diff --git a/.dockerignore b/.dockerignore
new file mode 100644
index 0000000..4d5f617
--- /dev/null
+++ b/.dockerignore
@@ -0,0 +1,4 @@
+**
+!*.py
+!static/
+!config/
diff --git a/.gitignore b/.gitignore
index b6e4761..9b7a254 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,4 @@
+data/
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..099caf3
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,20 @@
+FROM tiangolo/uvicorn-gunicorn-fastapi:python3.8                        
+                                                                        
+RUN /usr/local/bin/python -m pip install --upgrade pip                  
+RUN pip install --no-cache-dir \                                        
+    dash \                                                              
+    plotly \                                                            
+    scikit-image \                                                      
+    pandas \                                                            
+    gunicorn                                                            
+RUN pip install --no-cache-dir requests                                 
+                                                                        
+RUN mkdir -p /app                                                       
+RUN mkdir -p /app/static                                                
+WORKDIR /app                                                            
+                                                                        
+ADD config/ /app/config                                                 
+ADD *.py /app/                                                          
+ADD static/ /app/static/                                                
+                                                                        
+ENTRYPOINT ["gunicorn", "-w", "1", "-b", "0.0.0.0:8050", "app:server"]  
\ No newline at end of file
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/app.py b/app.py
index 241585a..a9131fa 100644
--- a/app.py
+++ b/app.py
@@ -1,213 +1,121 @@
+import flask
 import dash
-import dash_core_components as dcc
-import dash_html_components as html
 from dash.dependencies import Input, Output, State
-import base64
 import json
-import os
 import matplotlib.cm
-import matplotlib.colors as mcolors
-import numpy as np
-import random
-import plotly.express as px
-from skimage import data, transform
-
-
-COLORMAP = 'plasma'
-KEYPOINTS = ['Nose', 'L_Eye', 'R_Eye', 'L_Ear', 'R_Ear', 'Throat',
-             'Withers', 'TailSet', 'L_F_Paw', 'R_F_Paw', 'L_F_Wrist',
-             'R_F_Wrist', 'L_F_Elbow', 'R_F_Elbow', 'L_B_Paw', 'R_B_Paw',
-             'L_B_Hock', 'R_B_Hock', 'L_B_Stiffle', 'R_B_Stiffle']
-N_SUBSET = 3
-IMAGE_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'full_dog.png')
-encoded_image = base64.b64encode(open(IMAGE_PATH, 'rb').read())
-
-img = data.chelsea()
-img = img[::2, ::2]
-images = [img, img[::-1], transform.rotate(img, 30)]
-cmap = matplotlib.cm.get_cmap(COLORMAP, N_SUBSET)
-
-
-def make_figure_image(i):
-    fig = px.imshow(images[i % len(images)])
-    fig.layout.xaxis.showticklabels = False
-    fig.layout.yaxis.showticklabels = False
-    fig.update_traces(hoverinfo='none', hovertemplate='')
-    return fig
-
-
-def draw_circle(center, radius, n_points=50):
-    pts = np.linspace(0, 2 * np.pi, n_points)
-    x = center[0] + radius * np.cos(pts)
-    y = center[1] + radius * np.sin(pts)
-    path = 'M ' + str(x[0]) + ',' + str(y[1])
-    for k in range(1, x.shape[0]):
-        path += ' L ' + str(x[k]) + ',' + str(y[k])
-    path += ' Z'
-    return path
-
-
-def compute_circle_center(path):
-    """
-    See Eqn 1 & 2 pp.12-13 in REGRESSIONS CONIQUES, QUADRIQUES
-    Régressions linéaires et apparentées, circulaire, sphérique
-    Jacquelin J., 2009.
-    """
-    coords = [list(map(float, coords.split(','))) for coords in path.split(' ')[1::2]]
-    x, y = np.array(coords).T
-    n = len(x)
-    sum_x = np.sum(x)
-    sum_y = np.sum(y)
-    sum_x2 = np.sum(x * x)
-    sum_y2 = np.sum(y * y)
-    delta11 = n * np.dot(x, y) - sum_x * sum_y
-    delta20 = n * sum_x2 - sum_x ** 2
-    delta02 = n * sum_y2 - sum_y ** 2
-    delta30 = n * np.sum(x ** 3) - sum_x2 * sum_x
-    delta03 = n * np.sum(y ** 3) - sum_y * sum_y2
-    delta21 = n * np.sum(x * x * y) - sum_x2 * sum_y
-    delta12 = n * np.sum(x * y * y) - sum_x * sum_y2
-
-    # Eqn 2, p.13
-    num_a = (delta30 + delta12) * delta02 - (delta03 + delta21) * delta11
-    num_b = (delta03 + delta21) * delta20 - (delta30 + delta12) * delta11
-    den = 2 * (delta20 * delta02 - delta11 * delta11)
-    a = num_a / den
-    b = num_b / den
-    return a, b
-
-
-def get_plotly_color(n):
-    return mcolors.to_hex(cmap(n))
-
-
-fig = make_figure_image(0)
-
-external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
-
-app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
-server = app.server
-
-options = random.sample(KEYPOINTS, N_SUBSET)
-
-styles = {
-    'pre': {
-        'border': 'thin lightgrey solid',
-        'overflowX': 'scroll'
-    }
-}
-
-app.layout = html.Div([
-    html.Div([
-        dcc.Graph(
-            id='canvas',
-            config={'editable': True},
-            figure=fig)
-    ],
-        className="six columns"
-    ),
-    html.Div([
-        html.H2("Controls"),
-        dcc.RadioItems(id='radio',
-                       options=[{'label': opt, 'value': opt} for opt in options],
-                       value=options[0]
-                       ),
-        html.Button('Previous', id='previous'),
-        html.Button('Next', id='next'),
-        html.Button('Clear', id='clear'),
-        html.Button('Save', id='save'),
-        dcc.Store(id='store', data=0),
-        html.P([
-            html.Label('Keypoint label size'),
-            dcc.Slider(id='slider',
-                       min=3,
-                       max=36,
-                       step=1,
-                       value=12)
-            ], style={'width': '80%',
-                      'display': 'inline-block'})
-    ],
-        className="six columns"
-    ),
-    html.Div([
-        dcc.Markdown("""
-                **Instructions**\n
-                Click on the image to add a keypoint.
