def update(self, index):
self.mi.update()
if index == -1:
index = self.mi.df.index.max()
try:
latest = self.mi.df.iloc[index]
except (IndexError, KeyError):
print "invalid index", index
return
if index == self.last_index:
return
self.last_index = index
filename = latest['filename']
filename = os.path.join(self.root_path, filename[1:])
print filename
if self.status_bar:
self.status_bar.update_filename(filename)
img, chunk = blosc_file.load_blosc_image(filename)
if self.guiwrapper:
self.autolevels = self.guiwrapper.toolbar.autolevel_checkbox.isChecked()
self.absolute_levels = self.guiwrapper.toolbar.absolute_level_checkbox.isChecked()
self.autorange = self.guiwrapper.toolbar.autorange_checkbox.isChecked()
# m = np.ma.masked_where(img > 16383, img)
# print m.mask
self.setImage(img, autoLevels=self.autolevels, autoRange=self.autorange)
if self.absolute_levels:
self.setLevels(0, 16384)
def test_blosc_image_round_trip(self):
filename = os.path.join(self.temp_dir,'blah2.blosc')
image = np.zeros(dtypes.image_dimensions, dtype='uint16')
chunk = np.zeros((1,), dtype=dtypes.chunk_dtype)
data = image.tostring() + chunk.tostring()
blosc_file.write_image_blosc(filename, data)
image2,chunk2 = blosc_file.load_blosc_image(filename)
assert np.all(image == image2)
assert np.all(chunk2 == chunk)
assert image.dtype == image2.dtype
def get_blobs_by_info(self,
index_row,
request_id,
stamp_size,
blob_threshold,
kernel_sigma,
kernel_size,
cell_size,
max_num_blobs,
quality=75,
format='jpeg'):
image, chunk = load_blosc_image(index_row['filename'])
tic = time.time()
image = self.hot_pixel_masker.process(image)
blob_finder = BlobFinder(image,
blob_threshold=blob_threshold,
kernel_size=kernel_size,
kernel_sigma=kernel_sigma,
cell_size=cell_size,
fit_blobs=False)
logger.debug("Found %d blobs in %.2f seconds" %
(len(blob_finder.blobs), (time.time() - tic)))
results = []
for blob in blob_finder.blobs:
if len(results) >= max_num_blobs:
break
row_offset = blob.x - stamp_size // 2
column_offset = blob.y - stamp_size // 2
stamp = image[row_offset:row_offset + stamp_size,
column_offset:column_offset + stamp_size]
if stamp.size == 0: # the blob was too close to an edge of the image, so don't bother returning it
logger.debug(
"Skipping blob at (%d,%d) because it is too close to edge of image"
% (blob.x, blob.y))
continue
results.append(
self.make_image_file(stamp,
index_row_data=index_row,
request_id=request_id,
row_offset=row_offset,
column_offset=column_offset,
num_rows=stamp.shape[0],
num_columns=stamp.shape[1],
scale_by=1,
quality=quality,
format=format))
return results
def update(self, index, autoLevels=False, autoRange=False):
self.mi.update()
if index == -1:
index = self.mi.df.index.max()
try:
latest = self.mi.df.iloc[index]
except (IndexError, KeyError):
print "invalid index", index
return
if index == self.last_index:
return
self.last_index = index
filename = latest['filename']
filename = os.path.join(self.root_path, filename[1:])
print filename
if self.real_time_values:
self.real_time_values.update_filename(filename)
img, chunk = blosc_file.load_blosc_image(filename)
self.setImage(img, autoLevels=autoLevels, autoRange=autoRange)
def update_img(n):
elapsed = time.time() - start_at
if n:
time_per_frame = elapsed / (n)
else:
time_per_frame = 1
sys.stdout.flush()
try:
