Data Visualization.py

brain_df['mask'].value_counts()
import plotly.graph_objects as go  # using plotly to create interactive plots

fig = go.Figure([go.Bar(x=brain_df['mask'].value_counts().index, 
                        y=brain_df['mask'].value_counts(), 
                        width=[.4, .4]
                       )
                ])
fig.update_traces(marker_color='rgb(158,202,225)', marker_line_color='rgb(8,48,107)',
                  marker_line_width=4, opacity=0.4
                 )
fig.update_layout(title_text="Mask Count Plot",
                  width=700,
                  height=550,
                  yaxis=dict(
                             title_text="Count",
                             tickmode="array",
                             titlefont=dict(size=20)
                           )
                 )
fig.update_yaxes(automargin=True)
fig.show()
for i in range(len(brain_df)):
    if cv2.imread(brain_df.mask_path[i]).max() > 0:
        break

plt.figure(figsize=(8,8))
plt.subplot(1,2,1)
plt.imshow(cv2.imread(brain_df.mask_path[i]));
plt.title('Tumor Location')

plt.subplot(1,2,2)
plt.imshow(cv2.imread(brain_df.image_path[i]));
cv2.imread(brain_df.mask_path[i]).max(), cv2.imread(brain_df.mask_path[i]).min()