def convert(path_list, annots, batch_size, max_idx, idx):
start = idx * batch_size
end = min(start + batch_size, max_idx)
path_list = path_list[start:end]
meta = pd.DataFrame(columns=['uid', 'flag', 'z_len', 'y_len', 'x_len'])
labels = pd.DataFrame(columns=['uid', 'flag', 'z', 'y', 'x', 'diam', 'vol'])
for i, path in enumerate(path_list):
if os.path.basename(path) == 'b8bb02d229361a623a4dc57aa0e5c485':
# ITK cannot read this file
continue
print('Converting %s' % path)
scan_data, uid = read_scan(path)
if scan_data is None:
continue
slices, spacing, origin = get_data(scan_data)
skip = 0
video.clip(slices, settings.low_thresh, settings.high_thresh)
msk = mask.get_mask(slices, uid)
# msk = mask.segment_lung_mask(slices, uid)
slices = video.normalize(slices, settings.low_thresh, settings.high_thresh)
mask.apply_mask(slices, msk)
slices, starts = trim(slices)
valid, flag = process_annotations(uid, annots, origin, labels, slices.shape, starts)
if not valid:
print('Ignoring %s - bad metadata' % path)
continue
video.write_data(slices, os.path.join(output_path, uid))
meta.loc[meta.shape[0]] = dict(uid=uid, flag=flag, z_len=slices.shape[0],
y_len=slices.shape[1], x_len=slices.shape[2])
return meta, labels
def convert(path_list, annots, batch_size, max_idx, idx):
start = idx * batch_size
end = min(start + batch_size, max_idx)
path_list = path_list[start:end]
meta = pd.DataFrame(columns=['uid', 'flag', 'z_len', 'y_len', 'x_len'])
labels = pd.DataFrame(columns=['uid', 'flag', 'z', 'y', 'x', 'diam', 'vol'])
for i, path in enumerate(path_list):
if os.path.basename(path) == 'b8bb02d229361a623a4dc57aa0e5c485':
# ITK cannot read this file
continue
print('Converting %s' % path)
scan_data, uid = read_scan(path)
if scan_data is None:
continue
slices, spacing, origin = get_data(scan_data)
skip = 0
video.clip(slices, settings.low_thresh, settings.high_thresh)
msk = mask.get_mask(slices, uid)
slices = video.normalize(slices, settings.low_thresh, settings.high_thresh)
mask.apply_mask(slices, msk)
slices, starts = trim(slices)
valid, flag = process_annotations(uid, annots, origin, labels, slices.shape, starts)
if not valid:
print('Ignoring %s - bad metadata' % path)
continue
video.write_data(slices, os.path.join(output_path, uid))
meta.loc[meta.shape[0]] = dict(uid=uid, flag=flag, z_len=slices.shape[0],
y_len=slices.shape[1], x_len=slices.shape[2])
return meta, labels
def phase():
# Get path, filenames, and mask setup
path = path_entry.get()
path_raw, path_images, filenames = get_path(path, filetype="h5")
first_file = os.path.join(path, filenames[0])
mask, coord = get_mask(first_file, border=2)
mask = mask[coord[0] : coord[1], coord[2] : coord[3]]
# Setup summary string
deb = "x size," + str(coord[1] - coord[0]) + "\n"
deb += "y size," + str(coord[3] - coord[2]) + "\n"
deb += "number of files," + str(len(filenames)) + "\n"
deb += "file, instensity, modulation, time\n"
# Run 9-bin phase wrap
i = 0
maxf = str(len(filenames))
# t.set(str(i)+'/'+maxf)
# win.update()
# zz = 0
zz = time.clock()
for ii in xrange(1, 14):
zz = time.clock()
for jj in xrange(10):
pool = Pool(processes=ii)
A = []
for filename in filenames:
A.append((filename, path, path_raw, path_images, mask, coord))
imap1 = pool.map(get_phase, A)
# imap1 = map(get_phase,A)
pool.close()
for x in imap1:
# t.set(str(i)+'/'+maxf)
# win.update()
# i+=1
deb += x
# print x
zz = time.clock() - zz
print ("Process=%d, time=%f") % (ii, zz / 10)
"""
for filename in filenames:
