Fix small group naming bug

copienator/commands/annotating.py

@@ -4,6 +4,7 @@ import argparse
 import io
 import os
 import re
+import shutil
 import subprocess
 import tempfile
 from collections.abc import Sequence
@@ -175,6 +176,10 @@ def render_latex_text(text, width_px, bg_color=(255, 255, 255, 255), max_lines=N
     final_img.alpha_composite(img)
     return final_img
 
+class AnnotationLatexError(RuntimeError):
+    """A feedback comment failed to render; diagnostics have been retained."""
+
+
 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
@@ -194,16 +199,37 @@ def render_real_latex_text(text, width_px, bg_color=(255, 255, 255, 255), max_li
             f.write(latex_template)
 
         # Compile to PDF
-        subprocess.run(
+        compilation = subprocess.run(
             ['pdflatex', '-interaction=nonstopmode', 'text.tex'],
             cwd=temp_dir,
-            stdout=subprocess.DEVNULL,
-            stderr=subprocess.DEVNULL,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.STDOUT,
             check=False,
         )
 
         if not os.path.exists(pdf_path):
-            raise RuntimeError("LaTeX compilation failed. Check your LaTeX syntax.")
+            diagnostics = Path(tempfile.mkdtemp(prefix="copienator-latex-error-"))
+            shutil.copy2(tex_path, diagnostics / "text.tex")
+            log_path = Path(temp_dir) / "text.log"
+            output = (compilation.stdout or b"").decode("utf-8", errors="replace")
+            (diagnostics / "compiler-output.txt").write_text(output, encoding="utf-8")
+            if log_path.exists():
+                shutil.copy2(log_path, diagnostics / "text.log")
+                log = log_path.read_text(encoding="utf-8", errors="replace")
+            else:
+                log = output
+            lines = log.splitlines()
+            first_error = next((i for i, line in enumerate(lines) if line.startswith("!")), max(0, len(lines) - 20))
+            excerpt = "\n".join(lines[first_error:first_error + 25])
+            raise AnnotationLatexError(
+                f"Échec de compilation LaTeX (code {compilation.returncode}).\n"
+                f"Commentaire LaTeX fautif :\n{text}\n\n"
+                f"Extrait du journal :\n{excerpt}\n\n"
+                f"Source LaTeX complète : {diagnostics / 'text.tex'}\n"
+                f"Diagnostics conservés dans : {diagnostics}\n"
+                "Modifiez le commentaire concerné dans correction.json, enregistrez le fichier, "
+                "puis relancez cette étape de génération des annotations."
+            )
 
         # Convert PDF to grayscale (ignoring pdf2image's broken transparency)
         images = convert_from_path(pdf_path, dpi=dpi)
@@ -295,7 +321,7 @@ def compose_label_image(base_img, label, result, hmin,
                         with_error=True,
                         with_empty=False,
                         more_right=False,
-                        with_id=None):
+                        with_id=None, source_pdf=None):
     """
     Composes the final image with annotations.
 
@@ -309,6 +335,21 @@ def compose_label_image(base_img, label, result, hmin,
                        called when elements are placed. Used for checkboxes.
     """
 
+    original_render = render_fn
+
+    def render_fn(text, *args, **kwargs):
+        try:
+            return original_render(text, *args, **kwargs)
+        except AnnotationLatexError as exc:
+            context = f"Question : {label}"
+            if source_pdf is not None:
+                source = Path(source_pdf)
+                context = f"Copie : {source.parent.name} — {context}\nPDF source : {source}"
+                context += f"\nFichier à modifier : {source.parent.parent.parent / 'correction.json'}"
+            elif with_id is not None:
+                context = f"Copie : {with_id} — {context}"
+            raise AnnotationLatexError(f"{context}\n{exc}") from exc
+
     left_pad = 0
     if base_img.width < TARGET_MIN_WIDTH:
         total_missing = TARGET_MIN_WIDTH - base_img.width
@@ -489,6 +530,7 @@ def process_student(student_id, labels_data, root_dir, all_labels, overwrite):
                 coordinates[0],
                 with_empty=True,
                 render_fn=render_real_latex_text,
+                source_pdf=pdf_full_path,
             )
             final_img.save(staging / f"{label}.jpg")
             if result.get('error', "") != "empty-answer":

copienator/commands/annotating_by_label.py

@@ -47,6 +47,7 @@ def render_item(item):
         draw_callback=checkbox_renderer.callback,
         more_right=True,
         with_id=student_id,
+        source_pdf=pdf_path,
     )
     if final_image is None:
         return None
@@ -233,15 +234,17 @@ def _unique_prefixes(groups: list[list[str]]) -> list[tuple[str, list[str]]]:
             candidate = f"{safe_labels[0]}+"
             if natural_key(candidate) > natural_key(previous):
                 base = candidate
-        prefix = base.removesuffix("i")
+        base = base.removesuffix("i")
+        # Keep related groups under the same short stem (I), I)-2, ...).
+        # Normalize before allocating a suffix so no later rewrite can collide.
+        if previous and base.startswith(previous):
+            base = previous
+        prefix = base
         counter = 2
         while prefix in used:
             prefix = f"{base}-{counter}"
             counter += 1
-        if counter == 2 and previous and previous in prefix:
-            prefix = f"{previous}-{counter}"
-        elif counter == 2:
-            previous = prefix
+        previous = base
         used.add(prefix)
         result.append((prefix, labels))
     return result
@@ -249,14 +252,16 @@ def _unique_prefixes(groups: list[list[str]]) -> list[tuple[str, list[str]]]:
 
 def _existing_group_state(
     output_root: Path,
-    prefix: str,
+    prefix: str | None = None,
 ) -> tuple[set[tuple[str, str]], int]:
     existing_items: set[tuple[str, str]] = set()
     maximum_group = 0
     if not output_root.is_dir():
         return existing_items, maximum_group
     for directory in output_root.iterdir():
-        if not directory.is_dir() or not directory.name.startswith(f"{prefix} G"):
+        if not directory.is_dir():
+            continue
+        if prefix is not None and not directory.name.startswith(f"{prefix} G"):
             continue
         try:
             maximum_group = max(maximum_group, int(directory.name.split(" G")[-1]))
@@ -317,8 +322,11 @@ def _generate_groups(
 ) -> tuple[int, bool]:
     generated = 0
     problems = False
+    # Resume by answer identity across all prefixes, including legacy names.
+    # Changing the naming scheme must not regenerate already reviewed PDFs.
+    existing_items = _existing_group_state(output_root)[0] if resume else set()
     for prefix, labels in _unique_prefixes(groups):
-        existing_items, maximum_group = (
+        _, maximum_group = (
             _existing_group_state(output_root, prefix) if resume else (set(), 0)
         )
         items = [

copienator/commands/annotating_with_checks.py

@@ -184,6 +184,7 @@ def _render_student(
             content["result"],
             content["coordinates"][0],
             draw_callback=checkbox_renderer.callback,
+            source_pdf=pdf_path,
         )
         if final_image is None:
             problems = True

copienator/commands/gemini_for_enonce.py

@@ -716,7 +716,7 @@ def process_exam(
 
     with io.StringIO() as f, io.StringIO() as f_full:
 
-        header = "# Edit labels. Modify groups (---). Ensure label uniqueness (XX). Duplicate CONTEXT.\n\n"
+        header = "# Edit labels. Modify groups (---). Ensure label uniqueness (XX). Duplicate/modify CONTEXT.\n\n"
         f.write(header)
         f_full.write(header)
 

