busino/bokeh_frog.py

## bokeh_frog.py
from io import BytesIO
import base64

import numpy
from PIL import Image as PilImage

from bokeh.plotting import figure
from bokeh.models.tools import HoverTool, WheelZoomTool, PanTool
from bokeh import events
from bokeh.layouts import widgetbox, row
from bokeh.models.widgets.buttons import Button
from bokeh.embed import components
from bokeh.io import output_file, save, show
from bokeh.core.properties import Instance, List
from bokeh.models.renderers import Renderer
from bokeh.models.tools import Tap
from bokeh.models.callbacks import CustomJS
from bokeh.models.markers import Cross, Square, SquareCross, CircleCross, Circle
from bokeh.models.sources import ColumnDataSource
from bokeh.models.widgets import Div


IMG_DATA = 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'


JS_CODE = """
import * as p from "core/properties"
import {TapTool, TapToolView} from "models/tools/gestures/tap_tool"
import {SelectTool, SelectToolView} from "models/tools/gestures/select_tool"
import {logger} from "core/logging"

export class TapDeleteToolView extends TapToolView

  _keyup: (e) ->
    if e.keyCode == 27
      for r in @computed_renderers
        ds = r.data_source
        sm = ds.selection_manager
        sm.clear()
    else if e.keyCode == 46
      if @model.source.selected['1d'].indices.length
        source = @model.source
        data = source.data
        index = source.selected['1d'].indices[0]
        data.x.splice(index, 1)
        data.y.splice(index, 1)
        data.db_id.splice(index, 1)
        for r in @computed_renderers
          r.data_source.selection_manager.clear()
        source.change.emit()

export class TapDeleteTool extends TapTool

  default_view: TapDeleteToolView
  tool_name: "TapDeleteTool"
  event_type: "tap"
  icon: "bk-tool-icon-lasso-select"

  @define {
    source: [ p.Instance ]
  }
"""


class TapDeleteTool(Tap):

    __implementation__ = JS_CODE

    source = Instance(ColumnDataSource)

    renderers = List(Instance(Renderer))


def image_label_plot(img_data, components=True):
    # For notebook
    #from bokeh.io import output_notebook
    #output_notebook()

    #
    # Image
    #
    #o_img = PilImage.open('1143_Alob_2015_05_18_001.jpg').convert('RGBA')
    o_img = PilImage.open(BytesIO(base64.b64decode(img_data))).convert('RGBA')
    xdim, ydim = o_img.size
    img = numpy.empty((ydim, xdim), dtype=numpy.uint32)
    view = img.view(dtype=numpy.uint8).reshape((ydim, xdim, 4))
    # Copy the RGBA image into view, flipping it so it comes right-side up
    # with a lower-left origin
    view[:,:,:] = numpy.flipud(numpy.asarray(o_img))

    #
    # Display the 32-bit RGBA image
    #
    plot = figure(plot_width=600, plot_height=500,
                  x_range=[0,xdim], y_range=[0,ydim],
                  tools='', logo=None,
                  title='Bokeh Frog')

    plot.image_rgba(image=[img], x=0, y=0, dw=xdim, dh=ydim)

    #
    # Data Source holding the Point Coordinates
    #
    source = ColumnDataSource(data=dict(x=[240, 242, 50], y=[97, 158, 120], db_id=[12, 13, 99]))
    selection_source = ColumnDataSource(data=dict(db_id=[]))

    #
    # Double Click for Point Creation
    #
    dtap_cb = CustomJS(args=dict(source=source),
                        code="""
    console.log('DoubleTap');
    var data = source.data;
    data['x'].push(cb_obj.x);
    data['y'].push(cb_obj.y);
    data['db_id'].push(Math.max.apply(null, data['db_id'])+1);
    source.change.emit();
    """)
    plot.js_on_event(events.DoubleTap, dtap_cb)

