import cv2
import numpy as np

# === 1. 檔案與參數設定 ===
img_path = r'C:\Users\rd_de\kneronstdc\work_dirs\vis_results\good\pic_0441_jpg.rf.6e56eb8c0bed7f773fb447b9e217f779_leftImg8bit.png'

# 色彩轉 label ID（RGB）
CLASS_RGB_TO_ID = {
    (128, 64, 128): 3,  # road（灰）
    (0, 255, 0): 1,     # grass（綠）
    (255, 0, 255): 9,   # background or sky（紫）可忽略
}

ROAD_ID = 3
GRASS_ID = 1

# === 2. 讀圖並轉為 label mask ===
bgr_img = cv2.imread(img_path)
rgb_img = cv2.cvtColor(bgr_img, cv2.COLOR_BGR2RGB)
height, width, _ = rgb_img.shape

label_mask = np.zeros((height, width), dtype=np.uint8)
for rgb, label in CLASS_RGB_TO_ID.items():
    match = np.all(rgb_img == rgb, axis=-1)
    label_mask[match] = label

# === 3. 分析畫面中下區域 ===
y_start = int(height * 0.6)
x_start = int(width * 0.4)
x_end = int(width * 0.6)
roi = label_mask[y_start:, x_start:x_end]

total_pixels = roi.size
road_pixels = np.sum(roi == ROAD_ID)
grass_pixels = np.sum(roi == GRASS_ID)

road_ratio = road_pixels / total_pixels
grass_ratio = grass_pixels / total_pixels

# === 4. 重心偏移分析 ===
road_mask = (label_mask == ROAD_ID).astype(np.uint8)
M = cv2.moments(road_mask)
center_x = width // 2
offset = 0
cx = center_x
if M["m00"] > 0:
    cx = int(M["m10"] / M["m00"])
    offset = cx - center_x

# === 5. 結果輸出 ===
print(f"🔍 中央 ROI - road比例: {road_ratio:.2f}, grass比例: {grass_ratio:.2f}")
if road_ratio < 0.5:
    print("⚠️ 偏離道路（ROI 中道路比例過少）")
if grass_ratio > 0.3:
    print("❗ 車輛壓到草地！")
if abs(offset) > 40:
    print(f"⚠️ 道路重心偏移：{offset} px")
else:
    print("✅ 道路重心正常")

# === 6. 可視化 ===
vis_img = bgr_img.copy()
cv2.rectangle(vis_img, (x_start, y_start), (x_end, height), (0, 255, 255), 2)  # 黃色框 ROI
cv2.line(vis_img, (center_x, 0), (center_x, height), (255, 0, 0), 2)            # 藍色中心線
cv2.circle(vis_img, (cx, height // 2), 6, (0, 0, 255), -1)                      # 紅色重心點

# 輸出圖片
save_path = r'C:\Users\rd_de\kneronstdc\work_dirs\vis_results\good\visual_check.png'
cv2.imwrite(save_path, vis_img)
print(f"✅ 分析圖儲存成功：{save_path}")