copienator/crop_diagnostics.py

@@ -0,0 +1,116 @@
+"""Optional detector explanations and independent, manually annotated crop checks.
+
+Annotations are evaluation data: they are never passed to the ink detector.
+"""
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import cv2
+import numpy as np
+from PIL import Image, ImageDraw
+
+
+MASK_DESCRIPTIONS = {
+    'isolated_edge_marks': 'Small border marks excluded by same-page edge position and isolation',
+    'confirmed_ruling': 'Confirmed neutral-paper ruling pixels',
+    'paper_suppressed': 'Foreground pixels suppressed by paper cleanup',
+    'rejected_artifacts': 'Pixels rejected as specks, thin ruling remnants or repeated holes',
+    'repeated_holes': 'Pixels rejected as repeated hole components during initial cleanup',
+    'refinement_removed': 'Pixels removed by the large-blank refinement',
+    'ruling_residuals': 'Thin seed-candidate remnants adjoining confirmed suppressed paper pixels',
+    'strong_seeds': 'Strong seed pixels, including any surviving paper or pagination',
+    'weak_candidates': 'Weak candidates before seed proximity and connectivity checks',
+    'foreground': 'All retained pixels that actually determine the crop',
+    'recovered_weak': 'Weak pixels recovered around strong seeds',
+    'unretained_weak': 'Weak candidates not retained; these may be ink OR paper',
+}
+
+
+def check_protected_regions(regions, result, *, width_mm, height_mm, shape):
+    """Fail if either crop boundary crosses a reviewed content rectangle.
+
+    Rectangles are [left, top, right, bottom] in original displayed millimetres.
+    They conservatively protect their entire area, including enclosed whitespace.
+    """
+    h = shape[0]
+    top = result['top_px'] / h * height_mm
+    bottom = result['bottom_px'] / h * height_mm
+    if not 0 <= result['top_px'] <= result['bottom_px'] <= h:
+        raise ValueError('Invalid crop bounds')
+    rows = []
+    seen = set()
+    for region in regions:
+        name = region['id']
+        if name in seen:
+            raise ValueError(f'Duplicate protected region: {name}')
+        seen.add(name)
+        x0, y0, x1, y1 = region['bbox_mm']
+        if not all(np.isfinite([x0,y0,x1,y1])) or not (
+                0 <= x0 < x1 <= width_mm and 0 <= y0 < y1 <= height_mm):
+            raise ValueError(f'Invalid protected rectangle: {name}')
+        top_loss = max(0.0, min(y1, top)-y0)
+        bottom_loss = max(0.0, y1-max(y0, bottom))
+        rows.append(dict(id=name, label=region['label'], bbox_mm=region['bbox_mm'],
+            passed=top_loss <= 1e-9 and bottom_loss <= 1e-9,
+            clipped_edges=[edge for edge, loss in [('top',top_loss),('bottom',bottom_loss)] if loss > 1e-9],
+            clipped_height_mm=round(top_loss+bottom_loss,4),
+            clipped_area_fraction=round(min(1.0,(top_loss+bottom_loss)/(y1-y0)),4)))
+    return rows
+
+
+def save_diagnostics(rgb, result, diagnostics, destination: Path, *, regions=(),
+                     width_mm, height_mm):
+    """Export exact binary masks, readable overlays and JSON boundary explanations."""
+    destination.mkdir(parents=True, exist_ok=True)
+    masks = diagnostics['masks']
+    files = {}
+    for name, mask in masks.items():
+        if mask.shape != rgb.shape[:2] or mask.dtype != np.bool_:
+            raise ValueError(f'Invalid diagnostic mask: {name}')
+        path = destination / f'{name}.png'
+        Image.fromarray(mask).save(path)
+        files[name] = path.name
+    views = {
+        'strong-seeds': [('strong_seeds',(220,50,20))],
+        'retained-ink': [('strong_seeds',(220,50,20)),('recovered_weak',(245,140,0))],
+        'unretained-weak': [('unretained_weak',(155,40,200))],
+        'paper-and-artifacts': [('paper_suppressed',(20,140,200)),
+            ('rejected_artifacts',(155,40,200)),('ruling_residuals',(155,40,200)),
+            ('isolated_edge_marks',(220,105,0)),
+            ('refinement_removed',(245,140,0))],
+        'protected-content': [],
+    }
+    preview = Image.fromarray(rgb)
+    preview.thumbnail((1000,1400))
+    sy = preview.height / rgb.shape[0]
+    overlays = {}
+    for name, layers in views.items():
+        canvas = np.array(preview).astype(np.float32)
+        for mask_name, colour in layers:
+            # Mark every source pixel represented by a preview pixel; thin strokes
+            # must not disappear merely because a preview was downsampled.
+            mask = masks[mask_name]
+            coverage = cv2.resize(mask.astype(np.float32), preview.size, interpolation=cv2.INTER_AREA) > 0
+            canvas[coverage] = .3*canvas[coverage] + .7*np.array(colour)
+        image = Image.fromarray(np.clip(canvas,0,255).astype(np.uint8))
+        draw = ImageDraw.Draw(image)
+        for region in regions:
+            x0,y0,x1,y1 = region['bbox_mm']
+            box = (x0/width_mm*image.width,y0/height_mm*image.height,
+                   x1/width_mm*image.width,y1/height_mm*image.height)
+            clipped = result['top_px']*sy > box[1] or result['bottom_px']*sy < box[3]
+            colour = (200,0,160) if clipped else (0,150,170)
+            draw.rectangle(box, outline=colour, width=2)
+        for y in (result['top_px']*sy, result['bottom_px']*sy):
+            draw.line((0,min(y,image.height-1),image.width,min(y,image.height-1)),fill=(215,20,20),width=2)
+        path = destination / f'{name}.jpg'
+        image.save(path, quality=90)
+        overlays[name] = path.name
+    data = {key:value for key,value in diagnostics.items() if key != 'masks'}
+    data.update(detector=result, mask_files=files, mask_descriptions=MASK_DESCRIPTIONS,
+                overlays=overlays, protected_regions=list(regions))
+    report = destination/'explanation.json'
+    report.write_text(json.dumps(data,indent=2)+'\n')
+    return dict(report=report.name, overlays=overlays, masks=files)

copienator/crop_exercise_bottoms.py

@@ -24,7 +24,6 @@ from copienator.ink_detection import detect_bounds
 
 LINES_PER_PAGE = 36
 MINIMUM_HEIGHT_LINES = 10
-IGNORED_BOTTOM_LINES = 0.75
 MINIMUM_CROP_LINES = 4
 
 
@@ -93,13 +92,8 @@ def process_exercise_pdf(
                 pixmap.height, pixmap.width, 3
             )
             pixels_per_point = pixmap.height / visible_height
-            ignored_pixels = min(
-                pixmap.height - 1,
-                round(IGNORED_BOTTOM_LINES * line_points * pixels_per_point),
-            )
-            analysis_bottom = pixmap.height - ignored_pixels
             detection = detect_bounds(
-                rgb[:analysis_bottom], dpi=dpi, padding_mm=padding_mm, min_crop_mm=0
+                rgb, dpi=dpi, padding_mm=padding_mm, min_crop_mm=0
             )
             proposed_bottom = detection["bottom_px"]
             removed_points = (pixmap.height - proposed_bottom) / pixels_per_point

copienator/edge_marks.py

@@ -0,0 +1,95 @@
+"""Group small isolated border marks using evidence from one displayed page.
+
+This identifies dispensable border marks, without recognizing pagination or
+consulting other pages. Component IDs are local to the caller's foreground.
+Long paper-line candidates are excluded from grouping but remain in the crop.
+"""
+import numpy as np
+
+
+def classify_edge_marks(labels, stats, eligible, rgb, dpi):
+    px = dpi/25.4
+    height, width = labels.shape
+    components = []
+    for i, (x, y, w, h, area) in enumerate(stats[1:], 1):
+        if not eligible[i] or area < .15*px*px:
+            continue
+        # Exclusion from candidate grouping ONLY. Pixels remain in the crop mask.
+        if ((h > 25*px and w < 3*px) or (w > 25*px and h < .6*px)):
+            continue
+        components.append(i)
+    parent = {i:i for i in components}
+    def find(i):
+        while parent[i] != i:
+            parent[i] = parent[parent[i]]
+            i = parent[i]
+        return i
+    # A y sweep bounds the search on noisy pages; uncertain large groups stay.
+    edge_components = [i for i in components if stats[i,2] <= 40*px
+                       and stats[i,3] <= 18*px and
+                       (stats[i,1]+stats[i,3] <= 40*px
+                        or stats[i,1] >= height-40*px)]
+    if len(edge_components) > 512:
+        return [], []
+    colours = {}
+    if rgb is not None:
+        for i in edge_components:
+            x,y,w,h,_ = stats[i]
+            values = rgb[y:y+h,x:x+w][labels[y:y+h,x:x+w]==i]
+            colours[i] = float(np.median(values.max(axis=1)-values.min(axis=1)))
+    ordered = sorted(edge_components, key=lambda i:stats[i,1])
+    for a, i in enumerate(ordered):
+        x,y,w,h,_ = stats[i]
+        for j in ordered[a+1:]:
+            xx,yy,ww,hh,_ = stats[j]
+            if yy > y+h+1.5*px:
+                break
+            gap_x = max(0, xx-(x+w), x-(xx+ww))
+            gap_y = max(0, yy-(y+h), y-(yy+hh))
+            incompatible = (rgb is not None and
+                ((colours[i] < 35 and colours[j] > 60)
+                 or (colours[j] < 35 and colours[i] > 60)))
+            if not incompatible and gap_x <= 3*px and gap_y <= 1.5*px:
+                parent[find(j)] = find(i)
+    groups = {}
+    for i in edge_components:
+        groups.setdefault(find(i), []).append(i)
+    rows = []
+    for ids in groups.values():
+        s=stats[ids];x,y=s[:,:2].min(axis=0);right,bottom=(s[:,:2]+s[:,2:4]).max(axis=0)
+        w,h=right-x,bottom-y
+        if not (w <= 40*px and h <= 18*px and h >= 1.5*px):
+            continue
+        edge = 'top' if bottom <= 40*px else 'bottom' if y >= height-40*px else None
+        if edge is None:
+            continue
+        underline_ids=[]
+        for i in ids:
+            xx,yy,ww,hh,area=stats[i]
+            if ww > 3*hh and ww >= .65*w and yy+hh >= bottom-1.5*px:
+                underline_ids.append(i)
+        lateral = (x+w/2 < width*.25 or x+w/2 > width*.75)
+        # Check separation from other compact strokes across the full width.
+        # Confirmed long line candidates remain in the actual crop mask.
+        body = [i for i in components if i not in ids and stats[i,3] < 18*px]
+        edge_distance = (y if edge == 'top' else height-bottom)/px
+        if body:
+            gap = ((min(stats[i,1] for i in body)-(y+h))/px if edge=='top' else
+                   (y-max(stats[i,1]+stats[i,3] for i in body))/px)
+        else:
+            gap = None
+        truncated = (x <= px or y <= px or right >= width-px or bottom >= height-px)
+        reasons=[]
+        if lateral:reasons.append('lateral-placement')
+        if gap is not None and gap >= 20:reasons.append('all-column-stroke-gap>=20mm')
+        if edge_distance <= 15:reasons.append('within-15mm-of-edge')
+        if underline_ids:reasons.append('underline-protection')
+        if truncated:reasons.append('scan-edge-truncated')
+        proposed = (lateral and edge_distance <= 15 and gap is not None
+                    and gap >= 20 and not underline_ids and not truncated)
+        rows.append(dict(bbox_mm=[round(float(v/px),2) for v in [x,y,x+w,y+h]],
+                         component_ids=ids,edge=edge,edge_distance_mm=round(edge_distance,2),gap_mm=None if gap is None else round(gap,2),
+                         evidence=reasons,proposed_pagination=bool(proposed)))
+    removed = [i for row in rows if row['proposed_pagination'] for i in row['component_ids']]
+    return removed, rows
+

copienator/ink_detection.py

@@ -10,6 +10,8 @@ from functools import lru_cache
 import cv2
 import numpy as np
 
+from copienator.edge_marks import classify_edge_marks
+from copienator.paper_ruling import ruling_suppression, _edge_connected_family
 from copienator.paper_background import _skew, _ruling, _foreground, _content_mask
 
 
@@ -136,7 +138,8 @@ def _large_blank_ink(gray: np.ndarray, clean: np.ndarray, dpi: float):
     return result, len(holes), changed
 
 
-def _neutral_paper_foreground(gray: np.ndarray, chroma: np.ndarray, dpi: float):
+def _neutral_paper_foreground(gray: np.ndarray, chroma: np.ndarray, dpi: float,
+                              *, diagnostics: dict | None = None):
     """Clean confirmed dark ruling before it can seed whole pages.
 