-            """),
-        html.Pre(id='click-data', style=styles['pre']),
-        html.Img(src='data:image/png;charset=utf-8;base64,{}'.format(encoded_image))
-    ],
-        className='six columns'
-    ),
-    html.Div(id='placeholder', style={'display': 'none'}),
-    html.Div(id='shapes', style={'display': 'none'})
-]
-)
+import utils, model, view
+from config import Config
+
+
+__version__ = "0.1"
+
+print(f"| Starting version {__version__}")
+
+config = Config('config/config.json')
+db = model.AppModel(config=config)
+cmap = matplotlib.cm.get_cmap('plasma', len(config.options))
+server = flask.Flask(__name__)
+view = view.AppView(__name__, db=db, config=config, server=server)
+
+
+@server.route('/csv/')
+def fetch_csv():
+    return db.to_csv()
+
+
+@server.route('/overview/')
+def fetch_html():
+    return db.to_html()
 
 
-@app.callback(Output('placeholder', 'children'),
+@view.app.callback(Output('placeholder', 'children'),
               [Input('save', 'n_clicks')],
               [State('store', 'data')])
 def save_data(click_s, ind_image):
     if click_s:
-        xy = {shape.name: compute_circle_center(shape.path) for shape in fig.layout.shapes}
+        xy = {shape.name: utils.compute_circle_center(shape.path) for shape in view.fig.layout.shapes}
         print(xy, ind_image)
 
 
-@app.callback(
+@view.app.callback(
+    Output('radio', 'options'),
+    [Input('next', 'n_clicks'),
+     Input('previous', 'n_clicks')]
+)
+def refresh_radio_buttons(click_n, click_p):
+    if not (click_n or click_p):
+        return dash.no_update
+    return view.refresh_radio_buttons()
+
+
+def store_data(db, username, shapes):
+    for shape in shapes:
+        db.add_annotation(
+            name=shape.name, username=username,
+            xy=utils.compute_circle_center(shape.path)
+        )
+
+
+@view.app.callback(
     [Output('canvas', 'figure'),
      Output('radio', 'value'),
      Output('store', 'data'),
-     Output('shapes', 'children')],
+     Output('shapes', 'children'),
+     ],
     [Input('canvas', 'clickData'),
      Input('canvas', 'relayoutData'),
      Input('next', 'n_clicks'),
      Input('previous', 'n_clicks'),
      Input('clear', 'n_clicks'),
-     Input('slider', 'value')],
+     Input('slider', 'value'),
+     Input('input_name', 'value')
+     ],
     [State('canvas', 'figure'),
      State('radio', 'value'),
      State('store', 'data'),
      State('shapes', 'children')]
     )
-def update_image(clickData, relayoutData, click_n, click_p, click_c, slider_val,
+def update_image(clickData, relayoutData, click_n, click_p, click_c, slider_val, username,
                  figure, option, ind_image, shapes):
+
+    # TODO Refactor: Remove if/else statements and instead write multiple
+    # callbacks.
     if not any(event for event in (clickData, click_n, click_p, click_c)):
         return dash.no_update, dash.no_update, dash.no_update, dash.no_update
-
-    if ind_image is None:
-        ind_image = 0
-
+    
+    if ind_image is None: ind_image = 0
     shapes = [] if shapes is None else json.loads(shapes)
-    n_bpt = options.index(option)
 
     ctx = dash.callback_context
     event = ctx.triggered[0]['prop_id']
     button_id = event.split('.')[0]
-    if button_id == 'clear':
-        fig.layout.shapes = []
-        fig.layout.xaxis.autorange = True
-        fig.layout.yaxis.autorange = 'reversed'
-        return make_figure_image(ind_image), options[0], ind_image, '[]'
-    elif button_id == 'next':
-        ind_image = (ind_image + 1) % len(images)
-        return make_figure_image(ind_image), options[0], ind_image, '[]'
-    elif button_id == 'previous':
-        ind_image = (ind_image - 1) % len(images)
-        return make_figure_image(ind_image), options[0], ind_image, '[]'
-    elif button_id == 'slider':
+    if button_id == 'slider':
         for i in range(len(shapes)):
-            center = compute_circle_center(shapes[i]['path'])
-            new_path = draw_circle(center, slider_val)
+            center = utils.compute_circle_center(shapes[i]['path'])
+            new_path = utils.draw_circle(center, slider_val)
             shapes[i]['path'] = new_path
+    elif button_id in ['clear', 'next', 'previous']:
+        if button_id == 'clear':
+            view.fig.layout.shapes = []
+            view.fig.layout.xaxis.autorange = True
+            view.fig.layout.yaxis.autorange = 'reversed'
+        elif button_id == 'next':
+            ind_image = (ind_image + 1) % len(db.dataset)
+            store_data(db, username, view.fig.layout.shapes)
+        elif button_id == 'previous':
+            ind_image = (ind_image - 1) % len(db.dataset)
+            store_data(db, username, view.fig.layout.shapes)
+        return view.make_figure_image(ind_image), view.options[0], ind_image, '[]'
 
     already_labeled = [shape['name'] for shape in shapes]
-    key = list(relayoutData)[0]
+    keys = list(relayoutData) if relayoutData else []
+    key = keys[0] if len(keys) > 0 else ""
     if option not in already_labeled and button_id != 'slider' and 'relayout' not in event:
         if clickData:
             x, y = clickData['points'][0]['x'], clickData['points'][0]['y']
-            circle = draw_circle((x, y), slider_val)
-            color = get_plotly_color(n_bpt)
+            circle = utils.draw_circle((x, y), slider_val)
+            ind_bpt = config.options.index(option)
