zjsh_yolov11/yemian/yemian_line/danmu_d.py

import os
import cv2
import numpy as np
from pathlib import Path
from ultralytics import YOLO

# --------------------
# 配置
# --------------------
TARGET_SIZE = 640
IMAGE_DIR = "/media/hx/04e879fa-d697-4b02-ac7e-a4148876ebb0/dataset/1/612/train/class0"
MODEL_PATH = "/home/hx/yolo/ultralytics_yolo11-main/runs/train/61seg/exp2/weights/best.pt"
OUTPUT_DIR = "/media/hx/04e879fa-d697-4b02-ac7e-a4148876ebb0/dataset/1/612/train/class2"
'''
ROIS = [
    (445, 540, 931, 319),
]

'''
ROIS = [
    (0, 0, 640, 640),
]

# --------------------
# 从 mask 中提取左右边界点
# --------------------
def extract_left_right_edge_points(mask_bin):
    h, w = mask_bin.shape
    left_pts = []
    right_pts = []

    for y in range(h):
        xs = np.where(mask_bin[y] > 0)[0]
        if len(xs) >= 2:
            left_pts.append([xs.min(), y])
            right_pts.append([xs.max(), y])

    return np.array(left_pts), np.array(right_pts)

# --------------------
# 按 seg 的 y 百分比筛选
# --------------------
def filter_by_seg_y_ratio(pts, y_start=0.35, y_end=0.85):
    if len(pts) < 2:
        return pts

    y_min = pts[:, 1].min()
    y_max = pts[:, 1].max()
    h = y_max - y_min
    if h < 10:
        return pts

    y0 = y_min + int(h * y_start)
    y1 = y_min + int(h * y_end)

    return pts[(pts[:, 1] >= y0) & (pts[:, 1] <= y1)]

# --------------------
# 拟合直线
# --------------------
def fit_line(pts):
    if len(pts) < 2:
        return None
    x = pts[:, 0]
    y = pts[:, 1]
    m, b = np.polyfit(y, x, 1)
    return m, b

# --------------------
# y 参考值（seg 底部）
# --------------------
def get_y_ref(mask_bin):
    h, w = mask_bin.shape
    ys = []
    for x in range(int(w * 0.2), int(w * 0.8)):
        y = np.where(mask_bin[:, x] > 0)[0]
        if len(y):
            ys.append(y.max())
    return int(np.mean(ys)) if ys else h // 2

# --------------------
# 单图处理
# --------------------
def process_one(img_path, model):
    img = cv2.imread(str(img_path))
    vis = img.copy()

    result_data = None  # (XL, Y, XR, Y, diff)

    for rx, ry, rw, rh in ROIS:
        roi = img[ry:ry+rh, rx:rx+rw]
        resized = cv2.resize(roi, (TARGET_SIZE, TARGET_SIZE))

        result = model(resized, imgsz=TARGET_SIZE, verbose=False)[0]
        if result.masks is None:
            continue

        mask = result.masks.data[0].cpu().numpy()
        mask_bin = (mask > 0.5).astype(np.uint8)
        mask_bin = cv2.resize(mask_bin, (rw, rh), cv2.INTER_NEAREST)

        # overlay mask
        green = np.zeros_like(roi)
        green[mask_bin == 1] = (0, 255, 0)
        vis[ry:ry+rh, rx:rx+rw] = cv2.addWeighted(roi, 0.7, green, 0.3, 0)

        # 边界点
        left_pts, right_pts = extract_left_right_edge_points(mask_bin)
        left_pts = filter_by_seg_y_ratio(left_pts)
        right_pts = filter_by_seg_y_ratio(right_pts)

        left_line = fit_line(left_pts)
        right_line = fit_line(right_pts)
        if left_line is None or right_line is None:
            continue

        m1, b1 = left_line
        m2, b2 = right_line

        y_ref = get_y_ref(mask_bin)

        # ROI 坐标
        x_left = int(m1 * y_ref + b1)
        x_right = int(m2 * y_ref + b2)

        # 🔴 全局坐标
        X_L = rx + x_left
        X_R = rx + x_right
        Y = ry + y_ref

        diff = X_R - X_L

        result_data = (X_L, Y, X_R, Y, diff)

        # ---------- 可视化 ----------
        roi_vis = vis[ry:ry+rh, rx:rx+rw]

        for (m, b), c in [((m1, b1), (0,0,255)), ((m2, b2), (255,0,0))]:
            cv2.line(
                roi_vis,
                (int(m * 0 + b), 0),
                (int(m * rh + b), rh),
                c, 3
            )

        cv2.line(roi_vis, (0, y_ref), (rw, y_ref), (0,255,255), 2)
        cv2.circle(roi_vis, (x_left, y_ref), 6, (0,0,255), -1)
        cv2.circle(roi_vis, (x_right, y_ref), 6, (255,0,0), -1)

        cv2.putText(
            roi_vis,
            f"diff={diff}px",
            (10, 40),
            cv2.FONT_HERSHEY_SIMPLEX,
            1,
            (0,255,255),
            2
        )

    return vis, result_data

# --------------------
# 批处理
# --------------------
def run():
    model = YOLO(MODEL_PATH)
    Path(OUTPUT_DIR).mkdir(exist_ok=True)

    for img in sorted(os.listdir(IMAGE_DIR)):
        if not img.lower().endswith((".jpg", ".png", ".jpeg")):
            continue

        vis, data = process_one(Path(IMAGE_DIR) / img, model)
        out = Path(OUTPUT_DIR) / f"vis_{img}"
        cv2.imwrite(str(out), vis)

        if data:
            XL, YL, XR, YR, diff = data
            print(f"[{img}]")
            print(f"  左交点: ({XL}, {YL})")
            print(f"  右交点: ({XR}, {YR})")
            print(f"  diff  : {diff} px")
        else:
            print(f"[{img}] 无有效结果")

# --------------------
if __name__ == "__main__":
    run()