Update app.py

app.py

@@ -6,28 +6,36 @@ from PIL import Image, ImageDraw, ImageFont
 text_pipe = pipeline("text-classification", model="karalif/myTestModel", return_all_scores=True)
 
 def draw_text_with_highlight(text):
+    # Assuming a comprehensive font file is in the same directory as the script
+    font_path = "path/to/your/font.ttf"  # Update this to the path of your font file
+    font_size = 24  # Adjust font size as needed
+
     # Create an image with white background
-    image = Image.new("RGB", (800, 100), "white")
+    image = Image.new("RGB", (1000, 60), "white")
     draw = ImageDraw.Draw(image)
-    
-    # Define the font and size
-    try:
-        # Attempt to use a nicer font if available
-        font = ImageFont.truetype("arial.ttf", 24)
-    except IOError:
-        # Fallback to default font
-        font = ImageFont.load_default()
-    
+    font = ImageFont.truetype(font_path, font_size)
+
     # Split the text to find the third word
     words = text.split()
+    
+    # Initialize starting position
+    x, y = 10, 10
     if len(words) >= 3:
-        # Highlight the third word with a different color
-        highlighted_text = " ".join(words[:2]) + " " + words[2] + " " + " ".join(words[3:])
-        draw.text((10, 10), highlighted_text, fill="black", font=font)
+        # Process each word to either draw normally or highlight
+        for i, word in enumerate(words):
+            if i == 2:  # The third word is at index 2
+                # Draw background for highlight
+                width, height = draw.textsize(word, font=font)
+                draw.rectangle((x, y, x + width, y + height), fill='yellow')
+                draw.text((x, y), word, fill="black", font=font)
+            else:
+                draw.text((x, y), word, fill="black", font=font)
+            # Update x to draw next word. Adding a space width.
+            x += draw.textsize(word + " ", font=font)[0]
     else:
         # Draw the text as is if less than three words
         draw.text((10, 10), text, fill="black", font=font)
-    
+
     return image
 
 def predict(text):