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import pickle | |
import pandas as pd | |
from bokeh.plotting import figure | |
from bokeh.models import ColumnDataSource, HoverTool, Div | |
from bokeh.layouts import column | |
import logging | |
# Configure logging | |
logging.basicConfig(level=logging.INFO) | |
logger = logging.getLogger(__name__) | |
def create_plot(): | |
# Load preprocessed data | |
logger.info("Loading preprocessed data...") | |
with open('processed_data.pkl', 'rb') as f: | |
df = pickle.load(f) | |
with open('contour_data.pkl', 'rb') as f: | |
contour_data = pickle.load(f) | |
logger.info("Data loaded successfully.") | |
logger.info("Creating Bokeh plot...") | |
p = figure(width=1280, height=800, title="UMAP projection of embeddings") | |
# Load contour data | |
contour_source = ColumnDataSource(data=dict(xs=contour_data['xs'], | |
ys=contour_data['ys'], | |
color=contour_data['color'])) | |
contour_renderer = p.patches(xs="xs", ys="ys", source=contour_source, fill_alpha=0.3, line_color=None, fill_color="color") | |
# Scatter plot | |
source = ColumnDataSource(df) | |
scatter_renderer = p.scatter('x', 'y', size=3, source=source, fill_alpha=0.2, line_alpha=0.1) | |
# Configure hover tool to display images | |
hover = HoverTool(renderers=[scatter_renderer]) | |
hover.tooltips = """ | |
<div> | |
<div> | |
<strong>Image ID:</strong> @id | |
</div> | |
<div> | |
<strong>Cap_ref:</strong> @caption | |
</div> | |
<div> | |
<strong>URL:</strong> @url | |
</div> | |
<div> | |
<img | |
src="data:image/jpeg;base64,@image_b64" height="200" alt="Image" | |
style="float: left; margin: 0px 15px 15px 0px;" | |
border="2" | |
></img> | |
</div> | |
</div> | |
""" | |
p.add_tools(hover) | |
return p |