     Returns None for ordinary ink components or unconfirmed paper geometry.
@@ -167,15 +170,26 @@ def _neutral_paper_foreground(gray: np.ndarray, chroma: np.ndarray, dpi: float):
                                    cv2.THRESH_BINARY_INV,block,9)
     horizontal, nh = _ruling(binary,True)
     vertical, nv = _ruling(binary,False)
-    if not (nh or nv):
+    if not ((nh and _edge_connected_family(binary,horizontal,True))
+            or (nv and _edge_connected_family(binary,vertical,False))):
         return None, dict(paper_cleanup=False)
     # The permissive mask retains faint, isolated marks.
     # Bands identify where ruling is expected, but only actual dark pixels
     # inside them may be suppressed. Erasing the complete band loses faint
     # writing alongside a dark grid line.
     paper_pixels = (horizontal|vertical) & ((normalized < 160).astype(np.uint8)*255)
-    clean, holes = _content_mask(_foreground(normalized,dpi,9,paper_pixels),dpi,nh,nv)
+    stages = {} if diagnostics is not None else None
+    foreground = _foreground(normalized,dpi,9,paper_pixels, diagnostics=stages)
+    clean, holes = _content_mask(foreground,dpi,nh,nv, diagnostics=stages)
+    before_refinement = clean.copy() if diagnostics is not None else None
     clean, repeated_holes, refined = _large_blank_ink(deskewed, clean, dpi)
+    if diagnostics is not None:
+        stages['confirmed_ruling'] = paper_pixels > 0
+        stages['refinement_removed'] = (before_refinement > 0) & (clean == 0)
+        inverse = cv2.invertAffineTransform(matrix)
+        for name, mask in stages.items():
+            diagnostics[name] = cv2.warpAffine(mask.astype(np.uint8), inverse,
+                (width,height), flags=cv2.INTER_NEAREST, borderValue=0) > 0
     restored = cv2.warpAffine(clean, cv2.invertAffineTransform(matrix),
                               (width,height), flags=cv2.INTER_NEAREST, borderValue=0)
     return restored > 0, dict(paper_cleanup=True, angle_deg=round(angle,3),
@@ -184,22 +198,45 @@ def _neutral_paper_foreground(gray: np.ndarray, chroma: np.ndarray, dpi: float):
                              large_blank_refinement=refined)
 
 
-def _seed_mask(mask: np.ndarray, px: float) -> np.ndarray:
+def _seed_mask(mask: np.ndarray, px: float, *, paper_nearby=None,
+               diagnostics=None) -> np.ndarray:
     n, labels, stats, _ = cv2.connectedComponentsWithStats(mask.astype(np.uint8), 8)
     keep = np.zeros(n, bool)
     keep[1:] = ((stats[1:, 4] >= max(4, .12*px*px))
                 & (stats[1:, 2] >= max(2, round(.35*px)))
                 & (stats[1:, 3] >= max(2, round(.35*px))))
+    if paper_nearby is not None:
+        w, h = stats[:,2], stats[:,3]
+        thin = max(2, round(.45*px))
+        aligned = ((np.minimum(w,h) <= thin)
+                   & (np.maximum(w,h) >= 3*np.minimum(w,h)))
+        overlap = np.bincount(labels[paper_nearby], minlength=n)
+        remnants = keep & aligned & (overlap >= .8*stats[:,4])
+        keep[remnants] = False
+        if diagnostics is not None:
+            diagnostics['ruling_residuals'] |= remnants[labels]
     return keep[labels]
 
 
 def detect_bounds(rgb: np.ndarray, dpi: float = 200, padding_mm: float = 6,
-                  min_crop_mm: float = 5) -> dict:
+                  min_crop_mm: float = 5, *, diagnostics: dict | None = None,
+                  colour_cleanup: bool = False, edge_mark_cleanup: bool = True) -> dict:
     """Locate strong ink, recover adjacent faint strokes, and retain padding.
 
