Update app.py

app.py

@@ -45,16 +45,40 @@ def planogram_compliance_check(planogram_image, master_planogram_image, annotati
 
     return compliance_score, annotated_image
 
-# Define the function to run planogram compliance check
 def run_compliance_check(planogram_img, master_planogram_img, sorted_xml_df, result_list):
-    # Perform further processing and calculation of compliance score
-    compliance_score = 0.0  # Placeholder for actual score calculation
-    annotated_image = None  # Placeholder for annotated image
+    # Placeholder for actual score calculation
+    compliance_score = 0.0
+
+    # Placeholder for annotated image
+    annotated_image = planogram_img.copy()
+
+    if sorted_xml_df is not None:
+        annotate_df = sorted_xml_df[["xmin", "ymin", "xmax", "ymax", "line_number", "cls"]].astype(int)
+    else:
+        annotate_df = None
+
+    mask = master_table != non_null_product
+    m_detected_table = np.ma.masked_array(master_table, mask=mask)
+    m_annotated_table = np.ma.masked_array(detected_table, mask=mask)
 
-    # Your compliance score calculation and image annotation logic here
+    # wrong_indexes = np.ravel_multi_index(master_table*mask != detected_table*mask, master_table.shape)
+    wrong_indexes = np.where(master_table != detected_table)
+    correct_indexes = np.where(master_table == detected_table)
+
+    # Annotate planogram compliance on the image
+    annotated_image = annotate_planogram_compliance(
+        annotated_image, annotate_df, correct_indexes, wrong_indexes, target_names
+    )
+
+    # Calculate compliance score
+    correct_matches = (np.ma.masked_equal(master_table, non_null_product) == detected_table).sum()
+    total_products = (master_table != non_null_product).sum()
+    if total_products != 0:
+        compliance_score = correct_matches / total_products
 
     return compliance_score, annotated_image
 
+
 # Gradio interface
 planogram_check_interface = gr.Interface(
     fn=planogram_compliance_check,