bug fixing for recom_cta

app.py

@@ -19,11 +19,29 @@ from bs4 import BeautifulSoup
 import numpy as np
 import tempfile
 from sklearn.preprocessing import normalize
+from colr import color
+import cv2
+from PIL import ImageColor
+
 
 
 CURRENT_THEME = "blue"
 IS_DARK_THEME = True
 
+
+def get_rgb(color_str):
+  return ImageColor.getcolor(color_str, "RGB")
+
+def create_image(width, height, rgb_color=(0, 0, 0)):
+    """Create new image(numpy array) filled with certain color in RGB"""
+    # Create black blank image
+    image = np.zeros((height, width, 3), np.uint8)
+    # Since OpenCV uses BGR, convert the color first
+    color = tuple(reversed(rgb_color))
+    # Fill image with color
+    image[:] = color
+    return image
+
 def add_bg_from_url():
     st.markdown(
         f"""
@@ -651,6 +669,10 @@ def get_predictions(selected_variable, selected_industry, selected_campaign,
                             target_rate = random.uniform(increment - 0.02, increment)
                             increment = target_rate - 0.001
                             recom_cta = row[2]
+                            st.markdown('##### recom_cta is: <span style="color:yellow">{}</span>'.format(recom_cta), unsafe_allow_html=True)
+                            st.markdown('##### target_rate for recom_cta is: <span style="color:yellow">{}</span>'.format(target_rate), unsafe_allow_html=True)
+
+
                             print(f"  {(color('  ', fore='#ffffff', back=recom_cta))}  \x1b[1m{round(target_rate*100, 2)}%\x1b[22m")
                                                                                                                                
                     else:

requirements.txt

@@ -7,4 +7,7 @@ gensim
 scikit-learn
 numpy
 altair<5
-s3fs
+s3fs
+colr
+opencv-python
+pillow