     Neutral punched-hole shadows usually have neither sufficient chroma nor
     sufficient darkness to seed a region. Nothing is discarded merely because
     it is in a side margin. Two seed thresholds expose unstable boundaries.
+
+    Small isolated side-margin marks near the physical top/bottom edge are
+    excluded using same-page position and separation. Marks near text remain.
+    edge_mark_cleanup=False is available for evaluation comparisons.
+
+    Experimental colour cleanup is opt-in because its full-resolution model
+    is too expensive for the default PDF processing path.
+
+    Optional diagnostics are written to a separate caller-owned dictionary.
+    Its masks use the original image coordinates and never influence decisions
+    or enter the JSON-serializable return value.
     """
     px = dpi/25.4
     h, w = rgb.shape[:2]
@@ -214,14 +251,38 @@ def detect_bounds(rgb: np.ndarray, dpi: float = 200, padding_mm: float = 6,
     vertical = cv2.morphologyEx(darkness, cv2.MORPH_OPEN,
                                 np.ones((length, 1), np.uint8))
     residual = cv2.subtract(darkness, np.maximum(horizontal, vertical))
-    # Strong strokes bypass the line-background estimate entirely: even a long
-    # isolated black or coloured fraction bar must survive. Local contrast is
-    # used only to recover weaker surrounding strokes.
+    # The directional estimate alone cannot veto a strong fraction bar. Only
+    # independently confirmed paper geometry may suppress a strong candidate.
     neutral_ink = gray < 95
-    cleaned, paper_info = _neutral_paper_foreground(gray, chroma, dpi)
+    if diagnostics is not None:
+        diagnostics.clear()
+        diagnostics['masks'] = {}
+        diagnostics['thresholds'] = []
+    masks = diagnostics['masks'] if diagnostics is not None else None
+    cleaned, paper_info = _neutral_paper_foreground(gray, chroma, dpi, diagnostics=masks)
     if cleaned is not None:
-        neutral_ink = cleaned
+        # Adaptive neutral cleanup includes faint paper fragments. Such pixels
+        # need local contrast or substantial darkness before they seed a crop.
+        neutral_ink = cleaned & ((residual > 25) | (gray < 95))
+    if colour_cleanup:
+        suppressed, ruling_info = ruling_suppression(rgb, dpi)
+    else:
+        suppressed, ruling_info = np.zeros((h,w), bool), {}
+    paper_info.update(ruling_info)
+    neutral_ink &= ~suppressed
+    paper_nearby = (cv2.dilate(suppressed.astype(np.uint8),
+                    np.ones((3,3),np.uint8)) > 0) if np.any(suppressed) else None
+    if masks is not None:
+        masks['paper_suppressed'] = masks.get('paper_suppressed', np.zeros((h,w), bool)) | suppressed
+        masks['confirmed_ruling'] = masks.get('confirmed_ruling', np.zeros((h,w), bool)) | suppressed
+        masks['ruling_residuals'] = np.zeros((h,w), bool)
+        masks['isolated_edge_marks'] = np.zeros((h,w), bool)
     weak = ((chroma > 60) | ((gray < 175) & (residual > 25))).astype(np.uint8)
+    weak[suppressed] = 0
+    if masks is not None:
+        masks['strong_seeds'] = np.zeros((h,w), bool)
+        masks['foreground'] = np.zeros((h,w), bool)
+        masks['weak_candidates'] = weak > 0
     radius = max(1, round(2*px))
     kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2*radius+1, 2*radius+1))
     extents = []
@@ -232,26 +293,67 @@ def detect_bounds(rgb: np.ndarray, dpi: float = 200, padding_mm: float = 6,
             counts.append(counts[0])
             if extents:
                 extents.append(extents[0])
+            if diagnostics is not None:
+                diagnostics['thresholds'].append(dict(
+                    diagnostics['thresholds'][0], threshold=115, reused=True))
             continue
-        seeds = _seed_mask((chroma > threshold) | neutral_ink, px)
+        seeds = _seed_mask(((chroma > threshold) | neutral_ink) & ~suppressed, px,
+                           paper_nearby=paper_nearby, diagnostics=masks)
         counts.append(int(np.count_nonzero(seeds)))
         if not np.any(seeds):
+            if diagnostics is not None:
+                diagnostics['thresholds'].append(dict(threshold=threshold,
+                    seed_pixels=0, extent=None, limiting_components={'top': [], 'bottom': []}))
             continue
         # Limit weak recovery to a physical neighbourhood: faint grid lines
         # connected to a letter cannot grow into a full-page foreground mask.
         nearby = cv2.dilate(seeds.astype(np.uint8), kernel)
         candidate = (weak & nearby) | seeds.astype(np.uint8)
-        n, labels = cv2.connectedComponents(candidate, 8)
+        if edge_mark_cleanup:
+            n, labels, stats, _ = cv2.connectedComponentsWithStats(candidate, 8)
+        else:
+            n, labels = cv2.connectedComponents(candidate, 8)
         seeded_labels = np.zeros(n, bool)
         seeded_labels[np.unique(labels[seeds])] = True
         seeded_labels[0] = False
-        ys = np.flatnonzero(np.any(seeded_labels[labels], axis=1))
+        removed, groups = (classify_edge_marks(labels, stats, seeded_labels, rgb, dpi)
+                           if edge_mark_cleanup else ([], []))
+        if removed:
+            remaining = seeded_labels.copy()
+            remaining[removed] = False
+            # Keep the original ink bounds if no foreground would remain.
+            if np.any(remaining):
+                if masks is not None:
+                    discarded = np.zeros(n,bool)
+                    discarded[removed] = True
+                    masks['isolated_edge_marks'] |= discarded[labels]
+                seeded_labels = remaining
+        retained = seeded_labels[labels]
+        if masks is not None:
+            masks['strong_seeds'] |= seeds & retained
+        ys = np.flatnonzero(np.any(retained, axis=1))
         extents.append((int(ys.min()), int(ys.max())+1))
+        if diagnostics is not None:
+            masks['foreground'] |= retained
+            diagnostics['thresholds'].append(_explain_extent(retained, seeds,
+                chroma, neutral_ink, threshold, extents[-1], px))
+            diagnostics['thresholds'][-1]['edge_mark_groups'] = groups
     result = dict(top_px=0, bottom_px=h, angle_deg=None,
                   horizontal_lines=0, vertical_lines=0, edge_artifacts=0,
                   detector="ink", seed_pixels=counts, status="review-no-ink-seeds")
     result.update(paper_info)
+    if diagnostics is not None:
+        masks['recovered_weak'] = masks['foreground'] & ~masks['strong_seeds']
+        masks['unretained_weak'] = masks['weak_candidates'] & ~masks['foreground']
+        for name in ('confirmed_ruling', 'paper_suppressed', 'rejected_artifacts',
+                     'repeated_holes', 'refinement_removed'):
+            masks.setdefault(name, np.zeros((h,w), bool))
+        diagnostics['shape'] = [h,w]
+        diagnostics['mask_pixels'] = {name: int(mask.sum()) for name, mask in masks.items()}
     if not extents:
+        if diagnostics is not None:
+            diagnostics['edges'] = {edge: {'reason': 'no-reliable-ink-seeds',
+                'boundary_px': 0 if edge == 'top' else h} for edge in ('top', 'bottom')}
         return result
     pad = padding_mm*px
     top = max(0, int(np.floor(min(e[0] for e in extents)-pad)))
@@ -263,6 +365,7 @@ def detect_bounds(rgb: np.ndarray, dpi: float = 200, padding_mm: float = 6,
         for edge, name in ((0, 'top'), (1, 'bottom')):
             if abs(extents[0][edge]-extents[1][edge]) > max(pad, 3*px):
                 uncertain.append(name)
+    proposed_top, proposed_bottom = top, bottom
     if top < min_crop_mm*px:
         top = 0
     if h-bottom < min_crop_mm*px:
@@ -270,4 +373,39 @@ def detect_bounds(rgb: np.ndarray, dpi: float = 200, padding_mm: float = 6,
     result.update(top_px=top, bottom_px=bottom,
                   status=('review-'+'-'.join(uncertain) if uncertain else
                           'cropped' if top or bottom < h else 'unchanged'))
+    if diagnostics is not None:
+        diagnostics['edges'] = {}
+        for edge, boundary, proposed, extent in (
+                ('top', top, proposed_top, min(e[0] for e in extents)),
+                ('bottom', bottom, proposed_bottom, max(e[1] for e in extents))):
+            removal = boundary if edge == 'top' else h-boundary
+            reason = 'crop-to-retained-ink-with-padding' if removal else (
+                'below-minimum-crop' if boundary != proposed else 'ink-or-padding-reaches-edge')
+            diagnostics['edges'][edge] = dict(boundary_px=boundary,
+                proposed_boundary_px=proposed, ink_extent_px=extent,
+                reason=reason, threshold_disagreement=edge in uncertain,
+                limiting_thresholds=[i['threshold'] for i in diagnostics['thresholds']
+                    if i['extent'] is not None and i['extent'][0 if edge == 'top' else 1] == extent])
     return result
+
+
+def _explain_extent(retained, seeds, chroma, neutral, threshold, extent, px):
+    """Describe actual boundary-setting regions; infer no handwriting semantics."""
+    _, labels, stats, _ = cv2.connectedComponentsWithStats(retained.astype(np.uint8), 8)
+    limiting = {}
+    for edge, row in (('top', extent[0]), ('bottom', extent[1]-1)):
+        ids = [int(i) for i in np.unique(labels[row]) if i]
+        components = []
+        for identifier in ids:
+            x,y,w,h,area = map(int, stats[identifier])
+            region = labels[y:y+h,x:x+w] == identifier
+            strong = seeds[y:y+h,x:x+w] & region
+            components.append(dict(component_id=identifier, bbox_px=[x,y,x+w,y+h],
+                bbox_mm=[round(v/px,3) for v in (x,y,x+w,y+h)], area_px=area,
+                seed_pixels=int(strong.sum()),
+                coloured_seed_pixels=int((strong & (chroma[y:y+h,x:x+w] > threshold)).sum()),
+                neutral_seed_pixels=int((strong & neutral[y:y+h,x:x+w]).sum()),
+                reason='retained-component-touches-' + edge + '-ink-extent'))
+        limiting[edge] = components
+    return dict(threshold=threshold, seed_pixels=int(seeds.sum()),
+                extent=list(extent), limiting_components=limiting)

copienator/json_io.py

@@ -23,6 +23,14 @@ def read_json(path: str | Path, *, default: T | object = _MISSING) -> T:
     target = Path(path)
     try:
         with target.open("r", encoding="utf-8") as stream:
+            if target.name == "refaire.json":
+                # This user-edited selection supports whole-line // comments.
+                # Preserve line numbers in JSON diagnostics and keep other JSON strict.
+                text = "".join(
+                    "\n" if line.lstrip().startswith("//") else line
+                    for line in stream
+                )
+                return cast(T, json.loads(text))
             return cast(T, json.load(stream))
     except FileNotFoundError:
         if default is _MISSING:

copienator/paper_background.py

@@ -82,7 +82,7 @@ def _ruling(binary: np.ndarray, horizontal: bool) -> tuple[np.ndarray, int]:
 
 
 def _foreground(gray: np.ndarray, dpi: float, threshold: int,
-                ruling: np.ndarray) -> np.ndarray:
+                ruling: np.ndarray, *, diagnostics: dict | None = None) -> np.ndarray:
     block = max(15, int(dpi / 5) | 1)
     binary = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                    cv2.THRESH_BINARY_INV, block, threshold)
@@ -100,12 +100,14 @@ def _foreground(gray: np.ndarray, dpi: float, threshold: int,
         # locally thicker excess strokes inside the suppression mask.
         excess_ink = cv2.erode(excess_ink, np.ones((2, 2), np.uint8)) > 0
         mask &= ~excess_ink
+    if diagnostics is not None:
+        diagnostics['paper_suppressed'] = mask & (binary > 0)
     binary[mask] = 0
     return binary
 
 
 def _content_mask(binary: np.ndarray, dpi: float, nh: int = 0,
-                  nv: int = 0) -> tuple[np.ndarray, int]:
+                  nv: int = 0, *, diagnostics: dict | None = None) -> tuple[np.ndarray, int]:
     """Filter only tiny speckles and repeated, matching edge-hole components."""
     px = dpi / 25.4
     # Small closing reconnects strokes interrupted by paper-line suppression.
@@ -142,5 +144,10 @@ def _content_mask(binary: np.ndarray, dpi: float, nh: int = 0,
             holes.update(similar)
     if holes:
         keep[list(holes)] = False
+    if diagnostics is not None:
+        diagnostics['rejected_artifacts'] = ~keep[labels] & (binary > 0)
+        hole_labels = np.zeros(n, bool)
+        hole_labels[list(holes)] = True
+        diagnostics['repeated_holes'] = hole_labels[labels] & (binary > 0)
     # Bound original residual ink, not the expanded/grouped mask.
     return (keep[labels] & (binary > 0)).astype(np.uint8), len(holes)

