678ghjkjh.py

678ghjkjh.py

import cv2
import numpy as np
from pathlib import Path


def detect_underline_by_vertical_context(img, low=150, high=220, bg_thresh=220, check_dist=3):
    """
    Detectează subliniere bazat pe context vertical.

    Un pixel e subliniere dacă:
    1. E în zona gri (low-high)
    2. Pixelii de DEASUPRA sunt fundal (>bg_thresh)
    3. Pixelii de DEDESUBT sunt fundal (>bg_thresh)

    Textul NU îndeplinește condițiile 2 și 3 (are alte litere în jur).
    """
    h, w = img.shape

    # Zona gri
    in_gray_zone = (img >= low) & (img < high)

    # Media pixelilor de deasupra
    above_mean = np.zeros_like(img, dtype=np.float32)
    for d in range(1, check_dist + 1):
        shifted = np.roll(img, d, axis=0)
        shifted[:d, :] = 255
        above_mean += shifted
    above_mean /= check_dist

    # Media pixelilor de dedesubt
    below_mean = np.zeros_like(img, dtype=np.float32)
    for d in range(1, check_dist + 1):
        shifted = np.roll(img, -d, axis=0)
        shifted[-d:, :] = 255
        below_mean += shifted
    below_mean /= check_dist

    # Condiții
    above_is_bg = above_mean > bg_thresh
    below_is_bg = below_mean > bg_thresh

    # Subliniere = în zona gri + fundal sus + fundal jos
    underline_mask = in_gray_zone & above_is_bg & below_is_bg

    return underline_mask.astype(np.uint8) * 255


def generate_variants(image_path, output_dir):
    """Generează variante cu detectare bazată pe context vertical"""
    img = cv2.imread(str(image_path))
    if img is None:
        raise ValueError(f"Nu s-a putut încărca: {image_path}")

    p = Path(image_path)
    output_dir = Path(output_dir)
    output_dir.mkdir(parents=True, exist_ok=True)

    # Desaturare completă
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    h, s, v = cv2.split(hsv)
    s_zero = np.zeros_like(s)
    hsv_desat = cv2.merge([h, s_zero, v])
    img_gray = cv2.cvtColor(hsv_desat, cv2.COLOR_HSV2BGR)
    gray = cv2.cvtColor(img_gray, cv2.COLOR_BGR2GRAY)

    # Gamma correction
    gamma = 3.0
    inv_gamma = 1.0 / gamma
    table = np.array([((i / 255.0) ** inv_gamma) * 255 for i in range(256)]).astype("uint8")
    gc = cv2.LUT(gray, table)

    # Configurații: (nume, low, high, bg_thresh, check_dist)
    configs = [
        ("vc1_150_220_bg220_d3", 150, 220, 220, 3),
        ("vc2_150_220_bg215_d3", 150, 220, 215, 3),
        ("vc3_155_215_bg220_d2", 155, 215, 220, 2),
        ("vc4_160_210_bg220_d4", 160, 210, 220, 4),
        ("vc5_150_220_bg210_d5", 150, 220, 210, 5),
        ("vc6_145_225_bg215_d3", 145, 225, 215, 3),
    ]

    for name, low, high, bg_thresh, dist in configs:
        mask = detect_underline_by_vertical_context(gc, low, high, bg_thresh, dist)

        # Aplicăm masca
        result = gc.copy()
        result[mask > 0] = 245

        # Binarizare
        blur = cv2.GaussianBlur(result, (3, 3), 0)
        binary = cv2.adaptiveThreshold(blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                        cv2.THRESH_BINARY, 25, 12)

        out_path = output_dir / f"{p.stem}_{name}{p.suffix}"
        cv2.imwrite(str(out_path), binary)
        print(f"Salvat: {out_path}  (low={low}, high={high}, bg={bg_thresh}, dist={dist})")


# ========== CONFIGURARE ==========
IMAGE_PATH = r"d:\imagine_noua.jpg"
OUTPUT_DIR = r"d:\output"
# =================================


if __name__ == "__main__":
    print("Eliminare sublinieri - Context Vertical")
    print("(Detectează pixeli cu fundal DEASUPRA și DEDESUBT)")
    print(f"Input:  {IMAGE_PATH}")
    print(f"Output: {OUTPUT_DIR}")
    print("-" * 60)

    generate_variants(IMAGE_PATH, OUTPUT_DIR)

    print("-" * 60)
    print("Gata!")