+            color = utils.get_plotly_color(cmap, ind_bpt)
             shape = dict(type='path',
                          path=circle,
                          line_color=color,
@@ -216,29 +124,35 @@ def update_image(clickData, relayoutData, click_n, click_p, click_c, slider_val,
                          opacity=0.8,
                          name=option)
             shapes.append(shape)
+            #db.add_annotation(
+            #    name=option, username=username,
+            #    xy=utils.compute_circle_center(circle)
+            #)
     else:
         if 'path' in key and button_id != 'slider':
             ind_moving = int(key.split('[')[1].split(']')[0])
             path = relayoutData.pop(key)
             shapes[ind_moving]['path'] = path
-    fig.update_layout(shapes=shapes)
+    view.fig.update_layout(shapes=shapes)
+    
     if 'range[' in key and 'clickData' not in event:
         xrange = relayoutData['xaxis.range[0]'], relayoutData['xaxis.range[1]']
         yrange = sorted((relayoutData['yaxis.range[0]'], relayoutData['yaxis.range[1]']),
                         reverse=True)
-        fig.update_xaxes(range=xrange, autorange=False)
-        fig.update_yaxes(range=yrange, autorange=False)
+        view.fig.update_xaxes(range=xrange, autorange=False)
+        view.fig.update_yaxes(range=yrange, autorange=False)
     elif 'autorange' in key:
-        fig.update_xaxes(autorange=True)
-        fig.update_yaxes(autorange='reversed')
+        view.fig.update_xaxes(autorange=True)
+        view.fig.update_yaxes(autorange='reversed')
+    n_bpt = view.options.index(option) if option in view.options else 0
     if button_id != 'slider' and 'relayout' not in event:
         n_bpt += 1
-    new_option = options[min(len(options) - 1, n_bpt)]
-    return ({'data': figure['data'], 'layout': fig['layout']},
+    new_option = view.options[min(len(view.options) - 1, n_bpt)]
+    return ({'data': figure['data'], 'layout': view.fig['layout']},
             new_option,
             ind_image,
             json.dumps(shapes))
 
 
 if __name__ == '__main__':
-    app.run_server(debug=False, port=8051)
+    view.app.run_server(debug=False, port=8051)
diff --git a/config.py b/config.py
new file mode 100644
index 0000000..a04cd84
--- /dev/null
+++ b/config.py
@@ -0,0 +1,13 @@
+import json
+import os.path as osp
+import glob
+
+
+class Config:
+    def __init__(self, config):
+        assert osp.exists(config)
+
+        with open(config, "r") as fp:
+            for key, val in json.load(fp).items():
+                setattr(self, key, val)
+        self.fnames = glob.glob('data/*.png')
diff --git a/config/config.json b/config/config.json
new file mode 100644
index 0000000..537de18
--- /dev/null
+++ b/config/config.json
@@ -0,0 +1,53 @@
+   {
+       "abbrv" : {
+        "L" : "Left",
+        "R" : "Right",
+        "F" : "Front",
+        "B" : "Back"
+        },
+        "options" : [
+        "Nose",
+        "L_Eye",
+        "R_Eye", 
+        "L_Ear", 
+        "R_Ear", 
+        "Throat", 
+        "Withers", 
+        "TailSet", 
+        "L_F_Paw", 
+        "R_F_Paw", 
+        "L_F_Wrist", 
+        "R_F_Wrist", 
+        "L_F_Elbow", 
+        "R_F_Elbow", 
+        "L_B_Paw", 
+        "R_B_Paw", 
+        "L_B_Hock", 
+        "R_B_Hock", 
+        "L_B_Stiffle", 
+        "R_B_Stiffle"
+    ],
+    "cmap" : [
+        "15188B",
+        "3B1C9D",
+        "591FA7", 
+        "7C21AA", 
+        "7822A9", 
+        "9124A5", 
+        "BD358A", 
+        "CD4877", 
+        "D9586C", 
+        "EA7058", 
+        "F89142", 
+        "FDAA34", 
+        "FDC727", 
+        "FED525", 
+        "1F948C", 
+        "2CB17C", 
+        "50C56A", 
+        "97DA3D", 
+        "BBDF27"
+    ],
+    "urls" : "config/filelist.lst",
+     "n2show" : 5
+}
\ No newline at end of file
diff --git a/config/filelist.lst b/config/filelist.lst
new file mode 100644
index 0000000..4323823
--- /dev/null
+++ b/config/filelist.lst
@@ -0,0 +1,68 @@
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/1de4a9e537_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/1f64955634_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/2feb30f208_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/4f824d3dcd_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/6b2261888d_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/6c9d29d509_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/52355da42f_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/a973f239cd_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/ad397527b2_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/aed4e0b4c4_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/ce25872021_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/de6a9382ca_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/de36b216da_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/ef0061a309_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/bear/fb5ba7ad6e_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/0a7a2514aa_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/3f3b15f083_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/5c7668855e_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/7e2f212fd3_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/8d4ab94e1c_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/8eb0d315c1_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/69f0af42a6_