def fill_tab(tab):
if tab == 'canvas-tab':
return [
dash_canvas.DashCanvas(
id='canvas-stitch',
width=canvas_width,
height=canvas_height,
scale=scale,
lineWidth=2,
lineColor='red',
tool="line",
hide_buttons=['pencil'],
image_content=array_to_data_url(
np.zeros((height, width), dtype=np.uint8)),
goButtonTitle='Estimate translation',
),
html.Button('Upload demo data', id='demo'),
image_upload_zone('upload-stitch', multiple=True, width=45),
]
elif tab == 'result-tab':
return [
html.Img(id='stitching-result',
src=array_to_data_url(
np.zeros((height, width), dtype=np.uint8)),
width=canvas_width)
]
else:
return [
html.Img(id='bla', src='assets/stitching.gif', width=canvas_width),
]
def save_segmentation(labs, save_mode):
new_labels = np.array(labs)
np.save('labels.npy', new_labels)
if save_mode == 'png':
color_labels = color.label2rgb(new_labels)
uri = array_to_data_url(new_labels, dtype=np.uint8)
return uri
def upload_content(list_image_string, list_filenames, click,
n_rows, n_cols):
if list_image_string is not None:
order = np.argsort(list_filenames)
image_list = [np.asarray(image_string_to_PILImage(
list_image_string[i])) for i in order]
res = tile_images(image_list, n_rows, n_cols)
return array_to_data_url(res)
elif click:
import os
filelist = glob('./assets/tile*.jpg')
filelist.sort()
image_list = [io.imread(filename) for filename in filelist[:4]]
res = tile_images(image_list, n_rows, n_cols)
return array_to_data_url(res)
else:
raise PreventUpdate
def update_figure(labs):
if labs:
new_labels = np.array(labs)
overlay = segmentation.mark_boundaries(img, new_labels)
overlay = img_as_ubyte(overlay)
return array_to_data_url(overlay)
else:
raise PreventUpdate
def modify_content(n_cl, n_rows, n_cols, overlap, estimate, image_string):
tiles = untile_images(image_string, n_rows, n_cols)
if estimate is not None and len(estimate) > 0:
overlap = []
for line in estimate:
overlap.append(1.1 * line['length'] / tiles.shape[3])
canvas = register_tiles(tiles,
n_rows,
n_cols,
overlaps=overlap,
pad=100)
return array_to_data_url(canvas)
def modify_content(n_cl, n_rows, n_cols, overlap, estimate, image_string):
if image_string is None:
raise PreventUpdate
tiles = untile_images(image_string, n_rows, n_cols)
if estimate is not None and len(estimate) > 0:
overlap_dict = _sort_props_lines(estimate, tiles.shape[2],
tiles.shape[3], n_cols)
else:
overlap_dict = None
canvas = register_tiles(tiles, n_rows, n_cols,
overlap_global=overlap,
overlap_local=overlap_dict,
pad=np.max(tiles.shape[2:])//2,
blending=True)
return array_to_data_url(canvas)
def update_figure_upload(image, string, h, s, w):
mask = parse_jsonstring(string, shape=(round(h / s), round(w / s)))
if mask.sum() > 0:
if image is None:
im = img
image = img
else:
im = image_string_to_PILImage(image)
im = np.asarray(im)
seg = superpixel_color_segmentation(im, mask)
else:
if image is None:
image = img
seg = np.ones((h, w))
fill_value = 255 * np.ones(3, dtype=np.uint8)
dat = np.copy(im)
dat[np.logical_not(seg)] = fill_value
return array_to_data_url(dat)
def description():
return "Remove background of image to extract objects of interest."
