Small fixes ; Make annotating not threaded

annotating.py

@@ -124,6 +124,11 @@ def normalize_mathtext(text):
     text = text.replace("\\\\", "\\")
     text = text.replace("\\llbracket", "[\\![")
     text = text.replace("\\rrbracket", "]\\!]")
+    text = text.replace("\\R", "\\mathbb{R}")
+    text = text.replace("\\N", "\\mathbb{N}")
+    text = text.replace("\\Z", "\\mathbb{Z}")
+    text = text.replace("\\C", "\\mathbb{C}")
+    text = text.replace("\\Q", "\\mathbb{Q}")
     # Sometimes, Gemini doesn't escape enough. In the json, you should have \\f
     text = text.replace('\f', r'\f')
     text = re.sub('\u0010', "", text)
@@ -214,8 +219,10 @@ def render_latex_text(text, width_px, bg_color=(255, 255, 255, 255), max_lines=N
     final_img.alpha_composite(img)
     return final_img
 
+import matplotlib.colors as mcolors
+
 def render_score_text(label, score, error, width_px, fontsize=18,
-                      bg_color=(255, 255, 255, 255)
+                      bg_color=(255, 255, 255, 255),
                       with_error=True):
     # 1. Calculate Color Gradient (0.0=DarkRed -> 4.0=Green)
     # Clamp score between 0 and 4
@@ -303,7 +310,7 @@ def compose_label_image(base_img, label, result, hmin,
     header_elements = []
 
     img_score = render_score_text(label, score, error, base_img.width // 2,
-                                  fontsize=18, with_error)
+                                  fontsize=18, with_error=with_error)
     header_elements.append({"type": "score", "img": img_score, "data": result})
 
     # Global Feedbacks
@@ -466,16 +473,22 @@ def process_student(student_id, labels_data, root_dir, all_labels, overwrite):
 
 
 def process_correction(root_dir, data, all_labels, overwrite=False):
-    with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:
-        # Create a list of futures
-        futures = []
-        for student_id, labels in sorted(data.items()):
-            futures.append(
-                executor.submit(process_student, student_id, labels, root_dir, all_labels, overwrite)
-            )
+    # with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor:
+    #     # Create a list of futures
+    #     futures = []
+    #     for student_id, labels in sorted(data.items()):
+    #         futures.append(
+    #             executor.submit(process_student, student_id, labels, root_dir, all_labels, overwrite)
+    #         )
 
-        # Wait for all threads to complete
-        concurrent.futures.wait(futures)
+    #     # Wait for all threads to complete
+    #     concurrent.futures.wait(futures)
+
+    # Ne pas thread cette applications
+    #  1. Il faut protéger les appels à matplotlib
+    #  2. tu vas perdre les erreurs
+    for student_id, labels in sorted(data.items()):
+        process_student(student_id, labels, root_dir, all_labels, overwrite)
 
 import argparse
 if __name__ == "__main__":