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/1187bbd0e3_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/ad573f7d31_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/b96c57d2c7_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/bf961167a6_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/cd47a23e31_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/d6c1b5749e_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/ec1299aee4_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/cat/eeed0c7d73_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/0d97fba242_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/6acc6049d9_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/6c99ea7c31_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/6ecad29e52_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/8a4a2fc105_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/8b518ee936_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/8e478e73f3_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/9b22b54ee4_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/9b473fc8fe_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/19e8bc6178_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/30dbdb2cd6_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/49fbf0c98a_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/65ab7e1d98_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/73c6ae7711_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/80c4a94706_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/86a8ae4223_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/247d729e36_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/823e7a86e8_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/868d6a0685_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/2465bf515d_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/47269e0499_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/49972c2d14_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/72690ef572_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/aa45f1caaf_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/b0df7c5c5c_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/b72ac6e10b_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/bb337f9830_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/bda224cb25_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/c0e8d4635c_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/c7a1a17308_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/c52bce43db_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/c2406ae462_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/caecf0a5db_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/d292a50c7f_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/dd9fe6c6ac_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/e23cca5244_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/ed8f814b2b_frame015.png
+http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/dog/fcfd81727f_frame015.png
\ No newline at end of file
diff --git a/createfilelist.py b/createfilelist.py
new file mode 100644
index 0000000..dafb1be
--- /dev/null
+++ b/createfilelist.py
@@ -0,0 +1,51 @@
+from bs4 import BeautifulSoup
+import requests
+
+url = 'http://deeplabcut.rowland.harvard.edu/datasets/animal_ytVOS_images/images_jpg/'
+ext = 'iso'
+
+animals=['dog','cat','bear']
+def write(data,fn="filelist.lst"):
+    with open("filelist.lst", "w") as f:
+        for s in data:
+            f.write(str(s) +"\n")
+
+def read(fn="filelist.lst"):
+    with open("filelist.lst", "r") as f:
+      for line in f:
+        score.append(int(line.strip()))
+
+def listurl(url,animals=None, ext=''):
+    page = requests.get(url).text
+    soup = BeautifulSoup(page, 'html.parser')
+    all=[url + '/' + node.get('href') for node in soup.find_all('a') if node.get('href').endswith(ext)]
+    if animals is not None: #then filter
+        urls=[]
+        for a in all:
+            for animal in animals:
+                if animal in str(a):
+                    urls.append(a)
+    else:
+        urls=all
+    return urls
+
+def listimgurl(url,imtype='.jpg', ext=''):
+    page = requests.get(url).text
+    soup = BeautifulSoup(page, 'html.parser')
+    all=[url + '/' + node.get('href') for node in soup.find_all('a') if node.get('href').endswith(ext)]
+    if animals is not None: #then filter
+        urls=[]
+        for a in all:
+            if imtype in str(a):
+                    urls.append(a)
+    else:
+        urls=all
+    return urls
+
+allanimalurls=listurl(url,animals)
+
+imlist=[]
+for allanimalurl in allanimalurls:
+    imlist.extend(listimgurl(allanimalurl))
+
+write(imlist,fn="filelist.lst")
diff --git a/custom_types.py b/custom_types.py
new file mode 100644
index 0000000..d030b23
--- /dev/null
+++ b/custom_types.py
@@ -0,0 +1,4 @@
+from collections import namedtuple
+
+
+Image = namedtuple("Image", ["fname", "image"])
diff --git a/exampleinterface.py b/exampleinterface.py
deleted file mode 100644
index 28e9fbd..0000000
--- a/exampleinterface.py
+++ /dev/null
@@ -1,24 +0,0 @@
-#interface to dlc
-
-import deeplabcut, os
-import pandas as pd
-from pathlib import Path
-
-cfgpath='/home/alex/Hacking/DeepLabCut-WebApp/openfield-Pranav-2018-10-30/config.yaml'
-deeplabcut.create_project.demo_data.load_demo_data(cfgpath,createtrainingset=False)
-
-
-cfg = deeplabcut.auxiliaryfunctions.read_config(cfgpath)
-
-
