Update app.py

app.py

@@ -645,6 +645,8 @@ def compute_gene_statistics(gene_shap: np.ndarray) -> Dict[str, float]:
 
 def create_simple_genome_diagram(gene_results: List[Dict[str, Any]], genome_length: int) -> Image.Image:
     """Create a simple genome diagram using PIL"""
+    from PIL import Image, ImageDraw, ImageFont
+    
     # Validate inputs
     if not gene_results or genome_length <= 0:
         img = Image.new('RGB', (800, 100), color='white')
@@ -678,8 +680,7 @@ def create_simple_genome_diagram(gene_results: List[Dict[str, Any]], genome_leng
         title_font = ImageFont.load_default()
     
     # Draw title
-    draw.text((margin, margin // 2), "Genome SHAP Analysis", 
-              fill='black', font=title_font or font)
+    draw.text((margin, margin // 2), "Genome SHAP Analysis", fill='black', font=title_font or font)
     
     # Draw genome line
     line_y = height // 2
@@ -688,7 +689,7 @@ def create_simple_genome_diagram(gene_results: List[Dict[str, Any]], genome_leng
     # Calculate scale factor
     scale = float(width - 2 * margin) / float(genome_length)
     
-    # Determine a reasonable step for scale markers (avoid zero step if genome_length<10)
+    # Determine a reasonable step for scale markers (avoid zero step if genome_length < 10)
     num_ticks = 10
     if genome_length < num_ticks:
         step = 1
@@ -729,8 +730,10 @@ def create_simple_genome_diagram(gene_results: List[Dict[str, Any]], genome_leng
         
         # Prepare gene name label
         label = f"{gene['gene_name']}"
-        # Use font.getsize to get text dimensions
-        label_width, label_height = font.getsize(label)
+        
+        # Fallback approach: use getmask(...) to get (width, height)
+        label_mask = font.getmask(label)
+        label_width, label_height = label_mask.size
         
         # Alternate label positions above/below
         if idx % 2 == 0:
@@ -796,6 +799,7 @@ def create_simple_genome_diagram(gene_results: List[Dict[str, Any]], genome_leng
     
     return img
 
+
 def analyze_gene_features(sequence_file: str, 
                         features_file: str, 
                         fasta_text: str = "",