Update faceless_processing.py

faceless_processing.py

@@ -61,14 +61,15 @@ class LineartConfig:
     silhouette_line_thickness: int = 4   # outer contour stroke width (px); match interior for uniform look
 
     # Edge detection
-    canny_low: int = 40
+    canny_low: int = 25               # lower = more body detail captured
     canny_high: int = 110
     bilateral_d: int = 11
     bilateral_sigma_color: int = 80
     bilateral_sigma_space: int = 80
     gaussian_ksize: int = 9
-    min_contour_perimeter: float = 50.0    # filters out short noisy lines
+    min_contour_perimeter: float = 30.0    # filters out short noisy lines
     interior_line_thickness: int = 3        # thickness of interior detail lines (>=1)
+    cluster_merge_radius: int = 5           # radius (px) to merge nearby parallel lines into one
 
     # Face detection
     face_scale_factor: float = 1.05
@@ -188,23 +189,33 @@ def build_face_erase_mask(faces: list, shape: Tuple[int, int], cfg: LineartConfi
 
 
 def build_interior_edges(rgb: np.ndarray, subject_mask: np.ndarray, cfg: LineartConfig) -> np.ndarray:
-    """Detect structural body lines using Canny, filtering noise."""
+    """Detect structural body lines, capturing more detail then summarising clustered strokes."""
     gray = cv2.cvtColor(rgb, cv2.COLOR_RGB2GRAY)
     blurred = cv2.GaussianBlur(gray, (cfg.gaussian_ksize, cfg.gaussian_ksize), 0)
     blurred = cv2.bilateralFilter(blurred, cfg.bilateral_d, cfg.bilateral_sigma_color, cfg.bilateral_sigma_space)
     edges = cv2.Canny(blurred, cfg.canny_low, cfg.canny_high)
     edges = cv2.bitwise_and(edges, subject_mask)
 
-    # Filter out short/noisy contours
+    # Step 1: draw all edges that pass the length filter
     contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
-    filtered = np.zeros_like(edges)
+    raw = np.zeros_like(edges)
     for cnt in contours:
+        if cv2.arcLength(cnt, False) > cfg.min_contour_perimeter:
+            cv2.drawContours(raw, [cnt], -1, 255, 1)
+
+    # Step 2: merge nearby parallel lines into single strokes
+    r = cfg.cluster_merge_radius
+    k_merge = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (r * 2 + 1, r * 2 + 1))
+    merged = cv2.morphologyEx(raw, cv2.MORPH_CLOSE, k_merge)   # join close lines
+    merged = cv2.erode(merged, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (r, r)), iterations=1)  # thin back
+
+    # Step 3: redraw surviving contours with final thickness for clean uniform strokes
+    contours2, _ = cv2.findContours(merged, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
+    filtered = np.zeros_like(edges)
+    for cnt in contours2:
         if cv2.arcLength(cnt, False) > cfg.min_contour_perimeter:
             cv2.drawContours(filtered, [cnt], -1, 255, cfg.interior_line_thickness)
 
-    # Mild dilation for uniform, solid strokes
-    kernel_dilate = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
-    filtered = cv2.dilate(filtered, kernel_dilate, iterations=1)
     return filtered