-videos = cfg['video_sets'].keys()
-#video_names = [Path(i).stem for i in videos]
-alldatafolders = [fn for fn in os.listdir(Path(cfgpath).parent / 'labeled-data') if '_labeled' not in fn]
-
-print("Bodyparts to label...", cfg['bodyparts'])
-print("Labeled-data contains:", len(alldatafolders))
-
-datafolder=alldatafolders[0]
-#loading data
-dataFrame = pd.read_hdf(os.path.join(cfg['project_path'],'labeled-data',datafolder,'CollectedData_'+cfg['scorer']+'.h5'),'df_with_missing')
-print(dataFrame.head())
diff --git a/model.py b/model.py
new file mode 100644
index 0000000..8de243e
--- /dev/null
+++ b/model.py
@@ -0,0 +1,74 @@
+import custom_types
+import pandas as pd
+import random
+import time
+from skimage import io
+
+
+
+class User:
+    """ Each user has a separate view on the labels and can label each image once """
+
+    def __init__(self, name):
+        self.name = name
+
+    def add_annotation(self):
+        pass
+
+    def to_csv(self):
+        return None
+
+
+class Dataset:
+    """ Handles async data fetching """
+
+    def __init__(self, fnames):
+        self.fnames = fnames
+        random.shuffle(self.fnames)
+        self.data = io.imread_collection(self.fnames)
+
+    def __getitem__(self, index):
+        if index >= len(self):
+            raise StopIteration
+
+        # TODO revert this at some point
+        img = self.data[index][::5, ::5]
+        return custom_types.Image(fname=self.fnames[index], image=img)
+
+    def __len__(self):
+        return len(self.fnames)
+
+
+class AppModel:
+
+    def __init__(self, config):
+        
+        self.config = config
+        self.users = []
+        self.dataset = Dataset(self.config.fnames)
+        self.annotations = []
+        self.active_image = None
+
+    def add_user(self, name):
+        print(f"| Added user: {name}")
+        self.users.append(User(name))
+
+    def add_annotation(self, name, username, xy):
+        self.annotations.append(dict(
+            name=self.active_image.fname,
+            label=name,
+            x=xy[0],
+            y=xy[1],
+            username=username,
+            timestamp=time.time())
+        )
+
+    def fetch_image(self, index):
+        self.active_image = self.dataset[index]
+        return self.active_image
+
+    def to_csv(self):
+        return pd.DataFrame(self.annotations).to_csv()
+
+    def to_html(self):
+        return pd.DataFrame(self.annotations).to_html()
\ No newline at end of file
diff --git a/openfield-Pranav-2018-10-30/config.yaml b/openfield-Pranav-2018-10-30/config.yaml
deleted file mode 100644
index 64c2ce1..0000000
--- a/openfield-Pranav-2018-10-30/config.yaml
+++ /dev/null
@@ -1,49 +0,0 @@
-# Project definitions (do not edit)
-Task: openfield
-scorer: Pranav
-date: Oct30
-
-# Project path (change when moving around)
-project_path: WILL BE AUTOMATICALLY UPDATED BY DEMO CODE
-
-# Annotation data set configuration (and individual video cropping parameters)
-video_sets:
-  WILL BE AUTOMATICALLY UPDATED BY DEMO CODE:
-    crop: 0, 640, 0, 480
-bodyparts:
-- snout
-- leftear
-- rightear
-- tailbase
-
-start: 0
-stop: 1
-numframes2pick: 20
-
-# Plotting configuration
-pcutoff: 0.4
-dotsize: 8
-alphavalue: 0.7
-colormap: jet
-
-# Training,Evaluation and Analysis configuration
-TrainingFraction:
-- 0.95
-iteration: 0
-default_net_type: resnet_50
-snapshotindex: -1
-batch_size: 4
-
-# Cropping Parameters (for analysis and outlier frame detection)
-cropping: false
-#if cropping is true for analysis, then set the values here:
-x1: 0
-x2: 640
-y1: 277
-y2: 624
-
-# Refinement configuration (parameters from annotation dataset configuration also relevant in this stage)
-corner2move2:
-- 50
-- 50
-move2corner: true
diff --git a/openfield-Pranav-2018-10-30/labeled-data/m4s1/.~lock.CollectedData_Pranav.csv# b/openfield-Pranav-2018-10-30/labeled-data/m4s1/.~lock.CollectedData_Pranav.csv#
deleted file mode 100644
index 88d97b6..0000000
--- a/openfield-Pranav-2018-10-30/labeled-data/m4s1/.~lock.CollectedData_Pranav.csv#
+++ /dev/null
@@ -1 +0,0 @@
-,alex,T440s,26.02.2020 19:00,file:///home/alex/.config/libreoffice/4;
\ No newline at end of file
diff --git a/openfield-Pranav-2018-10-30/labeled-data/m4s1/CollectedData_Pranav.csv b/openfield-Pranav-2018-10-30/labeled-data/m4s1/CollectedData_Pranav.csv
deleted file mode 100644
index d9d4f56..0000000
--- a/openfield-Pranav-2018-10-30/labeled-data/m4s1/CollectedData_Pranav.csv
+++ /dev/null
@@ -1,119 +0,0 @@
-scorer,Pranav,Pranav,Pranav,Pranav,Pranav,Pranav,Pranav,Pranav
-bodyparts,snout,snout,leftear,leftear,rightear,rightear,tailbase,tailbase
-coords,x,y,x,y,x,y,x,y
-labeled-data/m4s1/img0000.png,21.521,265.428,33.819,265.941,19.984,250.05599999999998,87.11,152.69799999999998
-labeled-data/m4s1/img0001.png,10.248,288.487,19.984,297.198,12.298,281.313,95.821,221.361
-labeled-data/m4s1/img0002.png,24.596,354.075,38.431,354.075,23.058000000000003,337.166,99.40799999999999,256.205
-labeled-data/m4s1/img0003.png,73.78699999999999,374.57199999999995,78.911,366.37300000000005,57.39,361.76099999999997,106.581,270.04
-labeled-data/m4s1/img0004.png,38.431,333.066,50.729,341.777,39.968,323.33099999999996,131.17700000000002,273.627
-labeled-data/m4s1/img0005.png,23.570999999999998,327.43,30.745,339.215,28.183000000000003,321.793,131.17700000000002,318.719
-labeled-data/m4s1/img0006.png,42.53,332.042,48.167,337.67800000000005,46.629,323.33099999999996,147.57399999999998,316.157
