fix colors

annotating.py

@@ -219,47 +219,55 @@ 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 io
+from PIL import Image
+import matplotlib.pyplot as plt
 import matplotlib.colors as mcolors
+from highlight_text import ax_text
 
 def render_score_text(label, score, error, width_px, fontsize=18,
                       bg_color=(255, 255, 255, 255),
                       with_error=True):
-    # 1. Calculate Color Gradient (0.0=DarkRed -> 4.0=Green)
+    # 1. Calculate Color Gradient
-    # Clamp score between 0 and 4
     t = max(0.0, min(1.0, float(score) / 4.0))
-
+    t = t*1.5 - 0.25
-    # Dark Red (139, 0, 0) to Green (0, 128, 0)
+    t = max(0.0, min(1.0, t))
-    red = 139 * (1 - t)
+    red = 200 * (1 - t)
-    green = 128 * t
+    green = 150 * t
     hex_color = mcolors.to_hex((red/255, green/255, 0))
 
-    # 2. Build Text with Mathtext Color
+    # 2. Build highlight-text String & Properties
-    # We use \color{hex} to color specific parts in Matplotlib
+    # Wrap colored parts in < >
-    score_str = f"{label}   ;   Note : \\color{{{hex_color}}}{{{score}}}"
+    score_str = f"{label}   ;   Note : <{score}>"
+    hl_props = [{"color": hex_color, "fontweight": "bold"}]
 
     if error and error != "null" and with_error:
-        # Uses standard Matplotlib color name 'orange'
+        score_str += f"   |   <Error: {error}>"
-        score_str += f"   |   \\color{{orange}}{{Error: {error}}}"
+        hl_props.append({"color": "orange", "fontweight": "bold"})
 
-    # 3. Wrap Text (using your existing heuristic)
+    # 3. Wrap Text
     dpi = 100
     fig_width = width_px / dpi
-    chars_per_line = int(fig_width * 10) # Heuristic from your snippet
+    chars_per_line = int(fig_width * 10)
 
-    # Use your existing wrapper
+    # Note: Since there is no LaTeX anymore, standard textwrap works well here
-    wrapped_text = wrap_latex_text(score_str, chars_per_line)
+    import textwrap
+    wrapped_text = textwrap.fill(score_str, width=chars_per_line)
 
-    # 4. Render (Standard Matplotlib boilerplate)
+    # 4. Render using highlight_text.ax_text
     num_lines = wrapped_text.count('\n') + 1
-    fig_height = num_lines * 0.4 + 0.2 # Slight padding adjustment
+    fig_height = num_lines * 0.4 + 0.2
 
-    fig = plt.figure(figsize=(fig_width, fig_height), dpi=dpi)
+    fig, ax = plt.subplots(figsize=(fig_width, fig_height), dpi=dpi)
+    ax.axis('off')
 
-    plt.text(0.01, 0.95, wrapped_text, fontsize=fontsize,
+    # Replaces plt.text
-             verticalalignment='top', horizontalalignment='left',
+    ax_text(0.01, 0.95, wrapped_text,
-             wrap=False) # wrap=False because wrap_latex_text handled it
+            fontsize=fontsize,
-
+            verticalalignment='top',
-    plt.axis('off')
+            horizontalalignment='left',
+            highlight_textprops=hl_props,
+            ax=ax)
 
     buf = io.BytesIO()
     plt.savefig(buf, format='png', bbox_inches='tight', pad_inches=0.1, transparent=True)
@@ -491,6 +499,7 @@ def process_correction(root_dir, data, all_labels, overwrite=False):
         process_student(student_id, labels, root_dir, all_labels, overwrite)
 
 import argparse
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Annotate copies")
     parser.add_argument("root_dir", help="Directory containing the copies")

reading_annotations.py

@@ -103,13 +103,13 @@ def detect_checks_and_notes(output_dir):
             actions.append(box)
             # It's checked, so we mask this area out for manual notes
             # Expand mask slightly to catch sloppy ticks
-            mask_draw.rectangle([x1-5, y1-5, x2+5, y2+5], fill=0)
+            mask_draw.rectangle([x1-15, y1-15, x2+15, y2+15], fill=0)
         else:
             mask_draw.rectangle([x1-2, y1-2, x2+2, y2+2], fill=0)
 
         if box["type"] == "score" and box["value"] == 0.0:
             # Mask the whole line
-            mask_draw.rectangle([0, y1-5, ref_img.width, y2+5], fill=0)
+            mask_draw.rectangle([0, y1-10, ref_img.width, y2+10], fill=0)
 
     # --- Extraction Phase ---
 
@@ -290,6 +290,8 @@ 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")
 
+from pathlib import Path
+
 if __name__ == "__main__":
     if len(sys.argv) < 2:
         print("Usage: python reading_annotations.py <Dir>")