Move to real LaTeX rendering

annotating.py

@@ -219,6 +219,71 @@ 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 os
+import tempfile
+import subprocess
+import PIL.ImageOps
+
+
+def render_real_latex_text(text, width_px, bg_color=(255, 255, 255, 255), max_lines=None, fontsize=19):
+    dpi = 100
+    width_in = width_px / dpi
+    line_spacing = int(fontsize * 1.2)
+
+    # Use the 'standalone' class with 'varwidth' to auto-crop height while restricting width
+    latex_template = f"""\\documentclass[varwidth={width_in}in,margin=0.2cm]{{standalone}}
+\\usepackage[utf8]{{inputenc}}
+\\usepackage[T1]{{fontenc}}
+\\usepackage{{lmodern}}  % Enables arbitrary font scaling
+\\usepackage{{amsmath, amssymb}}
+%\\usepackage{{anyfontsize}} % replaces by lmodern
+\\begin{{document}}
+\\fontsize{{{fontsize}}}{{{line_spacing}}}\\selectfont
+{text}
+\\end{{document}}
+"""
+
+    with tempfile.TemporaryDirectory() as temp_dir:
+        tex_path = os.path.join(temp_dir, 'text.tex')
+        pdf_path = os.path.join(temp_dir, 'text.pdf')
+
+        with open(tex_path, 'w', encoding='utf-8') as f:
+            f.write(latex_template)
+
+        # Compile to PDF
+        result = subprocess.run(
+            ['pdflatex', '-interaction=nonstopmode', 'text.tex'],
+            cwd=temp_dir,
+            stdout=subprocess.DEVNULL,
+            stderr=subprocess.DEVNULL
+        )
+
+        if not os.path.exists(pdf_path):
+            raise RuntimeError("LaTeX compilation failed. Check your LaTeX syntax.")
+
+        # Convert PDF to grayscale (ignoring pdf2image's broken transparency)
+        images = convert_from_path(pdf_path, dpi=dpi)
+        gray_img = images[0].convert("L")
+
+    # 1. Invert grayscale to create an alpha mask (white bg = 0, black text = 255)
+    alpha_mask = PIL.ImageOps.invert(gray_img)
+
+    # 2. Create a transparent image with black text using the mask
+    text_img = Image.new("RGBA", gray_img.size, (0, 0, 0, 255))
+    text_img.putalpha(alpha_mask)
+
+    # 3. Create the requested background and composite the text over it
+    final_img = Image.new("RGBA", text_img.size, bg_color)
+    final_img.alpha_composite(text_img)
+
+    # (Optional) Truncate image height if max_lines is strictly enforced
+    if max_lines:
+        max_height_px = int((fontsize * 1.2 / 72.0) * dpi * max_lines) # Points to pixels
+        if final_img.height > max_height_px:
+            final_img = final_img.crop((0, 0, final_img.width, max_height_px))
+
+    return final_img
+
 import io
 from PIL import Image
 import matplotlib.pyplot as plt
@@ -376,7 +441,7 @@ def compose_label_image(base_img, label, result, hmin,
 
         # Render Text
         txt_img = render_fn(fb['text'], width_px=ANNOT_WIDTH,
-                            bg_color=(255, 200, 200, 180), max_lines=3)
+                            bg_color=(255, 200, 200, 180), max_lines=None)
 
         # Calculate Position
         center_y = (target_ymin + target_ymax) / 2
@@ -458,7 +523,8 @@ def process_student(student_id, labels_data, root_dir, all_labels, overwrite):
         d_notes[label] = str(score)
 
         final_img, _ = compose_label_image(base_img, label, result, coordinates[0],
-                                           with_empty=True)
+                                           with_empty=True,
+                                           render_fn=render_real_latex_text)
         # 7. Save Image
         save_path = os.path.join(output_dir, f"{label}.jpg")
         final_img.save(save_path)

annotating_with_checks.py

@@ -39,8 +39,9 @@ def draw_checkbox(draw, x, y, size=BOX_SIZE, label=None, fill="white"):
 