-labeled-data/m4s1/img0007.png,63.026,333.066,70.71300000000001,341.265,67.638,324.868,173.707,316.66900000000004
-labeled-data/m4s1/img0008.png,95.821,334.60400000000004,104.01899999999999,343.827,100.432,326.405,209.063,317.694
-labeled-data/m4s1/img0009.png,113.755,318.207,120.416,332.042,122.978,313.082,235.709,320.256
-labeled-data/m4s1/img0010.png,54.828,339.728,64.051,348.439,59.44,329.48,177.294,326.405
-labeled-data/m4s1/img0011.png,32.282,383.795,40.993,388.407,30.745,370.472,134.764,331.017
-labeled-data/m4s1/img0012.png,28.183000000000003,440.16,39.968,441.69699999999995,27.67,426.837,109.14299999999999,358.175
-labeled-data/m4s1/img0013.png,92.74600000000001,460.657,93.771,449.384,73.78699999999999,445.284,125.54,358.68699999999995
-labeled-data/m4s1/img0014.png,24.083000000000002,423.251,35.356,431.449,28.695,412.49,130.665,390.45599999999996
-labeled-data/m4s1/img0015.png,24.083000000000002,395.06800000000004,32.282,406.341,29.206999999999997,386.35699999999997,136.30100000000002,405.316
-labeled-data/m4s1/img0016.png,28.183000000000003,430.42400000000004,37.918,439.648,30.232,422.226,137.838,418.639
-labeled-data/m4s1/img0017.png,49.191,430.93699999999995,57.39,440.673,50.216,425.81300000000005,156.797,413.515
-labeled-data/m4s1/img0018.png,66.101,433.499,74.29899999999999,444.772,68.15100000000001,425.81300000000005,176.78099999999998,415.05199999999996
-labeled-data/m4s1/img0019.png,86.085,435.036,95.821,444.772,89.15899999999999,426.837,200.352,417.102
-labeled-data/m4s1/img0020.png,103.507,446.82099999999997,115.292,451.94599999999997,106.581,436.061,218.287,417.61400000000003
-labeled-data/m4s1/img0021.png,53.803000000000004,437.086,64.564,448.35900000000004,58.927,428.375,175.24400000000003,425.3
-labeled-data/m4s1/img0022.png,26.645,435.548,36.381,448.871,32.794000000000004,428.375,147.062,441.69699999999995
-labeled-data/m4s1/img0023.png,29.206999999999997,407.87800000000004,34.330999999999996,424.275,39.968,405.829,146.037,448.35900000000004
-labeled-data/m4s1/img0024.png,22.546,419.151,29.206999999999997,427.35,26.645,410.44,136.813,437.086
-labeled-data/m4s1/img0025.png,18.959,425.3,26.645,437.086,23.570999999999998,416.077,135.276,431.962
-labeled-data/m4s1/img0026.png,25.108,443.235,31.769000000000002,448.871,28.695,430.93699999999995,135.789,438.62300000000005
-labeled-data/m4s1/img0027.png,41.505,413.515,45.092,432.474,49.70399999999999,415.05199999999996,159.359,442.722
-labeled-data/m4s1/img0028.png,17.422,399.167,26.645,415.05199999999996,29.72,398.655,133.739,437.086
-labeled-data/m4s1/img0029.png,30.745,428.88699999999994,37.406,438.62300000000005,34.844,419.664,142.96200000000002,430.42400000000004
-labeled-data/m4s1/img0030.png,55.853,434.524,61.489,444.259,57.39,428.88699999999994,166.533,430.42400000000004
-labeled-data/m4s1/img0031.png,81.986,437.598,89.15899999999999,445.284,84.035,429.912,195.22799999999998,430.93699999999995
-labeled-data/m4s1/img0032.png,98.895,448.35900000000004,109.656,452.97,100.945,437.598,217.262,429.912
-labeled-data/m4s1/img0033.png,43.555,442.21,51.753,449.384,47.653999999999996,432.474,162.434,442.722
-labeled-data/m4s1/img0034.png,25.62,437.086,33.306999999999995,446.309,30.745,428.88699999999994,144.5,438.62300000000005
-labeled-data/m4s1/img0035.png,40.993,419.664,38.943000000000005,445.79699999999997,41.505,425.81300000000005,149.624,446.309
-labeled-data/m4s1/img0036.png,57.902,421.20099999999996,57.902,446.309,57.39,428.375,172.17,447.846
-labeled-data/m4s1/img0037.png,78.911,420.176,79.936,446.82099999999997,79.936,428.375,196.765,447.334
-labeled-data/m4s1/img0038.png,105.044,424.275,109.656,448.871,115.805,427.35,229.047,449.89599999999996
-labeled-data/m4s1/img0039.png,77.88600000000001,428.88699999999994,87.62200000000001,445.284,87.62200000000001,427.86199999999997,209.576,450.408
-labeled-data/m4s1/img0040.png,50.216,381.233,50.216,405.316,64.051,384.30699999999996,159.872,448.35900000000004
-labeled-data/m4s1/img0041.png,71.737,307.95799999999997,51.753,333.066,71.225,329.48,119.904,426.325
-labeled-data/m4s1/img0042.png,73.78699999999999,203.42700000000002,56.878,223.923,74.29899999999999,220.33599999999998,92.74600000000001,341.265
-labeled-data/m4s1/img0043.png,96.333,104.01899999999999,74.29899999999999,118.367,95.30799999999999,116.829,100.432,234.171
-labeled-data/m4s1/img0044.png,71.737,89.15899999999999,70.71300000000001,102.48200000000001,83.523,88.135,111.705,198.815
-labeled-data/m4s1/img0045.png,38.431,72.25,41.505,81.986,48.167,66.101,129.127,140.4
-labeled-data/m4s1/img0046.png,17.422,66.613,22.034000000000002,80.44800000000001,28.183000000000003,60.977,120.929,106.581
-labeled-data/m4s1/img0047.png,24.083000000000002,64.051,29.206999999999997,78.911,34.844,59.44,128.102,97.35799999999999
-labeled-data/m4s1/img0048.png,19.984,73.78699999999999,21.521,85.572,31.256999999999998,65.07600000000001,125.02799999999999,89.67200000000001
-labeled-data/m4s1/img0049.png,23.058000000000003,78.399,28.183000000000003,89.67200000000001,34.330999999999996,71.225,134.251,90.697
-labeled-data/m4s1/img0050.png,24.596,92.234,31.256999999999998,102.994,32.794000000000004,79.936,146.549,83.01
-labeled-data/m4s1/img0051.png,19.472,79.42399999999999,27.158,91.721,29.206999999999997,72.25,132.714,82.49799999999999
-labeled-data/m4s1/img0052.png,18.959,73.275,26.133000000000003,84.035,33.306999999999995,63.538999999999994,134.764,84.035