copienator/paper_ruling.py

@@ -0,0 +1,165 @@
+"""Colour-aware suppression of pixels supported by recurring paper geometry.
+
+This only identifies paper ruling. It does not classify pagination or introduce
+an independent faint-writing detector.
+"""
+
+import cv2
+import numpy as np
+
+from copienator.paper_background import _ruling, _runs, _skew
+
+
+def _maximum(image):
+    first, second, third = cv2.split(image)
+    return cv2.max(cv2.max(first, second), third)
+
+
+def _minimum(image):
+    first, second, third = cv2.split(image)
+    return cv2.min(cv2.min(first, second), third)
+
+
+def _thick_strokes(binary, dpi):
+    """Protect substantial excess thickness without keeping grid junctions."""
+    height, width = binary.shape
+    widths = []
+    for horizontal in (True, False):
+        dimension = width if horizontal else height
+        length = max(25, round(dimension*.12))
+        kernel = np.ones((1,length) if horizontal else (length,1), np.uint8)
+        lines = cv2.morphologyEx(binary, cv2.MORPH_OPEN, kernel)
+        counts = np.count_nonzero(lines, axis=1 if horizontal else 0)
+        widths.extend(b-a for a,b in _runs(counts > dimension*.3))
+    thickness = max(3, int(np.ceil(np.quantile(widths,.95)))+2) if widths else 3
+    kernel = np.ones((thickness,thickness), np.uint8)
+    cores = cv2.erode(binary, kernel)
+    count, labels, stats, _ = cv2.connectedComponentsWithStats(cores, 8)
+    keep = np.zeros(count, bool)
+    px = dpi/25.4
+    x, _, w, h, area = stats[1:].T
+    keep[1:] = ((area >= .3*px*px) & (np.maximum(w,h) >= 1.5*px)
+                & (np.minimum(w,h) >= 2))
+    # A slightly thicker full-height margin rule is still a paper candidate.
+    # It will only be removed if its colour also passes the ruling model below.
+    side_line = ((h > height*.7) & (w < 2*px)
+                 & ((x < width*.3) | (x > width*.7)))
+    keep[1:] &= ~side_line
+    return cv2.dilate(keep[labels].astype(np.uint8), kernel) > 0
+
+
+def _edge_connected_family(binary, bands, horizontal):
+    """Require several ruling bands reaching a physical edge of the scan.
+
+    Regularly spaced fraction bars inside an answer are not enough evidence.
+    """
+    dimension = binary.shape[1] if horizontal else binary.shape[0]
+    length = max(25, round(dimension*.12))
+    lines = cv2.morphologyEx(binary, cv2.MORPH_OPEN,
+        np.ones((1,length) if horizontal else (length,1), np.uint8))
+    edge = max(3, round(dimension*.08))
+    if horizontal:
+        touching = np.any(lines[:,:edge] | lines[:,-edge:], axis=1)
+        positions = np.any(bands, axis=1)
+    else:
+        touching = np.any(lines[:edge] | lines[-edge:], axis=0)
+        positions = np.any(bands, axis=0)
+    return sum(np.any(touching[a:b]) for a,b in _runs(positions)) >= 5
+
+
+def ruling_suppression(rgb: np.ndarray, dpi: float):
+    """Return a mask in original coordinates and evidence for paper cleanup.
+
+    Require a periodic horizontal or vertical family before modelling any line.
+    Compare actual RGB pixels with locally persistent line colour, retain darker
+    or different-colour strokes, and guard unusually thick strokes. A separate
+    full-height margin rule is eligible only alongside that confirmed family.
+    """
+    height, width = rgb.shape[:2]
+    lowest = _minimum(rgb)
+    chroma = cv2.subtract(_maximum(rgb), lowest)
+    _, _, stats, _ = cv2.connectedComponentsWithStats(
+        ((lowest < 215) & ((chroma > 20) | (lowest < 160))).astype(np.uint8), 8)
+    spans = np.maximum(stats[1:,2]/width, stats[1:,3]/height)
+    if not (np.any(spans > .35) or np.count_nonzero(spans > .05) >= 3):
+        return np.zeros((height,width), bool), {}
+
+    angle = _skew(lowest, angle_step=.5)
+    matrix = cv2.getRotationMatrix2D((width/2,height/2), angle, 1)
+    corners = cv2.transform(np.array([[[0,0],[width,0],[0,height],
+                                       [width,height]]], dtype=float), matrix)[0]
+    origin = np.floor(corners.min(axis=0))
+    size = np.ceil(corners.max(axis=0)-origin).astype(int)
+    matrix[:,2] -= origin
+    image = cv2.warpAffine(rgb, matrix, tuple(size), borderValue=(255,255,255))
+    dark = 255-image
+    dark16 = dark.astype(np.int16)
+    darkness = _maximum(dark)
+    binary = cv2.adaptiveThreshold(_minimum(image), 255,
+        cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,
+        max(15,int(dpi/5) | 1), 5)
+    horizontal, nh = _ruling(binary, True)
+    vertical, nv = _ruling(binary, False)
+    if not ((nh and _edge_connected_family(binary,horizontal,True))
+            or (nv and _edge_connected_family(binary,vertical,False))):
+        return np.zeros((height,width), bool), {}
+
+    thick = _thick_strokes(binary, dpi)
+    removed = np.zeros(binary.shape, bool)
+    protected = np.zeros(binary.shape, bool)
+    for is_horizontal, bands, count in ((True,horizontal,nh),(False,vertical,nv)):
+        length = max(25, round(5.2*dpi/25.4))
+        tolerance = max(3, round(.8*dpi/25.4) | 1)
+        transverse = np.ones((tolerance,1) if is_horizontal else (1,tolerance), np.uint8)
+        along = np.ones((1,length) if is_horizontal else (length,1), np.uint8)
+        # Small transverse tolerance follows local scan warp. The RGB model is
+        # still tested against actual pixels; it does not erase entire bands.
+        broadened = cv2.dilate(dark, transverse)
+        model = cv2.morphologyEx(broadened, cv2.MORPH_OPEN, along)
+        support = _maximum(model) > 9
+        if count:
+            support &= bands > 0
+        close = _maximum(np.abs(dark16-model.astype(np.int16))) < 40
+        sample = support & (darkness > 9) & close & ~thick
+        # Neutral, red, green and blue line families are modelled separately so
+        # a red margin rule cannot be mistaken for unusually dark blue writing.
+        first, second, third = cv2.split(model)
+        classes = np.full(binary.shape, 2, np.uint8)
+        classes[second <= third] = 1
+        classes[(first <= second) & (first <= third)] = 0
+        classes[cv2.subtract(_maximum(model),_minimum(model)) < 25] = 3
+        credible = np.zeros(binary.shape, bool)
+        for colour in range(4):
+            selected = sample & (classes == colour)
+            if selected.sum() < 100:
+                continue
+            yy, xx = np.nonzero(selected)
+            spread = np.ptp(yy if is_horizontal else xx)
+            axis_size = image.shape[0] if is_horizontal else image.shape[1]
+            margin_rule = (not is_horizontal and np.ptp(yy) > image.shape[0]*.7
+                and (np.median(xx) < image.shape[1]*.3 or np.median(xx) > image.shape[1]*.7))
+            if spread < axis_size*.35 and not margin_rule:
+                continue
+            # An isolated long fraction bar must not define its own paper colour.
+            # The upper quantile admits darker major rules within an established
+            # family while rejecting excess ink on most of its pixels.
+            ceiling = np.floor(np.quantile(dark[selected],.99,axis=0)+25).astype(np.int16)
+            credible |= ((classes == colour)
+                         & (_maximum(dark16-ceiling) <= 0))
+        match = close & credible & (darkness > 9) & ~thick
+        removed |= support & match
+        protected |= support & ~match & (binary > 0)
+
+    inverse = cv2.invertAffineTransform(matrix)
+    result = cv2.warpAffine(removed.astype(np.uint8), inverse,
+                           (width,height), flags=cv2.INTER_LINEAR) > 0
+    guard = cv2.warpAffine(protected.astype(np.uint8), inverse,
+                          (width,height), flags=cv2.INTER_LINEAR) > 0
+    # Cover one-pixel deskew/interpolation remnants, except next to writing that
+    # failed the paper test. Confirmed pixels of the other orientation remain
+    # removable at line crossings.
+    kernel = np.ones((3,3), np.uint8)
+    result |= ((cv2.dilate(result.astype(np.uint8),kernel) > 0)
+               & ~(cv2.dilate(guard.astype(np.uint8),kernel) > 0))
+    return result, dict(ruling_cleanup=True, ruling_angle_deg=round(angle,3),
+                       ruling_horizontal_lines=nh, ruling_vertical_lines=nv)

copienator_gui/app.py

@@ -30,6 +30,7 @@ from .scores import ScoreEditorPanel
 from .notifications import notify_desktop
 from .syncthing import SyncthingPanel
 from .manual_resolution import ManualResolutionPanel
+from .recorrection import prepare_selection_file
 from .refaire import SECTION as REFAIRE_SECTION
 from .refaire import (
     RefaireSelection,
@@ -930,6 +931,14 @@ class CopienatorApp(tk.Tk):
             self.arg_vars['target'].trace_add('write', lambda *_args: self._refresh_persp_inventory())
             self._refresh_persp_inventory()
 
+        if step.id == "prepare_recorrection":
+            self.edit_recorrection_button = ttk.Button(
+                self.form, text="Ouvrir refaire.json (avec exemples)",
+                command=self._edit_recorrection,
+            )
+            self.edit_recorrection_button.grid(row=row, column=0, columnspan=2, sticky="w", pady=8)
+            row += 1
+
         if step.id == "manual_resolution":
             def manual_evaluation():
                 target = self.arg_vars.get("target")
@@ -1117,6 +1126,7 @@ class CopienatorApp(tk.Tk):
             "cutleft",
             "labels",
             "plotting",
+            "splitting",
         }
         if step.id in copy_selection_steps:
             evaluation = self.evaluation
@@ -1310,6 +1320,16 @@ class CopienatorApp(tk.Tk):
         except (OSError, RuntimeError) as exc:
             messagebox.showerror("Ouverture impossible", str(exc))
 