 def safe_render_latex(*args, **kwargs):
     """Thread-safe wrapper for latex rendering."""
-    with LATEX_LOCK:
+    # with LATEX_LOCK:
-        return annotating.render_latex_text(*args, **kwargs)
+    #     return annotating.render_latex_text(*args, **kwargs)
+    return annotating.render_real_latex_text(*args, **kwargs)
 
 class CheckboxRenderer:
     def __init__(self, label_name):

reading_annotations.py

@@ -226,6 +226,7 @@ def apply_actions_and_regenerate(root_dir, data, student_id, actions, notes_laye
 
     # --- 2. Process Images (Cut notes, Regenerate, Concatenate) ---
     concat_list = []
+    concat_list_F = []
     d_notes = dict.fromkeys(all_labels, "")
 
     # Iterate over images defined in bnote.json to maintain order/geometry
@@ -235,7 +236,8 @@ def apply_actions_and_regenerate(root_dir, data, student_id, actions, notes_laye
 
         # Update scores dict
         content = labels_data[label]
-        d_notes[label] = str(content['result'].get('score', 0))
+        result = content['result']
+        d_notes[label] = str(result.get('score', 0))
 
         # A. Cut Manual Notes
         hmin, hmax = img_info["hmin"], img_info["hmax"]
@@ -272,6 +274,14 @@ def apply_actions_and_regenerate(root_dir, data, student_id, actions, notes_laye
 
         concat_list.append(final_img)
 
+        perfect_no_comment = True
+        if float(d_notes[label]) != 4.0:
+            perfect_no_comment = False
+        if len(result.get('feedback', [])) != 0:
+            perfect_no_comment = False
+        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)
@@ -289,6 +299,18 @@ def apply_actions_and_regenerate(root_dir, data, student_id, actions, notes_laye
 
         full_img.save(os.path.join(output_dir, "Concat.jpg"))
         print(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)
+        full_img = Image.new("RGB", (max_w, total_h), "white")
+
+        y = 0
+        for img in concat_list_F:
+            full_img.paste(img, (0, y))
+            y += img.height
+
+        full_img.save(os.path.join(output_dir, "Concat_F.jpg"))
+        print(f"  Saved regenerated Concat_F.jpg")
 
 from pathlib import Path
 

reading_grouped_annotations.py

@@ -65,13 +65,15 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
 
     # --- 2. Process Images (Regenerate & Concatenate) ---
     concat_list = []
+    concat_list_F = []
     d_notes = dict.fromkeys(all_labels, "")
 
     # Iterate over all labels naturally to assemble a complete student profile
     sorted_labels = sorted(labels_data.items(), key=lambda x: natural_key(x[0]))
 
     for label, content in sorted_labels:
-        d_notes[label] = str(content['result'].get('score', 0))
+        result = content['result']
+        d_notes[label] = str(result.get('score', 0))
 
         pdf_path = os.path.join(root_dir, f"Copie{student_id}", f"{label}.pdf")
         if not os.path.exists(pdf_path): continue
@@ -102,6 +104,16 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
 
         concat_list.append(final_img)
 
+        perfect_no_comment = True
+        if float(d_notes[label]) != 4.0:
+            perfect_no_comment = False
+        else:
+            if len(result.get('feedback', [])) != 0:
+                perfect_no_comment = False
+        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)
@@ -119,6 +131,18 @@ def apply_actions_and_regenerate_grouped(root_dir, data, student_id, actions, la
 
         full_img.save(os.path.join(output_dir, "Concat.jpg"))
         print(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)
+        full_img = Image.new("RGB", (max_w, total_h), "white")
+
+        y = 0
+        for img in concat_list_F:
+            full_img.paste(img, (0, y))
+            y += img.height
+
+        full_img.save(os.path.join(output_dir, "Concat_F.jpg"))
+        print(f"  Saved regenerated Concat_F.jpg")
 
 
 if __name__ == "__main__":