Chained callback with an image

Hello all,

I am new to Dash. I am trying to create an app where I input a brain MRI image. Then, I would use a previously built CNN model to predict whether the imported image has a brain tumor in it or not.

I am struggling in managing to use the image imported in the first callback as the input from which to predict with the model. Here is my code so far:

import datetime
import dash
from dash.dependencies import Input, Output, State
import dash_core_components as dcc
import dash_html_components as html

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

app.layout = html.Div([
    dcc.Upload(
        id='upload-image',
        children=html.Div([
            'Drag and Drop or ',
            html.A('Select Files')
        ]),
        style={
            'width': '100%',
            'height': '60px',
            'lineHeight': '60px',
            'borderWidth': '1px',
            'borderStyle': 'dashed',
            'borderRadius': '5px',
            'textAlign': 'center',
            'margin': '10px'
        },
        # Allow multiple files to be uploaded
        multiple=False
    ),
    html.Div(id='output-image-upload'),
    
    html.Div(id='prediction', style={'position':'absolute', 'left':'950px', 'top':'400px'}),

])

def parse_contents(contents, filename, date):
    return html.Div([
        html.H5(filename),
        html.H6(datetime.datetime.fromtimestamp(date)),

        # HTML images accept base64 encoded strings in the same format
        # that is supplied by the upload
        html.Img(src=contents),
        html.Hr(),
        html.Div('Raw Content'),
        html.Pre(contents[0:200] + '...', style={
            'whiteSpace': 'pre-wrap',
            'wordBreak': 'break-all'
        })
    ])


@app.callback(Output('output-image-upload', 'children'),
              [Input('upload-image', 'contents')],
              [State('upload-image', 'filename'),
               State('upload-image', 'last_modified')])
def update_output(list_of_contents, list_of_names, list_of_dates):        
    
    if list_of_contents is not None:
        children = [
            parse_contents(c, n, d) for c, n, d in
            zip(list_of_contents, list_of_names, list_of_dates)]
    
        return children
   
 
@app.callback(Output('prediction', 'children'),
              [Input('output-image-upload', 'children')])

def update_output(output_before):        
    
    image = output_before
    
    model = load_model('model.h5') 
    dim = (150, 150)
    img = Image.open(image)
    x = np.array(img.resize(dim))
    x = x.reshape(1,150,150,3)
    answ = model.predict_on_batch(x)

    classification = np.where(answ == np.amax(answ))[1][0]
    pred=str(answ[0][classification]*100) + '% Confidence This Is ' + names(classification)
    
    return pred    
    
    
if __name__ == '__main__':
    app.run_server(debug=True, use_reloader=False)

The problem really comes from the second callback where I try to use the image from the previous callback as an input. The rest works great.

Any ideas? Should you have any questions, let me know!

Thanks a lot in advance!

2 posts - 2 participants

Read full topic