizes.append(len(c_data))
frames = np.zeros((len(sizes)), dtype=np.uint64)
for i, s in enumerate(sizes):
frames[i] = s
#
#
# no of frames
output = np.uint64(len(sizes)).tobytes()
# frame sizes
output += frames.tobytes()
output += compressed_data
# print sizes
return output
def geom_image(image_data, norm=None, vmin=None, vmax=None):
"""
Displays image specified by ndarray with shape (n, m) or (n, m, 3) or (n, m, 4).
This geom is not as flexible as geom_raster or geom_tile but vastly superior in the terms of
rendering efficiency.
This geom doesn't understand any aesthetics.
It doesn't support color scales either.
The following images will be rendered depending on the input array:
N x M - gray-scale
N x M x 3 - RGB
N x M x 4 - RGBA
The type of values in array can be int, uint or float of any size.
The value for each component of integer arrays should be in the range [0,255].
The value for each component of float arrays should be in the range [0,1] for RGB or RGBA images.
If gray-scale is encoded as float array then the values will be normalized. If arguments vmin/vmax are specified,
they will be used in normalization. Otherwise, min/max value will be computed from the image data.
Parameters
----------
image_data : numpy.ndarray with shape (n, m) or (n, m, 3) or (n, m, 4)
Specifies image type, size and pixel values.
norm : bool
False - disables default scaling of a 2-D float (luminance) input to the (0, 1) range.
vmin, vmax : scalar, optional, default: None
Uses normalized luminance data. Only applied to gray-scale images encoded as float array.
Returns
-------
geom object specification
Examples
--------
>>> import numpy as np
>>> from lets_plot import *
>>> image = np.random.choice([0.0, 1.0], [10, 100, 3])
>>> ggplot() + geom_image(image)
"""
if png == None:
raise Exception("pypng is not installed")
if not is_ndarray(image_data):
raise Exception(
"Invalid image_data: ndarray is expected but was {}".format(
type(image_data)))
if image_data.ndim not in (2, 3):
raise Exception(
"Invalid image_data: 2d or 3d array is expected but was {}-dimensional"
.format(image_data.ndim))
vmin = float(vmin) if vmin else None
vmax = float(vmax) if vmax else None
if vmin and vmax and vmin >= vmax:
raise Exception(
"vmin value must be less then vmax value, was: {} >= {}".format(
vmin, vmax))
# Figure out the type of the image
if image_data.ndim == 2:
height, width = image_data.shape
image_type = 'gray'
nchannels = 1
else:
height, width, nchannels = image_data.shape
if nchannels == 3:
image_type = 'rgb'
elif nchannels == 4:
image_type = 'rgba'
else:
raise Exception(
"Invalid image_data: num of channels in color image expected 3 (RGB) or 4 (RGBA) but was {}"
.format(nchannels))
# Choose scaler function (sometimes - normalization)
if image_data.dtype.kind == 'f':
if image_type == 'gray':
normaize = as_boolean(norm, default=True)
if normaize:
# normalize values (gray-scale, floats)
lower = vmin if vmin else image_data.min()
upper = vmax if vmax else image_data.max()
if lower == upper:
# 'normalize' to grey
def scaler(v):
return 127
else:
offset = -lower
ratio = 255. / (upper - lower)
def scaler(v):
return _scaler_to_byte(v, offset, ratio)
else:
# do not normalize
scaler = _scaler_0_255_byte
else:
# do not normalize values (colors)
scaler = _scaler_0_1_byte
elif image_data.dtype.kind in ('i', 'u'):
# do not normalize values (ints)
scaler = _scaler_0_255_byte
else:
raise Exception(
"Invalid image_data: floating point or integer dtype is expected but was '{}'"
.format(image_data.dtype))
# set output type to int8 - pypng produces broken colors with other types
scale = numpy.vectorize(scaler, otypes=[numpy.int8])
# from [[[R, G, B], [R, G, B]], ...] to [[R, G, B, R, G, B],..], or pypng will fail
image_2d = scale(image_data).reshape(-1, width * nchannels)
png_bytes = io.BytesIO()
png.Writer(width=width,
height=height,
greyscale=(image_type == 'gray'),
alpha=(image_type == 'rgba'),
bitdepth=8).write(png_bytes, image_2d)
href = 'data:image/png;base64,' + str(
base64.standard_b64encode(png_bytes.getvalue()), 'utf-8')
# image bounds (including 1/2 pixel expand in all directions)
xmin = [-0.5]
ymin = [-0.5]
xmax = [width - 0.5]
ymax = [height - 0.5]
mapping = aes(xmin=xmin, ymin=ymin, xmax=xmax, ymax=ymax)
return _geom('image', mapping=mapping, href=href)
rows = int(dataset.Rows)
cols = int(dataset.Columns)
print("Image size.......: {rows:d} x {cols:d}, {size:d} bytes".format(
rows=rows, cols=cols, size=len(dataset.PixelData)))
if 'PixelSpacing' in dataset:
print("Pixel spacing....:", dataset.PixelSpacing)
# use .get() if not sure the item exists, and want a default value if missing
print("Slice location...:", dataset.get('SliceLocation', "(missing)"))
# plot the image using matplotlib
print(dataset.pixel_array)
if for_save:
ds = dataset
shape = ds.pixel_array.shape
image_2d = ds.pixel_array.astype(float)
image_2d_scaled = (np.maximum(image_2d,0) / image_2d.max()) * 255.0
# Convert to uint
image_2d_scaled = np.uint8(image_2d_scaled)
# Write the PNG file
with open('/media/j/DATA/ckpt/AS/2020_08_18_copy/1.png', 'wb') as png_file:
w = png.Writer(shape[1], shape[0], greyscale=True)
w.write(png_file, image_2d_scaled)
else:
plt.imshow(dataset.pixel_array, cmap=plt.cm.bone)
plt.show()
def write_png(self, file_name, cell_size=10):
s = self.to_png_rgbs(cell_size)
w = png.Writer(len(s[0]) // 3, len(s), greyscale=False)
with open(file_name, 'wb') as f:
w.write(f, s)
#zoom=0.003
##
#latitude = 73
#longitude = -40
#zoom=1.0
# creating map using basicProjection
newMap = []
n_ = 600
m_ = 700
getPixel = equirectangularProjection( map_rgb, n, m )
basicProjection = planeProjection( latitude*pi/180
, longitude*pi/180
, 1/float(zoom*min(n_, m_))
)
print "constructing new image ..."