    #
    # Show the position of the Point when moving selected point
    #
    move_cb = CustomJS(args=dict(source=source, selection_source=selection_source),
                        code="""
    if (selection_source.data['db_id'].length & source.selected['1d'].indices.length) {
      console.log('Mouse Move');
      var index = source.selected['1d'].indices[0];
      var data = source.data;
      data['x'][index] = cb_obj.x;
      data['y'][index] = cb_obj.y;
      source.change.emit();
    }
    """)
    plot.js_on_event(events.MouseMove, move_cb)

    #
    # Select and Release Point on click
    # is a little bit hacky
    #
    sg_cb = CustomJS(args=dict(source=source, selection_source=selection_source),
                        code="""
    console.log('SelectionGeometry');

    if (source.selected['1d'].indices.length) {
        // when releasing the selection the mousemove is stopped and the points stays on current position
        if (selection_source.data['db_id'].length) {
            console.log('Clear selection');
            selection_source.data['db_id'].length = 0;
            source.selection_manager.clear();
            source.change.emit();
        }
        // select the point
        else {
            console.log('Add new selection');
            selection_source.data['db_id'].length=0;
            selection_source.data['db_id'].push(source.selected['1d'].indices[0]);
            selection_source.change.emit();
        }
    }
    """)
    plot.js_on_event(events.SelectionGeometry, sg_cb)

    #
    # Glyph
    #
    GLYPH_CLASS = CircleCross#Square# Circle, Cross
    FILL_ALPHA = 0.1
    LINE_WIDTH = 1.2
    LINE_COLOR = 'yellow'
    glyph = GLYPH_CLASS(size=24, x='x', y='y',
                        line_width=LINE_WIDTH, line_color=LINE_COLOR,
                        fill_alpha=FILL_ALPHA)
    cr = plot.add_glyph(source, glyph)

    #
    # Define Selection and Hover of Glyph
    #
    cr.selection_glyph = GLYPH_CLASS(line_color='firebrick', line_width=LINE_WIDTH,
                                     fill_alpha=FILL_ALPHA)
    cr.nonselection_glyph = GLYPH_CLASS(line_width=LINE_WIDTH, line_color=LINE_COLOR,
                                        fill_alpha=FILL_ALPHA)
    cr.hover_glyph = GLYPH_CLASS(line_color='firebrick', line_width=LINE_WIDTH,
                                 fill_alpha=FILL_ALPHA)

    #
    # Plot Tools
    #

    # Create A New TapDeleteTool
    plot.add_tools(TapDeleteTool(renderers=[cr], source=source))
    #plot.add_tools(TapTool(behavior='select', renderers=[cr]))
    # Hover to inform the user that the glyph can be selected
    plot.add_tools(HoverTool(tooltips=None, renderers=[cr]))
    # Scroll
    wz = WheelZoomTool()
    plot.add_tools(wz)
    plot.toolbar.active_scroll = wz
    plot.add_tools(PanTool())

    #
    # Doc Div
    #
    p = Div(text='''
    <h2>HowTo Label the Frog</h2>
    <font style="font-size: 1.2em">
    <dl>
      <dt>New Point:</dt><dd>Double-Click</dd>
      <dt>Edit Point:</dt><dd>Click (Select) > Drag > Click (Place)</dd>
      <dt>Delete Point:</dt><dd>Click (Select) > Press Delete-Key</dd>
    </dl>
    <p>Please label all my warts.</p>
    <p>And don't call me frog, I'm a <b>toad</b>!</p>
    </font>
    ''')

    #
    # Layout
    #
    layout = row(widgetbox(p, width=420), plot)

    output_file('bokeh_frog.html')
    save(layout)
    #show(layout)
    #for notebook output
    #r = show(layout, notebook_handle=True)

    if not components:
        return layout
    return components(layout)

if __name__ == '__main__':


    plot = image_label_plot(IMG_DATA, components=False)

    output_file('bokeh_frog.html')
    save(plot)