+    def _edit_recorrection(self) -> None:
+        if self.evaluation is None:
+            return
+        try:
+            path = prepare_selection_file(self.evaluation)
+        except OSError as exc:
+            messagebox.showerror("Préparation impossible", str(exc))
+            return
+        self._open_desktop_path(path, "fichier refaire.json")
+
     def _select_variant(self, index: int) -> None:
         if not self.current_step or index < 0:
             return
@@ -1546,6 +1566,15 @@ class CopienatorApp(tk.Tk):
         if step.id == "refaire_selection":
             self._save_refaire_selection()
             return
+        if step.id == "prepare_recorrection":
+            try:
+                load_selection(evaluation)
+            except (OSError, ValueError, TypeError) as exc:
+                messagebox.showerror("Sélection à vérifier", str(exc))
+                return
+            self._mark_step("success")
+            self._select_refaire_correction()
+            return
         if step.section == REFAIRE_SECTION:
             try:
                 self._refaire_selection()

copienator_gui/recorrection.py

@@ -0,0 +1,25 @@
+"""Editable examples for the optional correction redo step."""
+
+from pathlib import Path
+
+from copienator import atomic_write_text
+
+
+EXAMPLES = """// Exemples de sélection pour refaire la correction
+// Les lignes commençant par // sont des commentaires et sont ignorées.
+// Modifiez la liste JSON ci-dessous, puis enregistrez le fichier.
+// Une copie entière : [["Copie46", []]]
+// Certaines questions : [["Copie46", ["II)8)", "II)9)"]]
+// Plusieurs copies : [["Copie46", []], ["Copie03", ["Ex 1"]]]
+// Utilisez les noms exacts des copies et des labels de votre évaluation.
+// [] après une copie signifie toutes ses questions ; [] seul ne sélectionne rien.
+// Séparez les entrées par des virgules, sans virgule après la dernière.
+"""
+
+
+def prepare_selection_file(evaluation: Path) -> Path:
+    path = evaluation / "refaire.json"
+    existing = path.read_text(encoding="utf-8") if path.exists() else "[]\n"
+    if not existing.startswith(EXAMPLES):
+        atomic_write_text(path, EXAMPLES + existing)
+    return path

copienator_gui/workflow.py

@@ -371,12 +371,12 @@ def build_workflow(show_personal_steps: bool) -> list[StepDefinition]:
             "splitting",
             "Labels et regroupement",
             "Découper les réponses par question",
-            "Découpe les copies à partir des coordonnées de labels vérifiées.",
+            "Découpe les copies à partir des coordonnées de labels vérifiées. "
+            "Ciblez une copie avec le sélecteur ou tout le dossier, puis cliquez sur Exécuter.",
             (python("default", "Découpage", "split-answers"),),
             arguments=(arg_target(),),
             requires=("Copies",),
             artifacts=("Copies/Copie*/*",),
-            auto_start_first_visit=True,
         ),
         StepDefinition(
             "crop_exercise_bottoms",
@@ -511,6 +511,19 @@ def build_workflow(show_personal_steps: bool) -> list[StepDefinition]:
             requires=("manual_resolutions.txt", "correction.json"),
             skip_without_manual_conflicts=True,
         ),
+        StepDefinition(
+            "prepare_recorrection",
+            "Correction",
+            "Choisir des copies à recorriger",
+            "Facultatif : ouvrez refaire.json et indiquez les copies entières ou les questions à recorriger. "
+            "Les exemples commentés expliquent la syntaxe. Enregistrez le fichier, puis marquez cette étape terminée : "
+            "vous reviendrez à Correction avec --refaire sélectionné, sans lancement automatique. "
+            "Les corrections sélectionnées seront remplacées ; celles des autres copies seront conservées. "
+            "Si vous avez modifié les découpes, régénérez les réponses avant la recorrection. "
+            "Ignorez cette étape si aucune reprise n’est nécessaire.",
+            (manual("default"),),
+            optional=True,
+        ),
         StepDefinition(
             "post_correction",
             "Correction",

docs/guide_utilisateur_gui.md

@@ -251,6 +251,31 @@ coupure, et quelle moitié doit être gardée. L'interface graphique vous
 fournira alors une instruction texte à copier et à mettre dans le
 fichier texte.
 
+Vous pouvez aussi ajouter vos propres instructions dans
+`manual_resolutions.txt`, même si Gemini n’a pas signalé ces conflits.
+Les lignes sont appliquées **de haut en bas**, avec une distinction importante :
+
+- La **source** est toujours le PDF tel qu’il existait au début de cette
+  exécution, avant les modifications des lignes précédentes.
+- La **cible** est sa version courante, tenant compte des lignes précédentes.
+
+Par exemple, pour une copie ayant les labels `A`, `B` et `C` :
+
+```text
+Copie46 A c{40}1> B|
+Copie46 C -> A|
+```
+
+La première ligne coupe A à 40 % de sa hauteur cumulée, conserve la première
+partie sous le label A et ajoute les 60 % restants après B. La seconde ligne
+ajoute C après **la partie conservée de A**, et non après A entier. C reste
+également disponible sous son propre label.
+
+En revanche, si une ligne ultérieure utilise **A comme source**, elle utilise
+le PDF A entier du début de l’exécution, pas seulement sa partie conservée.
+Une seule coupe par label source et par copie est autorisée dans une même
+exécution. Remplacez `A`, `B` et `C` par les labels exacts de votre évaluation.
+
 Enregistrez le fichier texte, éventuellement le **Recharger**, puis
 **Exécuter**.
 

tests/test_annotation_latex_errors.py

@@ -0,0 +1,58 @@
+import tempfile
+import unittest
+from pathlib import Path
+from subprocess import CompletedProcess
+from unittest.mock import Mock, patch
+
+from PIL import Image
+
+from copienator.commands import annotating
+
+
+class AnnotationLatexErrorTests(unittest.TestCase):
+    def test_failure_preserves_source_and_log_and_explains_recovery(self):
+        with tempfile.TemporaryDirectory() as directory:
+            diagnostics = Path(directory) / "diagnostics"
+            diagnostics.mkdir()
+
+            def compile_latex(command, **kwargs):
+                Path(kwargs["cwd"], "text.log").write_bytes(
+                    b"preamble\n! Missing \\endcsname inserted.\nl.12 \\end{document}\n\xff"
+                )
+                return CompletedProcess(command, 1, stdout=b"compiler output\xff")
+
+            # Patch only the retained diagnostics directory, not TemporaryDirectory.
+            original_mkdtemp = tempfile.mkdtemp
+
+            def make_directory(*args, **kwargs):
+                if kwargs.get("prefix") == "copienator-latex-error-":
+                    return str(diagnostics)
+                return original_mkdtemp(*args, **kwargs)
+
+            with patch.object(annotating.subprocess, "run", side_effect=compile_latex), patch.object(
+                annotating.tempfile, "mkdtemp", side_effect=make_directory
+            ):
+                with self.assertRaises(annotating.AnnotationLatexError) as caught:
+                    annotating.render_real_latex_text(r"Antislash \.", 400)
+            message = str(caught.exception)
+            for expected in ("code 1", r"Antislash \.", "Missing", "correction.json", "relancez cette étape", str(diagnostics)):
+                self.assertIn(expected, message)
+            self.assertIn(r"Antislash \.", (diagnostics / "text.tex").read_text())
+            self.assertTrue((diagnostics / "text.log").exists())
+            self.assertTrue((diagnostics / "compiler-output.txt").exists())
+
+    def test_comment_error_identifies_copy_label_and_correction_file(self):
+        for box in (None, [0, 0, 20, 20]):
+            with self.subTest(box=box), patch.object(
+                annotating, "render_score_text", return_value=Image.new("RGBA", (200, 40))
+            ):
+                with self.assertRaises(annotating.AnnotationLatexError) as caught:
+                    annotating.compose_label_image(
+                        Image.new("RGB", (800, 200)), "I)7)",
+                        {"feedback": [{"text": "Bad comment", "box_2d": box}]}, 0,
+                        render_fn=Mock(side_effect=annotating.AnnotationLatexError("Bad comment")),
+                        source_pdf=Path("/exam/Copies/Copie39/I)7).pdf"),
+                    )
+                message = str(caught.exception)
+                for expected in ("Copie39", "I)7)", "/exam/correction.json", "Bad comment"):
+                    self.assertIn(expected, message)