-labeled-data/m4s1/img0053.png,27.158,73.78699999999999,29.206999999999997,85.06,34.844,69.175,143.475,88.135
-labeled-data/m4s1/img0054.png,57.902,73.78699999999999,59.952,83.523,65.07600000000001,67.638,177.294,84.54799999999999
-labeled-data/m4s1/img0055.png,84.54799999999999,70.71300000000001,88.135,81.473,93.771,63.026,207.014,84.54799999999999
-labeled-data/m4s1/img0056.png,92.234,73.275,97.87,80.44800000000001,100.945,63.538999999999994,210.6,85.06
-labeled-data/m4s1/img0057.png,58.415,72.762,63.026,83.01,68.15100000000001,63.026,174.732,76.861
-labeled-data/m4s1/img0058.png,81.473,116.829,90.697,112.21799999999999,77.88600000000001,93.771,182.93,83.01
-labeled-data/m4s1/img0059.png,40.993,140.91299999999998,52.778,143.475,45.092,126.565,153.72299999999998,83.523
-labeled-data/m4s1/img0060.png,32.282,207.014,43.555,202.91400000000002,27.158,187.542,109.14299999999999,112.73
-labeled-data/m4s1/img0061.png,30.745,293.611,41.505,286.437,24.083000000000002,274.652,75.837,168.583
-labeled-data/m4s1/img0062.png,51.753,354.075,65.58800000000001,349.464,45.092,336.653,87.11,228.02200000000002
-labeled-data/m4s1/img0063.png,43.555,387.38199999999995,54.828,386.869,38.431,376.621,94.796,281.825
-labeled-data/m4s1/img0064.png,117.34200000000001,407.87800000000004,111.705,398.655,91.721,405.829,100.945,294.123
-labeled-data/m4s1/img0065.png,87.11,429.912,97.35799999999999,427.86199999999997,81.986,418.639,125.02799999999999,306.934
-labeled-data/m4s1/img0066.png,29.206999999999997,422.226,39.455999999999996,426.837,31.769000000000002,411.465,130.665,373.54699999999997
-labeled-data/m4s1/img0067.png,50.216,318.207,37.918,344.339,55.853,330.504,135.276,408.903
-labeled-data/m4s1/img0068.png,59.44,217.262,47.141999999999996,238.271,62.001999999999995,228.535,92.74600000000001,348.439
-labeled-data/m4s1/img0069.png,52.778,107.094,39.455999999999996,126.565,54.315,116.829,78.399,234.171
-labeled-data/m4s1/img0070.png,76.34899999999999,71.225,62.001999999999995,83.523,80.961,76.34899999999999,100.945,180.368
-labeled-data/m4s1/img0071.png,91.721,65.58800000000001,82.49799999999999,75.837,99.40799999999999,70.71300000000001,117.854,176.269
-labeled-data/m4s1/img0072.png,108.631,64.564,100.432,75.837,119.39200000000001,69.688,136.30100000000002,175.757
-labeled-data/m4s1/img0073.png,132.714,61.489,121.954,72.25,143.987,66.613,161.409,175.24400000000003
-labeled-data/m4s1/img0074.png,163.459,62.513999999999996,150.136,71.225,171.145,67.638,186.517,174.732
-labeled-data/m4s1/img0075.png,152.69799999999998,62.513999999999996,149.111,76.861,167.046,64.564,214.7,164.484
-labeled-data/m4s1/img0076.png,113.243,60.977,116.829,76.34899999999999,128.615,56.365,215.725,121.441
-labeled-data/m4s1/img0077.png,54.828,74.812,60.977,83.01,67.126,66.101,171.145,91.721
-labeled-data/m4s1/img0078.png,23.058000000000003,94.796,29.72,102.48200000000001,30.232,84.035,136.813,85.572
-labeled-data/m4s1/img0079.png,18.447,80.961,23.570999999999998,91.721,27.158,71.225,126.053,85.06
-labeled-data/m4s1/img0080.png,26.133000000000003,143.475,36.894,139.376,26.645,120.416,125.02799999999999,80.961
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diff --git a/openfield-Pranav-2018-10-30/videos/m3v1mp4.mp4 b/openfield-Pranav-2018-10-30/videos/m3v1mp4.mp4
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diff --git a/prepare_data.sh b/prepare_data.sh
new file mode 100644
index 0000000..41966b9
--- /dev/null
+++ b/prepare_data.sh
@@ -0,0 +1,5 @@
+#!/bin/bash
+
+mkdir -p data
+parallel wget :::: config/filelist.lst
+mv *.png data
diff --git a/run.sh b/run.sh
new file mode 100755
index 0000000..bc6d480
--- /dev/null
+++ b/run.sh
@@ -0,0 +1,6 @@
+#!/bin/bash
+
+sudo docker build -t dlcapp .
+sudo docker run -p 8050:8050 \
+    --mount type=bind,source=$(pwd)/data,destination=/app/data,readonly \
+    --user nobody -it dlcapp
\ No newline at end of file
diff --git a/scripts/query_files.sh b/scripts/query_files.sh
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index 0000000..7763afc
--- /dev/null
+++ b/scripts/query_files.sh
@@ -0,0 +1,7 @@
+#!/bin/bash
+# Generates a file list of possible images
+
+wget --spider -r --no-parent http://deeplabcut.rowland.harvard.edu/datasets/ \
+|& grep http \
+| grep png \
+| awk '{print $3}'
diff --git a/static/img/example_labels.png b/static/img/example_labels.png
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diff --git a/update_app.sh b/update_app.sh
new file mode 100755
index 0000000..da06adf
--- /dev/null
+++ b/update_app.sh
@@ -0,0 +1,10 @@
+#!/bin/bash
+
+# check github and update app if needed
+# run with watch
+
+update=$(git fetch --dry-run |& grep stes/webinar | wc -l)
+if [[ $update -ne 0 ]]; then
+    git pull origin stes/webinar
+fi
+
diff --git a/utils.py b/utils.py
new file mode 100644
index 0000000..35dfe80
--- /dev/null
+++ b/utils.py
@@ -0,0 +1,47 @@
+import matplotlib.colors as mcolors
+import numpy as np
+
+
+def draw_circle(center, radius, n_points=50):
+    pts = np.linspace(0, 2 * np.pi, n_points)
+    x = center[0] + radius * np.cos(pts)
+    y = center[1] + radius * np.sin(pts)
+    path = 'M ' + str(x[0]) + ',' + str(y[1])
+    for k in range(1, x.shape[0]):
+        path += ' L ' + str(x[k]) + ',' + str(y[k])
+    path += ' Z'
+    return path
+
+
+def compute_circle_center(path):
+    """
+    See Eqn 1 & 2 pp.12-13 in REGRESSIONS CONIQUES, QUADRIQUES
+    Régressions linéaires et apparentées, circulaire, sphérique
+    Jacquelin J., 2009.