layout = html.Div([
html.Div([
html.Div([
html.H2(children='Remove image background'),
dcc.Markdown('''
Draw on the object of interest, and press remove background.'''),
dash_canvas.DashCanvas(
id='canvas-bg',
width=canvas_width,
height=canvas_height,
scale=scale,
image_content=array_to_data_url(img_app3),
lineWidth=4,
goButtonTitle='Remove background',
hide_buttons=['line', 'zoom', 'pan'],
),
html.H6(children=['Brush width']),
dcc.Slider(
id='bg-width-slider',
min=2,
max=40,
step=1,
value=[5]
),
image_upload_zone('upload-image-bg'),
], className="seven columns"),
html.Div([
list_columns = ['length', 'width', 'height']
columns = [{"name": i, "id": i} for i in list_columns]
layout = html.Div([
html.Div([
dash_canvas.DashCanvas(
id='canvas-line',
width=canvas_width,
height=canvas_height,
scale=scale,
lineWidth=2,
lineColor='red',
tool="line",
hide_buttons=['pencil'],
image_content=array_to_data_url(img),
goButtonTitle='Measure',
),
],
className="seven columns"),
html.Div([
html.H3('Draw lines and measure lengths'),
html.H3(children='How to use this app', id='measure-subtitle'),
html.Img(id='measure-help', src='assets/measure.gif', width='100%'),
html.H4(children="Objects properties"),
dash_table.DataTable(
id='table-line',
columns=columns,
editable=True,
),
],
id='download-link',
download="correct_segmentation.png",
href="",
target="_blank"),
dcc.Store(id='cache', data=''),
],
className="four columns"),
html.Div([
dash_canvas.DashCanvas(
id='canvas_',
width=canvas_width,
height=canvas_height,
scale=scale,
lineWidth=2,
lineColor='red',
image_content=array_to_data_url(overlay),
goButtonTitle='Update segmentation',
),
],
className="six columns"),
])
# ----------------------- Callbacks -----------------------------
def callbacks(app):
@app.callback(Output('cache', 'data'), [
Input('canvas_', 'trigger'),
], [
State('canvas_', 'json_data'),
State('canvas_', 'scale'),
dcc.Tabs(id='stitching-tabs',
value='canvas-tab',
children=[
dcc.Tab(label='Image tiles',
value='canvas-tab',
children=[
dash_canvas.DashCanvas(
id='canvas-stitch',
width=canvas_width,
height=canvas_height,
scale=scale,
lineWidth=2,
lineColor='red',
tool="line",
image_content=array_to_data_url(
np.zeros(
(width, width), dtype=np.uint8)),
goButtonTitle='Estimate translation',
),
html.Button('Upload demo data', id='demo'),
image_upload_zone(
'upload-stitch', multiple=True, width=45),
html.Div(id='sh_x', hidden=True),
]),
dcc.Tab(label='Stitched Image',
value='result-tab',
children=[
html.Img(id='stitching-result',
src=array_to_data_url(
np.zeros((height, width),
dtype=np.uint8)),
height=canvas_height,
scale=scale,
filename=filename,
lineWidth=4,
goButtonTitle='Remove background',
hide_buttons=['line', 'zoom', 'pan'],
),
html.H6(children=['Brush width']),
dcc.Slider(id='bg-width-slider', min=2, max=40, step=1, value=[5]),
image_upload_zone('upload-image-bg'),
],
className="six columns"),
html.Div([
html.H3(children='Image without background'),
html.Img(id='segmentation-bg',
src=array_to_data_url(np.zeros_like(img)),
width=canvas_width)
],
className="six columns")
],
className="row")
])
# ----------------------- Callbacks -----------------------------
def callbacks(app):
@app.callback(Output('segmentation-bg', 'src'), [
Input('canvas-bg', 'image_content'),
Input('canvas-bg', 'json_data'),
Input('canvas-bg', 'height')
], [
def update_figure_upload(string):
if string is None:
raise PreventUpdate
return array_to_data_url(img)
def modify_result(contrast, brightness, image_string):
print('in modify result')
img = np.asarray(image_string_to_PILImage(image_string))
img = contrast_adjust(img, contrast)
img = brightness_adjust(img, brightness)
return array_to_data_url(img)