tests/test_crop_diagnostics.py

@@ -0,0 +1,118 @@
+import json
+import tempfile
+import unittest
+from pathlib import Path
+
+import cv2
+import numpy as np
+from PIL import Image
+
+from copienator.crop_diagnostics import check_protected_regions, save_diagnostics
+from copienator.ink_detection import detect_bounds
+
+
+class CropDiagnosticsTests(unittest.TestCase):
+    def scan(self, *, dark=False, skew=False):
+        rgb = np.full((900,650,3),255,np.uint8)
+        if dark:
+            for y in range(15,900,20):
+                cv2.line(rgb,(0,y),(649,y),(65,65,65),1)
+            for x in range(10,650,20):
+                cv2.line(rgb,(x,0),(x,899),(65,65,65),1)
+        cv2.putText(rgb,'answer',(100,400),cv2.FONT_HERSHEY_SIMPLEX,1,(20,50,180),2)
+        cv2.putText(rgb,'more',(100,560),cv2.FONT_HERSHEY_SIMPLEX,.8,(30,30,30),2)
+        if skew:
+            rgb = cv2.warpAffine(rgb,cv2.getRotationMatrix2D((325,450),2,1),
+                                (650,900),borderValue=(255,255,255))
+        return rgb
+
+    def test_diagnostics_leave_decisions_and_json_contract_unchanged(self):
+        for dark,skew in [(False,False),(True,False),(True,True)]:
+            with self.subTest(dark=dark,skew=skew):
+                rgb = self.scan(dark=dark,skew=skew)
+                before = rgb.copy()
+                normal = detect_bounds(rgb,dpi=150)
+                debug = {'stale': 'discard this'}
+                observed = detect_bounds(rgb,dpi=150,diagnostics=debug)
+                self.assertEqual(normal,observed)
+                json.dumps(observed)
+                np.testing.assert_array_equal(rgb,before)
+                self.assertNotIn('stale',debug)
+                for name,mask in debug['masks'].items():
+                    self.assertEqual(mask.shape,rgb.shape[:2],name)
+                    self.assertEqual(mask.dtype,np.bool_,name)
+                masks = debug['masks']
+                self.assertFalse(np.any(masks['strong_seeds'] & ~masks['foreground']))
+                self.assertFalse(np.any(masks['recovered_weak'] & masks['strong_seeds']))
+                for item in debug['thresholds']:
+                    for edge in ['top','bottom']:
+                        for component in item['limiting_components'][edge]:
+                            box = component['bbox_px']
+                            self.assertEqual(box[1] if edge=='top' else box[3],
+                                             item['extent'][0 if edge=='top' else 1])
+                            self.assertGreater(component['seed_pixels'],0)
+
+    def test_blank_fallback_has_empty_foreground_and_explanation(self):
+        rgb = np.full((400,300,3),255,np.uint8)
+        debug = {}
+        result = detect_bounds(rgb,diagnostics=debug)
+        self.assertEqual((result['top_px'],result['bottom_px']),(0,400))
+        self.assertFalse(debug['masks']['foreground'].any())
+        self.assertEqual(debug['edges']['bottom']['reason'],'no-reliable-ink-seeds')
+
+    def test_faint_unseeded_candidate_is_distinguished_from_recovered_ink(self):
+        rgb = self.scan()
+        cv2.putText(rgb,'weak',(100,800),cv2.FONT_HERSHEY_SIMPLEX,1,(130,160,205),2)
+        debug = {}
+        detect_bounds(rgb,dpi=150,diagnostics=debug)
+        self.assertTrue(debug['masks']['unretained_weak'][770:810,100:220].any())
+        self.assertFalse(debug['masks']['foreground'][770:810,100:220].any())
+
+    def test_exported_masks_match_actual_pixels_and_report_is_serializable(self):
+        rgb = self.scan(dark=True,skew=True)
+        debug = {}
+        result = detect_bounds(rgb,dpi=150,diagnostics=debug)
+        with tempfile.TemporaryDirectory() as tmp:
+            files = save_diagnostics(rgb,result,debug,Path(tmp),width_mm=110,height_mm=152)
+            for name,path in files['masks'].items():
+                with Image.open(Path(tmp)/path) as im:
+                    np.testing.assert_array_equal(np.array(im).astype(bool),debug['masks'][name])
+            report = json.loads((Path(tmp)/files['report']).read_text())
+            self.assertEqual(report['detector'],result)
+            self.assertEqual(report['shape'],list(rgb.shape[:2]))
+            for path in files['overlays'].values():
+                self.assertTrue((Path(tmp)/path).is_file())
+
+
+class ProtectedContentTests(unittest.TestCase):
+    def check(self,top,bottom,box):
+        return check_protected_regions([dict(id='ink',label='Real ink',bbox_mm=box)],
+            dict(top_px=top,bottom_px=bottom),width_mm=80,height_mm=100,shape=(1000,800))[0]
+
+    def test_both_boundaries_can_clip_a_protected_region(self):
+        top = self.check(210,800,[10,20,50,30])
+        self.assertFalse(top['passed'])
+        self.assertEqual(top['clipped_edges'],['top'])
+        self.assertAlmostEqual(top['clipped_area_fraction'],.1)
+        bottom = self.check(100,790,[10,70,50,80])
+        self.assertFalse(bottom['passed'])
+        self.assertEqual(bottom['clipped_edges'],['bottom'])
+        self.assertAlmostEqual(bottom['clipped_area_fraction'],.1)
+
+    def test_contact_at_boundary_and_short_page_physical_height(self):
+        self.assertTrue(self.check(200,300,[10,20,50,30])['passed'])
+        row = check_protected_regions([dict(id='end',label='End',bbox_mm=[2,17,20,19])],
+            dict(top_px=0,bottom_px=180),width_mm=40,height_mm=20,shape=(200,400))[0]
+        self.assertFalse(row['passed'])
+        self.assertAlmostEqual(row['clipped_area_fraction'],.5)
+
+    def test_full_removal_and_invalid_ground_truth(self):
+        self.assertEqual(self.check(400,800,[10,20,50,30])['clipped_area_fraction'],1)
+        with self.assertRaises(ValueError):
+            self.check(0,1000,[10,20,90,30])
+        with self.assertRaises(ValueError):
+            self.check(0,1000,[10,30,50,20])
+
+
+if __name__ == '__main__':
+    unittest.main()

tests/test_crop_exercise_bottoms.py

@@ -20,7 +20,7 @@ class CropExerciseBottomsTests(unittest.TestCase):
             page = document.new_page(width=600, height=height)
             page.insert_text((80, text_y), "student answer", fontsize=16)
             if footer:
-                page.insert_text((20, height - 3), "Ex 2", fontsize=10)
+                page.insert_text((20, height - 15), "9/9", fontsize=10)
             document.save(path)
         return path
 
@@ -33,7 +33,7 @@ class CropExerciseBottomsTests(unittest.TestCase):
         self.assertEqual(records[0]["status"], "skipped-short")
         self.assertFalse(destination.exists())
 
-    def test_footer_fragment_is_ignored_for_a_large_bottom_crop(self):
+    def test_isolated_page_number_allows_a_large_bottom_crop(self):
         source = self.make_pdf("large.pdf", 400, 100)
         destination = self.root / "out" / source.name
         records = process_exercise_pdf(
@@ -45,6 +45,18 @@ class CropExerciseBottomsTests(unittest.TestCase):
             self.assertLess(result[0].rect.height, 250)
             self.assertAlmostEqual(result[0].rect.width, 600)
 
+    def test_content_in_former_ignored_bottom_strip_is_retained(self):
+        source = self.make_pdf("bottom-content.pdf", 400, 100, footer=False)
+        with pymupdf.open(source) as doc:
+            doc[0].insert_text((20, 399), "Ex 2", fontsize=10)
+            doc.save(self.root / "bottom-label.pdf")
+        records = process_exercise_pdf(
+            self.root / "bottom-label.pdf", self.root / "retained.pdf",
+            self.review, 800, dpi=150
+        )
+        self.assertEqual(records[0]["status"], "unchanged-small-crop")
+        self.assertFalse((self.root / "retained.pdf").exists())
+
     def test_crop_smaller_than_four_lines_is_not_written(self):
         source = self.make_pdf("small.pdf", 400, 330, footer=False)
         destination = self.root / "out" / source.name

tests/test_edge_marks.py

@@ -0,0 +1,58 @@
+import unittest
+
+import cv2
+import numpy as np
+
+from copienator.ink_detection import detect_bounds
+
+
+class EdgeMarksTests(unittest.TestCase):
+    def page(self, last_answer=1000):
+        rgb = np.full((2340,1654,3),255,np.uint8)
+        cv2.putText(rgb,'answer',(500,600),cv2.FONT_HERSHEY_SIMPLEX,1.5,(20,60,180),2)
+        cv2.putText(rgb,'more',(500,last_answer),cv2.FONT_HERSHEY_SIMPLEX,1.5,(20,60,180),2)
+        return rgb
+
+    def test_isolated_footer_fraction_is_removed(self):
+        rgb=self.page()
+        cv2.putText(rgb,'9/9',(1400,2220),cv2.FONT_HERSHEY_SIMPLEX,1.2,(20,20,20),2)
+        debug={}
+        result=detect_bounds(rgb,diagnostics=debug)
+        self.assertLess(result['bottom_px'],1100)
+        self.assertTrue(debug['masks']['isolated_edge_marks'].any())
+        self.assertFalse(debug['masks']['foreground'][2150:].any())
+        self.assertFalse(debug['masks']['strong_seeds'][2150:].any())
+        self.assertEqual(result,detect_bounds(rgb))
+
+    def test_close_footer_stays_with_answer(self):
+        rgb=self.page(last_answer=2170)
+        cv2.putText(rgb,'9/9',(1400,2220),cv2.FONT_HERSHEY_SIMPLEX,1.2,(20,20,20),2)
+        self.assertGreater(detect_bounds(rgb)['bottom_px'],2220)
+
+    def test_central_sparse_ratio_stays(self):
+        rgb=self.page()
+        cv2.putText(rgb,'9/9',(760,2220),cv2.FONT_HERSHEY_SIMPLEX,1.2,(20,20,20),2)
+        self.assertGreater(detect_bounds(rgb)['bottom_px'],2220)
+
+    def test_isolated_bare_border_digit_needs_no_recognition(self):
+        rgb=self.page()
+        cv2.putText(rgb,'7',(1400,2240),cv2.FONT_HERSHEY_SIMPLEX,1.2,(20,20,20),2)
+        self.assertLess(detect_bounds(rgb)['bottom_px'],1100)
+
+    def test_underlined_question_at_upper_edge_stays(self):
+        rgb=self.page()
+        cv2.putText(rgb,'16',(310,85),cv2.FONT_HERSHEY_SIMPLEX,1.2,(20,20,20),2)
+        cv2.line(rgb,(310,90),(355,90),(20,20,20),2)
+        self.assertLess(detect_bounds(rgb)['top_px'],60)
+
+    def test_name_in_other_margin_blocks_header_removal(self):
+        rgb=self.page()
+        cv2.circle(rgb,(90,55),22,(20,20,20),2)
+        cv2.putText(rgb,'1',(81,64),cv2.FONT_HERSHEY_SIMPLEX,.7,(20,20,20),1)
+        cv2.putText(rgb,'Name',(1350,120),cv2.FONT_HERSHEY_SIMPLEX,1,(20,20,20),2)
+        result=detect_bounds(rgb)
+        self.assertEqual(result['top_px'],0)
+
+
+if __name__=='__main__':
+    unittest.main()

tests/test_gui_convenience.py

@@ -214,6 +214,49 @@ class GuiConvenienceTests(unittest.TestCase):
         self.assertNotIn("overwrite", self.app.arg_vars)
         self.assertIn("--refaire", self.app._make_command())
 