+    """
+    coords = [list(map(float, coords.split(','))) for coords in path.split(' ')[1::2]]
+    x, y = np.array(coords).T
+    n = len(x)
+    sum_x = np.sum(x)
+    sum_y = np.sum(y)
+    sum_x2 = np.sum(x * x)
+    sum_y2 = np.sum(y * y)
+    delta11 = n * np.dot(x, y) - sum_x * sum_y
+    delta20 = n * sum_x2 - sum_x ** 2
+    delta02 = n * sum_y2 - sum_y ** 2
+    delta30 = n * np.sum(x ** 3) - sum_x2 * sum_x
+    delta03 = n * np.sum(y ** 3) - sum_y * sum_y2
+    delta21 = n * np.sum(x * x * y) - sum_x2 * sum_y
+    delta12 = n * np.sum(x * y * y) - sum_x * sum_y2
+
+    # Eqn 2, p.13
+    num_a = (delta30 + delta12) * delta02 - (delta03 + delta21) * delta11
+    num_b = (delta03 + delta21) * delta20 - (delta30 + delta12) * delta11
+    den = 2 * (delta20 * delta02 - delta11 * delta11)
+    a = num_a / den
+    b = num_b / den
+    return a, b
+
+
+def get_plotly_color(cmap, n):
+    return mcolors.to_hex(cmap(n))
diff --git a/view.py b/view.py
new file mode 100644
index 0000000..0d6673f
--- /dev/null
+++ b/view.py
@@ -0,0 +1,129 @@
+import dash
+import dash_core_components as dcc
+import dash_html_components as html
+import plotly.express as px
+import random
+import uuid
+
+
+class AppView:
+
+    def __init__(self, name, db, config, server):
+        external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
+
+        self.app = dash.Dash(name, external_stylesheets=external_stylesheets, server=server)
+        self.db = db
+        self.current_idx = 0
+        self.appconfig = config
+        self.pick_keypoint_subset()
+        self.make_figure_image(self.current_idx)
+        self.app.layout = self.make_layout()
+
+    @property
+    def options(self):
+        return [self.appconfig.options[i] for i in self.subset]
+
+    @property
+    def fig(self):
+        return self._fig
+
+    def make_figure_image(self, i):
+        data = self.db.fetch_image(i % len(self.db.dataset))
+        fig = px.imshow(data.image)
+        fig.layout.xaxis.showticklabels = False
+        fig.layout.yaxis.showticklabels = False
+        fig.update_traces(hoverinfo='none', hovertemplate='')
+        fig.update_layout(
+            title={
+                'text': data.fname,
+                'y': 0.9,
+                'x': 0.5,
+                'xanchor': 'center',
+                'yanchor': 'top'}
+        )
+        self._fig = fig
+        return self._fig
+
+    @property
+    def style(self):
+        return {
+            'pre': {
+                'border': 'thin lightgrey solid',
+                'overflowX': 'scroll'
+            }
+        }
+
+    def make_layout(self):
+        return html.Div([
+            html.Div([
+                dcc.Graph(
+                    id='canvas',
+                    config={
+                        'editable': True,
+                        'doubleClick': False,
+                        'showTips': False,
+                        'showLink': False,
+                    },
+                    figure=self.fig)
+            ],
+                className="six columns"
+            ),
+            html.Div([
+                html.Div([
+                    html.H3("DeepLabCut Labeling App"),
+                    html.Div([
+                        dcc.RadioItems(id='radio',
+                                       options=[{'label': opt, 'value': opt} for opt in
+                                                self.options],
+                                       value=self.options[0]
+                                       ),
+                    ], style={"column-count": "4"}),
+                ]),
+                html.Div([
+                    dcc.Input(
+                        id="input_name",
+                        type='text',
+                        placeholder="Please add username"
+                    ),
+                    html.Button('Previous', id='previous'),
+                    html.Button('Next', id='next'),
+                    html.Button('Clear', id='clear'),
+                    html.Button('Save', id='save'),
+                    dcc.Store(id='store', data=0),
+                ]),
+                html.Div([
+                    html.Label('Keypoint label size'),
+                    dcc.Slider(id='slider',
+                               min=1,
+                               max=24,
+                               step=1,
+                               value=8)
+                ], style={'width': '80%',
+                          'display': 'inline-block'})
+            ],
+                className="six columns"
+            ),
+            html.Div([
+                dcc.Markdown("""
+                        **Instructions**\n
+                        Left click on the image to add a keypoint. Please skip/do not label occluded points. If you make a mistake, click clear to start again.
+
+                        ![](/static/img/example_labels.png)
+                    """),
+                html.Pre(id='click-data', style=self.style['pre'])
+            ],
+                className='six columns',
+                style={"overflow-x": "hidden"}
+            ),
+            html.Div(id='placeholder', style={'display': 'none'}),
+            html.Div(id='shapes', style={'display': 'none'})
+        ]
+        )
+
+    def pick_keypoint_subset(self):
+        self.subset = [0, 1, 2, 8, 9]
+        #random.sample(range(len(self.appconfig.options)), self.appconfig.n2show)
+
+    def refresh_radio_buttons(self):
+        self.pick_keypoint_subset()
+        return [{'label': opt, 'value': opt} for opt in self.options]