t.set(str(i))
win.update()
z = time.clock()
deb = get_phase(filename, path, path_raw, path_images, mask, coord, deb)
zz+=time.clock()-z
i+=1
"""
# Print summary and save to ./debug.csv
# print deb
f_debug = os.path.join(path, "debug.csv")
f_debug = open(f_debug, "w")
f_debug.write(deb)
f_debug.close()
"""
def play(self, word):
feeble_attempts = 0
guessed_letters = set()
wrong_letters = set()
word_mask = mask.get_mask(word, guessed_letters)
while feeble_attempts < NUMBER_OF_FEEBLE_ATTEMPTS and word != word_mask:
letter = self.guesser.guess_letter(word_mask, guessed_letters, wrong_letters)
if letter in guessed_letters or letter in wrong_letters:
raise Exception()
if letter in word:
guessed_letters.add(letter)
word_mask = mask.get_mask(word, guessed_letters)
else:
wrong_letters.add(letter)
feeble_attempts += 1
return word == word_mask, word_mask, feeble_attempts
def test(nyu2_loader, model, width, height):
for i, image in enumerate(nyu2_loader):
image = torch.autograd.Variable(image, volatile=True).cuda()
out = model(image)
out = out.view(out.size(2),out.size(3)).data.cpu().numpy()
max_pix = out.max()
min_pix = out.min()
out = (out-min_pix)/(max_pix-min_pix)*255
out = cv2.resize(out,(width,height),interpolation=cv2.INTER_CUBIC)
cv2.imwrite(os.path.join(args.output, "out_grey.png"),out)
out_grey = cv2.imread(os.path.join(args.output, "out_grey.png"),0)
out_color = cv2.applyColorMap(out_grey, cv2.COLORMAP_JET)
cv2.imwrite(os.path.join(args.output, "out_color.png"),out_color)
vol = get_volume(out_grey, args.json)
print("Volume:")
print(vol)
print("unit: cm^3")
out_file = open(os.path.join(args.output, "out.txt"), "w")
out_file.write("Volume:\n")
out_file.write(str(vol))
out_file.write("\n")
out_file.write("unit: cm^3")
out_file.close()
get_mask(out_grey, args.json, args.output)
if __name__ == "__main__":
args = parser.parse_args()
cmap = args.cmap
labels = np.load(args.labels)
scale = args.scale_factor
mask = None
if args.video:
# Load video and reshape labels
frame = skvideo.io.vread(args.video, num_frames=1)[0]
M, N, _ = frame.shape
# Upscale the labels if needed
if scale > 1:
upscaled = scale_labels(labels, M, N, scale)
labels_grid = upscaled
else:
labels_grid = np.reshape(labels, (M, N))
# Display the image, with or without masking out the background
if args.use_mask:
mask = get_mask(skvideo.io.vread(args.video))
show_with_mask(labels_grid, mask)
else:
show_overlay(labels_grid,
frame,
args.cmap,
save_image=args.save_image)
else:
show_lables(labels, cmap=cmap, save_image=args.save_image)
sys.stdout.write('.')
'''
return "%s,%f,%f\n" % (filename, ave_int, ave_mod)
if __name__ == '__main__':
#path = diropenbox('Pick directory to process',default=r'c:\phase')
path = r'C:\Users\jsaredy\Desktop\4 1_20130710'
#path = r'C:\Users\jsaredy\Desktop\run3'
path_raw, path_images, filenames = get_path(path, 'h5')
first_file = os.path.join(path,filenames[0])
mask,coord = get_mask(first_file, border=2)
mask = mask[coord[0]:coord[1],coord[2]:coord[3]]
#coord [0] = x_min, [1] = x_max, [2] = y_min, [3] = y_max
deb = ''
#for filename in filenames:
# deb = get_phase(filename, path, path_raw, path_images, mask, coord, deb)
pool = Pool()
A=[]
for filename in filenames:
A.append((filename, path, path_raw, path_images, mask, coord))
zz = time.clock()
imap1 = pool.imap(get_phase,A)
#imap1 = map(get_phase,A)
pool.close()
pool.join()
#
print("Loading video %s..." % filename)
num_frames = 0
vid = skvideo.io.vread(filename, num_frames=num_frames,