+    def test_optional_recorrection_opens_examples_and_returns_to_correction(self):
+        from copienator import read_json
+        ids = [step.id for step in self.app.steps]
+        self.assertEqual(ids[ids.index("manual_resolution") + 1], "prepare_recorrection")
+        copies = self.evaluation / "Copies"
+        copies.mkdir()
+        (copies / "Copie46.pdf").touch()
+        (self.evaluation / "labels").write_text("II)9)\n")
+        self.app.tree.selection_set("prepare_recorrection")
+        self.app.update()
+        with patch("copienator_gui.app.open_path") as opened:
+            self.app.edit_recorrection_button.invoke()
+        path = self.evaluation / "refaire.json"
+        opened.assert_called_once_with(path)
+        self.assertEqual(read_json(path), [])
+        path.write_text(path.read_text().replace("\n[]\n", '\n[["Copie46", []]]\n'))
+        with patch.object(self.app.runner, "start") as start:
+            self.app.run_button.invoke()
+            self.app.update()
+        start.assert_not_called()
+        self.assertEqual(self.app.state_store.step("prepare_recorrection")["status"], "success")
+        self.assertEqual(self.app.current_step.id, "correction")
+        self.assertEqual(self.app.variant_var.get(), "refaire")
+        self.assertIn("--refaire", self.app._make_command())
+        self.assertNotIn("--overwrite", self.app._make_command())
+
+    def test_ignoring_optional_recorrection_continues_without_creating_file(self):
+        self.app.tree.selection_set("prepare_recorrection")
+        self.app.update()
+        self.app._skip_step()
+        self.app.update()
+        self.assertEqual(self.app.current_step.id, "post_correction")
+        self.assertEqual(self.app.state_store.step("prepare_recorrection")["status"], "skipped")
+        self.assertFalse((self.evaluation / "refaire.json").exists())
+
+    def test_optional_recorrection_requires_a_saved_selection(self):
+        self.app.tree.selection_set("prepare_recorrection")
+        self.app.update()
+        with patch("copienator_gui.app.messagebox.showerror") as error:
+            self.app.run_button.invoke()
+        error.assert_called_once()
+        self.assertEqual(self.app.current_step.id, "prepare_recorrection")
+
     def test_giving_names_waits_for_explicit_manual_completion(self):
         return_dir = self.evaluation / "A Rendre" / "Student (01)"
         return_dir.mkdir(parents=True)
@@ -560,6 +603,25 @@ class GuiConvenienceTests(unittest.TestCase):
         self.assertIn("Cibler la copie sélectionnée", controls)
         self.assertIn("Cibler tout le dossier", controls)
 
+    def test_answer_splitting_waits_for_target_and_can_select_one_copy(self):
+        copies = self.evaluation / "Copies"
+        copies.mkdir()
+        for name in ("Copie01.pdf", "Copie46.pdf"):
+            (copies / name).touch()
+        with patch.object(self.app, "_run_current_step") as run:
+            self.app.tree.selection_set("splitting")
+            self.app.update()
+            run.assert_not_called()
+        self.assertIn("Copie46.pdf", self.app.copy_paths)
+        self.app.copy_var.set("Copie46.pdf")
+        self.app._target_selected_copy()
+        command = self.app._make_command()
+        self.assertIn("split-answers", command)
+        self.assertEqual(Path(command[5]), copies / "Copie46.pdf")
+        self.app._target_all_pages()
+        command = self.app._make_command()
+        self.assertEqual((self.repository / command[5]).resolve(), self.evaluation)
+
     def test_label_review_can_show_and_target_one_copy(self):
         copies = self.evaluation / "Copies"
         copies.mkdir()

tests/test_gui_core.py

@@ -2378,7 +2378,7 @@ class WorkflowTests(unittest.TestCase):
 
         self.assertEqual(
             auto_start,
-            {"crop_blank_margins", "splitting", "crop_exercise_bottoms", "grouping"},
+            {"crop_blank_margins", "crop_exercise_bottoms", "grouping"},
         )
         self.assertEqual(
             skip_for_live, {"submit_batches", "batch_status", "fetch_batches"}

tests/test_paper_ruling.py

@@ -0,0 +1,87 @@
+import unittest
+from unittest.mock import patch
+
+import cv2
+import numpy as np
+
+from copienator.ink_detection import detect_bounds
+
+
+class PaperRulingTests(unittest.TestCase):
+    def scan(self, colour, *, warp=False):
+        image = np.full((1200, 850, 3), 255, np.uint8)
+        for y in range(20, 1200, 20):
+            cv2.line(image, (0, y), (849, y), colour, 1)
+        for x in range(10, 850, 20):
+            cv2.line(image, (x, 0), (x, 1199), colour, 1)
+        cv2.line(image, (80, 0), (80, 1199), (210, 70, 80), 2)
+        cv2.putText(image, 'answer', (120, 410), cv2.FONT_HERSHEY_SIMPLEX,
+                    1, (20, 60, 180), 2)
+        cv2.putText(image, 'more', (120, 710), cv2.FONT_HERSHEY_SIMPLEX,
+                    1, (20, 60, 180), 2)
+        if warp:
+            yy, xx = np.indices(image.shape[:2], dtype=np.float32)
+            image = cv2.remap(image, xx+2*np.sin(yy/95), yy,
+                              cv2.INTER_LINEAR, borderValue=(255,255,255))
+        return image
+
+    def test_default_path_does_not_run_experimental_colour_model(self):
+        image = self.scan((70, 110, 225))
+        with patch('copienator.ink_detection.ruling_suppression',
+                   side_effect=AssertionError('Expensive colour model invoked')):
+            result = detect_bounds(image, dpi=150)
+        self.assertLess(result['top_px'], 410)
+        self.assertGreater(result['bottom_px'], 710)
+        self.assertFalse(result.get('ruling_cleanup', False))
+
+    def test_saturated_coloured_grid_and_margin_do_not_seed_blank_edges(self):
+        for colour in [(65, 65, 65), (70, 110, 225), (155, 170, 240)]:
+            for warp in [False, True]:
+                with self.subTest(colour=colour, warp=warp):
+                    image = self.scan(colour, warp=warp)
+                    debug = {}
+                    result = detect_bounds(image, dpi=150, colour_cleanup=True, diagnostics=debug)
+                    self.assertGreater(result['top_px'], 280)
+                    self.assertLess(result['bottom_px'], 810)
+                    self.assertTrue(result['ruling_cleanup'])
+                    self.assertTrue(debug['masks']['paper_suppressed'].any())
+                    self.assertFalse(debug['masks']['foreground'][:250].any())
+
+    def test_writing_crossing_ruling_keeps_both_outer_bounds(self):
+        image = self.scan((70, 110, 225))
+        cv2.putText(image, 'top', (120, 200), cv2.FONT_HERSHEY_SIMPLEX,
+                    .7, (190, 20, 20), 2)
+        cv2.putText(image, 'bottom', (120, 1000), cv2.FONT_HERSHEY_SIMPLEX,
+                    .7, (20, 20, 20), 2)
+        result = detect_bounds(image, dpi=150, colour_cleanup=True)
+        self.assertLess(result['top_px'], 180)
+        self.assertGreater(result['bottom_px'], 1000)
+
+    def test_isolated_bars_and_axes_are_not_a_ruling_colour_family(self):
+        for colour in [(190, 20, 20), (20, 20, 20), (20, 90, 190)]:
+            with self.subTest(colour=colour):
+                image = self.scan((70, 110, 225))
+                cv2.line(image, (100, 1020), (700, 1020), colour, 3)
+                cv2.line(image, (425, 980), (425, 1120), colour, 3)
+                result = detect_bounds(image, dpi=150, colour_cleanup=True)
+                self.assertGreater(result['bottom_px'], 1120)
+
+    def test_grid_colour_with_a_thicker_answer_bar_is_preserved(self):
+        colour = (70, 110, 225)
+        image = self.scan(colour)
+        cv2.line(image, (150, 1020), (650, 1020), colour, 5)
+        self.assertGreater(detect_bounds(image, dpi=150, colour_cleanup=True)['bottom_px'], 1020)
+
+    def test_regular_fraction_bars_inside_an_answer_are_not_paper(self):
+        image = np.full((1200,850,3),255,np.uint8)
+        cv2.putText(image,'answer',(120,300),cv2.FONT_HERSHEY_SIMPLEX,
+                    1,(20,60,180),2)
+        for y in (400,550,700,850,1000):
+            cv2.line(image,(130,y),(700,y),(20,20,20),3)
+        result = detect_bounds(image,dpi=150, colour_cleanup=True)
+        self.assertGreater(result['bottom_px'],1000)
+        self.assertFalse(result.get('ruling_cleanup',False))
+
+
+if __name__ == '__main__':
+    unittest.main()

tests/test_recorrection_file.py

@@ -0,0 +1,34 @@
+import json
+import tempfile
+import unittest
+from pathlib import Path
+
+from copienator import read_json
+from copienator_gui.recorrection import prepare_selection_file
+
+
+class RecorrectionFileTests(unittest.TestCase):
+    def test_examples_are_inactive_and_opening_preserves_selection(self):
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            path = prepare_selection_file(root)
+            self.assertEqual(read_json(path), [])
+            self.assertIn('// Une copie entière', path.read_text())
+            selection = [["Copie46", ["II)9)"]]]
+            path.write_text(json.dumps(selection))
+            prepare_selection_file(root)
+            self.assertEqual(read_json(path), selection)
+            before = path.read_bytes()
+            prepare_selection_file(root)
+            self.assertEqual(path.read_bytes(), before)
+
+    def test_comments_do_not_affect_strings_or_other_json_files(self):
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            path = root / "refaire.json"
+            path.write_text('// Example\n[["Copie01", ["a//b"]]]\n')
+            self.assertEqual(read_json(path), [["Copie01", ["a//b"]]])
+            other = root / "correction.json"
+            other.write_text(path.read_text())
+            with self.assertRaises(json.JSONDecodeError):
+                read_json(other)