for i in range(n_):
newMap.append([])
for j in range(m_):
(lat, lon) = basicProjection(i-(n_/2), j-(m_/2))
(r,g,b) = getPixel(lat, lon)
newMap[-1] += [r,g,b]
f = open('newMap.png', 'wb')
w = png.Writer(m_, n_)
w.write(f, newMap)
f.close()
def extract_from_bag(rgb_img_list,
path_to_bags,
path_to_annotations,
tol_min=0.06,
tol_max=0.2):
"""
Expects a list of paths to RGB data
and the path to the folder containing the related bags with depth data
Method to pick the nearest depth frame and pcl in time, based
on set time tolerance (min, max).
In our case param values where chosen based on a 30 fps sensor
Based on how timestamps were formatted to create img files, see also DH_IO.py
"""
available_bags = [(datetime.datetime.strptime(objname[:-6],
"%Y-%m-%d-%H-%M-%S"),
objname[:-6], objname[-6:])
for objname in os.listdir(str(path_to_bags))
if objname[-4:] == '.bag']
available_bags.sort(key=lambda x: x[0]) # order chronologically
dimg_list = []
# pcls =[]
img_index = {}
for imgp in rgb_img_list:
filename = str(imgp.split("/")[-1])
out_path_rgb = imgp.split("TBA")[0] + "validated/" + filename
if os.path.exists(out_path_rgb):
continue # skip
basestamp = filename.split('_')[0]
stampsecs = filename.split('_')[1]
if 'jpg' or 'png' in stampsecs:
stampsecs = stampsecs[:-4]
basestamp = basestamp[:10] + ' ' + basestamp[11:13] + ':' + basestamp[
14:16] + ':' + basestamp[17:]
timestring = basestamp + '.' + stampsecs
rgb_time = datetime.datetime.strptime(timestring,
"%Y-%m-%d %H:%M:%S.%f")
try:
img_index[rgb_time]["urls"].append(imgp)
except: # new key
img_index[rgb_time] = {}
img_index[rgb_time]["urls"] = []
img_index[rgb_time]["urls"].append(imgp)
for timekey, path_dict in img_index.items():
# array of images for that timekey
imgps = path_dict["urls"]
origin_path = imgps[0]
filenam = origin_path.split("TBA")[1]
out_path_rgb = origin_path.split("TBA")[0] + "validated/" + filenam
out_path_depth = origin_path.split(
"TBA")[0] + "validated/" + filenam[:-4] + 'depth.png'
# copy RGB file to validated files folder
for n, (bdate, bname, ext) in enumerate(
available_bags
): # find bag file the img belongs to (time-wise)
try:
if timekey >= bdate and timekey < available_bags[n + 1][0]:
tgt_bag = bname + ext
break
except IndexError: # reached end of bag list
if timekey >= bdate:
tgt_bag = bname + ext
break
bag = rosbag.Bag(os.path.join(str(path_to_bags), tgt_bag))
# iterate over bag within a certain time window before and after the rgb timestamp
#t0_min, t0_max = timekey - datetime.timedelta(seconds=tol_min), timekey + datetime.timedelta(seconds=tol_min)
t1_min, t1_max = timekey - datetime.timedelta(
seconds=tol_max), timekey + datetime.timedelta(seconds=tol_max)
#d_img, pcloud = find_nearest_frame(bag, timekey, t0_min, t0_max, search_list = ['/camera/depth/image_raw','/camera/depth/points'])
# If none found, try again with less strict tolerance
#if d_img is None:
d_img, pcloud = find_nearest_frame(
bag,
timekey,
t1_min,
t1_max,
search_list=['/camera/depth/image_raw'])
#if pcloud is None:
# d_img, pcloud = find_nearest_frame(bag, timekey, t1_min, t1_max, search_list=['/camera/depth/points'])
if d_img is None:
dimg_list.append(d_img)
continue
#Save copy of depth image locally, one copy for each crop at that timestamp
d_img.astype(np.uint16)
if path_to_annotations is None:
# Just return/save full depth image
dimg_list.append(d_img)
# save as 16-bit one-channeled PNG
shutil.copyfile(origin_path, out_path_rgb)
with open(out_path_depth,
'wb') as f: # 16-bit PNG img, with values in millimeters
writer = png.Writer(width=d_img.shape[1],
height=d_img.shape[0],
bitdepth=16)
# Convert array to the Python list of lists expected by the png writer.
gray2list = d_img.tolist()
writer.write(f, gray2list)
else: #crop depth image before adding to list
# Crop to 2D bbox or polygon
dimg_list = crop_test(imgps, path_to_annotations, None, d_img,
dimg_list)
