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app.py
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app.py
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import dash
from dash import dcc
from dash import html
import dash_daq as daq
import plotly.express as px
from dash.dependencies import (Input, Output, State)
from image_ops_scratch import (ImageOperations, read_image_string)
from image_morphs_scratch import MorphologicalTransformations
########################################
external_stylesheets = [
'https://codepen.io/chriddyp/pen/bWLwgP.css'
]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.config['suppress_callback_exceptions'] = True
app.title = 'Image Processing App'
server = app.server
########################################
image_ops = ['None', 'Equalize', 'Flip', 'Mirror', 'Binarize', 'Invert', 'Solarize']
image_morphs = ['None', 'Erode', 'Dilate', 'Open', 'Close', 'Gradient', 'Boundary Extraction']
tab_style = {
'borderBottom': '1px solid #d6d6d6',
'padding': '10px',
'fontWeight': 'bold'
}
tab_selected_style = {
'borderTop': '5px solid #d6d6d6',
'borderBottom': '3px solid #d6d6d6',
'backgroundColor': '#7E8483',
'color': 'white',
'padding': '6px'
}
app.layout = html.Div([
html.Meta(charSet='UTF-8'),
html.Meta(name='viewport', content='width=device-width, initial-scale=1.0'),
html.Div([
html.Div(
id='title-app',
children=[
html.H3(app.title)
],
style={'textAlign' : 'center', 'paddingTop' : 30}
),
html.Div([
dcc.Upload(
id='upload-image',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files')
]),
style={
'width': '100%',
'height': '70px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px',
'backgroundColor': '#F0F1F1'
},
multiple=True
),
], style={'paddingTop' : 50}),
html.Div([
dcc.Tabs(
id='image-processors-tabs',
value='operators',
children=[
dcc.Tab(
label='Operations',
value='operators',
style=tab_style,
selected_style=tab_selected_style,
children=[
html.Div([
# daq.ToggleSwitch(
# id='image-mode',
# size=60,
# label='Gray Scale',
# labelPosition='top',
# color='#717171',
# value=False,
# )
], style={'paddingTop' : 30, 'paddingBottom' : 10}),
html.Div([
dcc.RadioItems(
id='in-operation',
options=[{'label' : op, 'value' : op.lower()} for op in image_ops],
value='none'
),
], className='select-operation')
]
),
dcc.Tab(
label='Transformations',
value='transformers',
style=tab_style,
selected_style=tab_selected_style,
children=[
html.Div([
html.P('Morph level - '),
dcc.Input(id='morph-level', type='number', placeholder='Enter Morph Level - ', value=3),
html.Div([
dcc.RadioItems(
id='in-transformation',
options=[{'label' : tr, 'value' : tr.lower()} for tr in image_morphs],
value='none'
),
], style={'paddingTop' : 20})
], className='select-operation')
]
)
]
)
], className='tab-div')
], className='flex-item-left'),
html.Div(id='result-in-out-image', className='flex-item-right'),
], className='flex-container')
def parse_contents(contents, filename, date):
image_mat = read_image_string(contents=contents)
return image_mat
@app.callback(
Output('result-in-out-image', 'children'),
[Input('image-processors-tabs', 'value')]
)
def set_output_layout(which_tab):
if which_tab == 'operators':
in_out_image_div = html.Div([
html.Div(
children= [
html.H5('Image Used - Output'),
dcc.Loading(
id='loading-op',
type='dot',
children=html.Div(id='output-image-op')
)
],
style={'textAlign' : 'center', 'paddingTop' : 50}
)
])
elif which_tab == 'transformers':
in_out_image_div = html.Div([
html.Div(
children= [
html.H5('Image Used - Output'),
dcc.Loading(
id='loading-morph',
type='dot',
children=html.Div(id='output-image-morph')
)
],
style={'textAlign' : 'center', 'paddingTop' : 50}
)
])
return in_out_image_div
@app.callback(
Output('output-image-op', 'children'),
[
Input('upload-image', 'contents'),
#Input('image-mode', 'value'),
Input('in-operation', 'value'),
# -------
State('upload-image', 'filename'),
State('upload-image', 'last_modified'),
]
)
def get_operated_image(contents, operation, filenames, dates):
image_mode = False
if contents is not None:
imsrc = parse_contents(contents, filenames, dates)
imo = ImageOperations(image_file_src=imsrc)
if (operation == 'equalize'):
out_img = imo.equalize_this(gray_scale=True) if image_mode else imo.equalize_this()
elif (operation == 'flip'):
out_img = imo.flip_this(gray_scale=True) if image_mode else imo.flip_this()
elif (operation == 'mirror'):
out_img = imo.mirror_this(gray_scale=True) if image_mode else imo.mirror_this()
elif (operation == 'binarize'):
out_img = imo.binarize_this(gray_scale=True) if image_mode else imo.binarize_this()
elif (operation == 'invert'):
out_img = imo.invert_this(gray_scale=True) if image_mode else imo.invert_this()
elif (operation == 'solarize'):
out_img = imo.solarize_this(gray_scale=True) if image_mode else imo.solarize_this()
else:
out_img = imo.read_this(gray_scale=True) if image_mode else imo.read_this()
out_image_fig = px.imshow(out_img, color_continuous_scale='gray') if image_mode else px.imshow(out_img)
out_image_fig.update_layout(
coloraxis_showscale=False,
width=600, height=400,
margin=dict(l=0, r=0, b=0, t=0)
)
out_image_fig.update_xaxes(showticklabels=False)
out_image_fig.update_yaxes(showticklabels=False)
output_result = html.Div([
dcc.Graph(id='out-op-img', figure=out_image_fig)
], style={'paddingTop' : 50})
return output_result
@app.callback(
Output('output-image-morph', 'children'),
[
Input('upload-image', 'contents'),
Input('morph-level', 'value'),
Input('in-transformation', 'value'),
# -------
State('upload-image', 'filename'),
State('upload-image', 'last_modified'),
]
)
def get_transformed_image(contents, level, transformation, filenames, dates):
if contents is not None:
imsrc = parse_contents(contents, filenames, dates)
morph = MorphologicalTransformations(image_file_src=imsrc, level=level)
level = 3 if level == None else level
image_src = morph.read_this()
if (transformation == 'erode'):
out_img = morph.erode_image(image_src=image_src)
elif (transformation == 'dilate'):
out_img = morph.dilate_image(image_src=image_src)
elif (transformation == 'open'):
out_img = morph.open_image(image_src=image_src)
elif (transformation == 'close'):
out_img = morph.close_image(image_src=image_src)
elif (transformation == 'gradient'):
out_img = morph.morph_gradient(image_src=image_src)
elif (transformation == 'boundary extraction'):
out_img = morph.extract_boundary(image_src=image_src)
else:
out_img = image_src
out_image_fig = px.imshow(out_img, color_continuous_scale='gray')
out_image_fig.update_layout(
coloraxis_showscale=False,
width=600, height=400,
margin=dict(l=0, r=0, b=0, t=0)
)
out_image_fig.update_xaxes(showticklabels=False)
out_image_fig.update_yaxes(showticklabels=False)
output_result = html.Div([
dcc.Graph(id='out-morph-img', figure=out_image_fig)
], style={'paddingTop' : 50})
return output_result
if __name__ == '__main__':
app.run_server(debug=True)