Make reading grouped annotations faster.

add_final_score.py

@@ -42,7 +42,7 @@ def process_images(base_dir):
         print(f"Error: Directory '{search_path}' not found.")
         sys.exit(1)
 
-    for img_path in search_path.glob("*/*.jpg"):
+    for img_path in sorted(search_path.glob("*/*.jpg")):
         student_name = img_path.stem # Filename without extension
 
         # 4. Find Score

reading_grouped_annotations.py

@@ -2,6 +2,7 @@ import sys
 import os
 import json
 import collections
+import concurrent.futures
 from pathlib import Path
 from PIL import Image
 
@@ -14,7 +15,9 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
     Modifies data based on actions, pastes label-specific note crops,
     regenerates label images for consistency, saves dirty ones,
     and generates Concat.jpg in the BGnot/Copie{id} directory.
+    Returns a string of accumulated log messages.
     """
+    logs = [f"\nProcessing compilation for: Copie{student_id}"]
     output_dir = os.path.join(root_dir, "BGnot", f"Copie{student_id}")
     os.makedirs(output_dir, exist_ok=True)
 
@@ -44,23 +47,23 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
             if act['type'] == 'score':
                 result['score'] = act['value']
                 dirty_labels.add(label)
-                print(f"  > Updated score for {label} to {act['value']}")
+                logs.append(f"  > Updated score for {label} to {act['value']}")
 
             elif act['type'] == 'del_global':
                 if act['index'] < len(global_fb):
                     global_fb[act['index']]["to_delete"] = True
                     dirty_labels.add(label)
-                    print(f"  > Deleted global feedback in {label}")
+                    logs.append(f"  > Deleted global feedback in {label}")
 
             elif act['type'] in ('del_local', 'del_local_rect'):
                 if act['index'] < len(local_fb):
                     target = local_fb[act['index']]
                     if act['type'] == 'del_local':
                         target["to_delete"] = True
-                        print(f"  > Deleted local feedback in {label}")
+                        logs.append(f"  > Deleted local feedback in {label}")
                     else:
                         target["norectangle"] = True
-                        print(f"  > Deleted rect in {label}")
+                        logs.append(f"  > Deleted rect in {label}")
                     dirty_labels.add(label)
 
     # --- 2. Process Images (Regenerate & Concatenate) ---
@@ -113,7 +116,7 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
         if (label in dirty_labels) or has_notes:
             save_path = os.path.join(output_dir, f"{label}.jpg")
             final_img.save(save_path)
-            print(f"  Saved dirty image: {label}.jpg")
+            logs.append(f"  Saved dirty image: {label}.jpg")
 
         concat_list.append(final_img)
 
@@ -126,11 +129,10 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
         if not perfect_no_comment:
             concat_list_F.append(final_img)
 
-
     # --- 3. Save Final Outputs ---
     with open(score_path, "w") as f:
         json.dump(d_notes, f, indent=4)
-    print(f"  Saved {score_path}")
+    logs.append(f"  Saved {score_path}")
 
     if concat_list:
         max_w = max(i.width for i in concat_list)
@@ -143,7 +145,8 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
             y += img.height
 
         full_img.save(os.path.join(output_dir, "Concat.jpg"))
-        print(f"  Saved regenerated Concat.jpg")
+        logs.append(f"  Saved regenerated Concat.jpg")
+
     if concat_list_F:
         max_w = max(i.width for i in concat_list_F)
         total_h = sum(i.height for i in concat_list_F)
@@ -155,7 +158,9 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
             y += img.height
 
         full_img.save(os.path.join(output_dir, "Concat_F.jpg"))
-        print(f"  Saved regenerated Concat_F.jpg")
+        logs.append(f"  Saved regenerated Concat_F.jpg")
+
+    return "\n".join(logs)
 
 
 if __name__ == "__main__":
@@ -223,20 +228,10 @@ if __name__ == "__main__":
                         'old_header_h': img_info.get("header_height", 0)
                     }
 
-    # --- 2. Dispatch data back to students and regenerate ---
+    def process_student(sid):
-    # affected_students = set(actions_by_student.keys()).union(set(notes_by_student.keys()))
-
-    # if not affected_students:
-    #     print("\nNo changes detected in any grouped annotations.")
-    #     sys.exit(0)
-
-    # for sid in sorted(affected_students, key=natural_key):
-    for sid in sorted(original_data.keys(), key=natural_key):
         if sid not in original_data:
-            continue
+            return ""
-
+        return apply_actions_and_regenerate_grouped(
-        print(f"\nProcessing compilation for: Copie{sid}")
-        apply_actions_and_regenerate_grouped(
             root_dir,
             original_data,
             sid,
@@ -244,3 +239,12 @@ if __name__ == "__main__":
             notes_by_student[sid],
             all_labels
         )
+
+    # --- 2. Process each student concurrently using 4 threads ---
+    sids = sorted(original_data.keys(), key=natural_key)
+    with concurrent.futures.ThreadPoolExecutor(max_workers=4) as executor:
+        futures = {executor.submit(process_student, sid): sid for sid in sids}
+        for future in concurrent.futures.as_completed(futures):
+            output = future.result()
+            if output:
+                print(output)