# npz = np.load(files[n])
# imall = npz['image']
imall, chunk = blosc_file.load_blosc_image(files[n])
except Exception:
return
nblobs = 0
# data = scipy.ndimage.gaussian_filter(imd,2)[::4,::4]
if downsample:
data = cv2.GaussianBlur(imall, (3, 3), 0)[::4, ::4]
else:
data = cv2.GaussianBlur(imall, (3, 3), 0)
im.set_data(data)
mn = data.mean(dtype='float64')
if mn < 1000:
mx = 1000
else:
mx = data.max() + 1000
# mx = 14000
# im.set_clim(mn-200,mn+200)
im.set_clim(0, mx)
try:
time_string = files[n].split('/')[-1].split('_')[1]
time_string = time_string[0:2] + ':' + time_string[
2:4] + ':' + time_string[4:]
txt.set_text(time_string)
except Exception:
pass
print(
"\r%d of %d %.1f minutes elapsed, %.1f minutes remaining, %d blobs"
% (n, len(files), elapsed / 60,
(len(files) - n) * time_per_frame / 60., nblobs)),
return im, txt
def update(self, index):
if index == -1:
index = len(self.filenames)
self.guiwrapper.status_bar.update_index(index)
filename = self.filenames[index]
self.last_index = index
print filename
self.guiwrapper.status_bar.update_filename(filename)
img, chunk = blosc_file.load_blosc_image(filename)
self.autolevels = self.guiwrapper.toolbar.autolevel_checkbox.isChecked(
)
self.absolute_levels = self.guiwrapper.toolbar.absolute_level_checkbox.isChecked(
)
self.autorange = self.guiwrapper.toolbar.autorange_checkbox.isChecked()
self.setImage(img,
autoLevels=self.autolevels,
autoRange=self.autorange)
if self.absolute_levels:
self.setLevels(0, 16384)
def solve_img(filename, solutions_path='./solutions'):
camera = int(re.findall('camera-\d', filename)[0][-1])
img, meta = load_blosc_image(filename)
work_dir = os.path.abspath(
os.path.join(solutions_path,
os.path.split(filename)[1]))
print work_dir
try:
os.makedirs(work_dir)
except OSError:
pass
timestamp = int(filename[-19:])
#bf = blobs.BlobFinder(by_camera[camera].process(img),blob_threshold=7,fit_blobs=False)
bf = blobs.BlobFinder(img,
blob_threshold=12,
fit_blobs=False,
kernel_size=32,
kernel_sigma=5)
xcoords = np.array([blob.x for blob in bf.blobs[:20]])
ycoords = np.array([blob.y for blob in bf.blobs[:20]])
res = pyadn.solve_xy(xcoords, ycoords, work_dir=work_dir)
res['timestamp'] = timestamp
return res
def get_image_by_info(self,
index_row_data,
request_id,
row_offset=0,
column_offset=0,
num_rows=3232,
num_columns=4864,
scale_by=1 / 8.,
quality=75,
format='jpeg'):
image, chunk = load_blosc_image(index_row_data['filename'])
image = self.hot_pixel_masker.process(image)
image = image[row_offset:row_offset + num_rows + 1,
column_offset:column_offset + num_columns + 1]
return self.make_image_file(image,
index_row_data=index_row_data,
request_id=request_id,
row_offset=row_offset,
column_offset=column_offset,
num_rows=num_rows,
num_columns=num_columns,
scale_by=scale_by,
quality=quality,
format=format)
def make_jpeg_from_blosc(filename, **kwargs):
img, chunk = blosc_file.load_blosc_image(filename)
img_jpeg, offset, scale = jpeg.simple_jpeg(img, **kwargs)
image_name = filename.split('/')[-1]
with open('/home/pmc/%s.jpeg' % image_name, 'wb') as f:
f.write(img_jpeg)
def test_blosc_image_write(self):
filename = os.path.join(self.temp_dir,'blah3.blosc')
image = np.random.random_integers(0,2**14-1,size=(31440952//2,)).astype('uint16')
blosc_file.write_image_blosc(filename, image)
image2,chunk2 = blosc_file.load_blosc_image(filename)