outputdict={"-pix_fmt": "gray"})[:, :, :, 0]
vid_color = skvideo.io.vread(filename, num_frames=num_frames)
frame_rate = skvideo.io.ffprobe(filename)['video']['@avg_frame_rate']
T, M, N = vid.shape
if args.small_size:
M = min(M, 150)
N = min(N, 150)
if args.small_time:
T = min(T, 149)
width = N
is_loopable = get_mask(vid_color)
np.set_printoptions(precision=2)
if USE_EMBEDDINGS:
embeddings_helper.setup(args, T) # TODO: something's off - shouldn't need all the frames
frames = embeddings_helper.export_frames()
lookup_table.compute_lookup_table(vid_color)
def id_to_loc(id):
if id < 0: raise Exception("ID must be >= 0")
i = id // width
j = id % width
if i >= M or j >= N:
raise Exception("Node ID {} too big coord would be ({}, {})".format(id, i, j))
def main():
sheet = cv2.imread("media/sheet.png")
s = open("media/rows.txt", "r").read()[:-1] # Remove newline
rows = [int(n) for n in s.split(" ")]
nb_rows = len(rows)
nb_cols = max(rows)
# Get sprite positions from mask
mask = get_mask()
boxes = get_bounding_boxes(mask) # box is [x, y, w, h]
# Sanity check
assert len(boxes) == sum(rows)
# Sort boxes
boxes = sort_boxes(boxes, rows)
# Get sprites from initial sheet, using sorted boxes positions
sprites = get_sprites(boxes, sheet)
# Save each sprite
# for i in range(nb_rows):
# for j in range(rows[i]):
# cv2.imwrite(f"media/sprite_{i}{j}.png", sprites[i][j])
# Get sprite max size
sizes = []
for r in sprites:
for s in r:
sizes.append(len(s))
sizes.append(len(s[0]))
sprite_size = max(sizes) + 10
# Create new sprite sheet
new_sheet = np.zeros((nb_rows * sprite_size, nb_cols * sprite_size, 3))
# From bottom
for i in range(nb_rows):
for j in range(rows[i]):
pos_i = i * sprite_size + sprite_size
pos_j = j * sprite_size + sprite_size // 2
new_sheet[pos_i - sprites[i][j].shape[0]:pos_i, pos_j:pos_j +
sprites[i][j].shape[1], ] = sprites[i][j].copy()
cv2.imwrite("media/fixed_sheet.png", new_sheet)
# Transparent background
img = Image.open('media/fixed_sheet.png')
img = img.convert("RGBA")
datas = img.getdata()
newData = []
for item in datas:
if item[0] == 0 and item[1] == 0 and item[2] == 0:
newData.append((255, 255, 255, 0))
else:
newData.append(item)
img.putdata(newData)
img.save("media/transparent_sheet.png", "PNG")
print("Done!")
def test_get_mask(self):
self.assertEqual(mask.get_mask('spam', []), '****')
self.assertEqual(mask.get_mask('spam', ['a', 'p']), '*pa*')
self.assertEqual(mask.get_mask('spam', ['a']), '**a*')
self.assertEqual(mask.get_mask('spam', ['m', 'a', 'p', 's']), 'spam')
self.assertEqual(mask.get_mask('', []), '')
okeys = []
fmtt = ''
header = '# '
for i in xrange(len(args.outputs)):
kupper = args.outputs[i].upper()
if kupper == 'COADD_OBJECTS_ID' or kupper == 'MODEST_CLASS':
fmtt += '%d '
else:
fmtt += '%.6f '
header += kupper + ' '
okeys.append(kupper)
else:
okeys = ''
if args.ids == None:
Bmask = mask.get_mask(Mk, args.path + fitsfile, output_keys=okeys)
masked_data = Bmask['MASK']
maskout = 'masked_data_' + range_z
else:
Bmask = mask.get_mask(Mk, args.path + fitsfile, output_keys=okeys, input_ids=args.ids)
masked_data = Bmask['MASK']
maskout = 'masked_data_ids'
if args.outputs != None:
fileoutputs = 'Output_catalog.txt'
if args.root != None: fileoutputs = args.root + '_' + fileoutputs
temp = Bmask[args.outputs[0].upper()]
for i in xrange(1, len(args.outputs)):
temp = vstack((temp, Bmask[args.outputs[i].upper()]))
with open(fileoutputs, 'wb') as fout:
fout.write(header + '\n')