import cv2
import numpy as np

# 创建画布
canvas = np.zeros((500, 700, 3), dtype=np.uint8)

# 画直线
cv2.line(canvas, (50, 50), (300, 200), (0, 255, 0), 2)       # 绿色线
cv2.line(canvas, (50, 100), (300, 250), (255, 0, 0), 5)      # 蓝色粗线

# 不同线型（仅 LINE_4 / LINE_8 / LINE_AA）
cv2.line(canvas, (50, 150), (300, 300), (0, 0, 255), 1, cv2.LINE_4)
cv2.line(canvas, (50, 200), (300, 350), (0, 255, 255), 1, cv2.LINE_AA)  # 抗锯齿

# 箭头线
cv2.arrowedLine(canvas, (400, 50), (600, 200), (255, 255, 0), 2,
                tipLength=0.05)

# 标记点
cv2.drawMarker(canvas, (350, 100), (0, 255, 255),
               cv2.MARKER_CROSS, 20, 2)
cv2.drawMarker(canvas, (400, 100), (0, 255, 255),
               cv2.MARKER_TILTED_CROSS, 20, 2)
cv2.drawMarker(canvas, (450, 100), (0, 255, 255),
               cv2.MARKER_STAR, 20, 2)

# 空心矩形
cv2.rectangle(canvas, (50, 300), (200, 450), (255, 255, 255), 2)

# 填充矩形（thickness = -1）
cv2.rectangle(canvas, (220, 300), (370, 450), (0, 128, 255), -1)

# 半透明矩形（需要混合操作）
overlay = canvas.copy()
cv2.rectangle(overlay, (390, 300), (540, 450), (255, 0, 128), -1)
cv2.addWeighted(overlay, 0.5, canvas, 0.5, 0, canvas)  # 50% 透明

# 圆
cv2.circle(canvas, (600, 100), 50, (255, 255, 255), 2)       # 空心
cv2.circle(canvas, (600, 250), 40, (0, 255, 0), -1)          # 填充

# 椭圆
cv2.ellipse(canvas, (150, 380), (100, 50), 30, 0, 360, (255, 0, 255), 2)
cv2.ellipse(canvas, (150, 380), (60, 30), 30, 0, 180, (0, 255, 255), -1)

# 弧线
cv2.ellipse(canvas, (500, 380), (80, 40), 0, 45, 270, (255, 255, 0), 3)

# 定义顶点
pts = np.array([[550, 300], [620, 350], [650, 450],
                [580, 470], [520, 420]], np.int32)
pts = pts.reshape((-1, 1, 2))

# 空心多边形
cv2.polylines(canvas, [pts], True, (0, 255, 255), 2)

# 填充多边形
pts2 = np.array([[400, 150], [450, 100], [500, 150],
                 [480, 200], [420, 200]], np.int32)
cv2.fillPoly(canvas, [pts2], (128, 255, 128))

# 凸包多边形（自动排序）
hull = cv2.convexHull(pts)
cv2.polylines(canvas, [hull], True, (0, 0, 255), 1, cv2.LINE_AA)

canvas = np.zeros((400, 600, 3), dtype=np.uint8)

# 基本文字
cv2.putText(canvas, "Hello OpenCV", (50, 50),
            cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255), 2)

# 不同字体
fonts = [
    (cv2.FONT_HERSHEY_SIMPLEX,        "SIMPLEX"),
    (cv2.FONT_HERSHEY_PLAIN,          "PLAIN"),
    (cv2.FONT_HERSHEY_DUPLEX,         "DUPLEX"),
    (cv2.FONT_HERSHEY_COMPLEX,        "COMPLEX"),
    (cv2.FONT_HERSHEY_TRIPLEX,        "TRIPLEX"),
    (cv2.FONT_HERSHEY_COMPLEX_SMALL,  "COMPLEX_SMALL"),
    (cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, "SCRIPT"),
    (cv2.FONT_HERSHEY_SCRIPT_COMPLEX, "SCRIPT_COMPLEX"),
]

for i, (font, name) in enumerate(fonts):
    y = 100 + i * 35
    cv2.putText(canvas, name, (50, y), font, 0.7, (0, 255, 0), 1, cv2.LINE_AA)

from PIL import Image, ImageDraw, ImageFont
import cv2
import numpy as np

def put_chinese_text(img, text, position, font_size=32,
                     color=(255, 255, 255)):
    """在 OpenCV 图像上绘制中文文字"""
    # 转换为 PIL Image
    img_pil = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
    draw = ImageDraw.Draw(img_pil)

    # 加载中文字体
    font = ImageFont.truetype("/usr/share/fonts/truetype/"
                              "noto/NotoSansCJK-Regular.ttc",
                              font_size)

    draw.text(position, text, font=font,
              fill=(color[2], color[1], color[0]))  # RGB 顺序

    # 转回 OpenCV 格式
    return cv2.cvtColor(np.array(img_pil), cv2.COLOR_RGB2BGR)

# 使用
canvas = np.zeros((400, 600, 3), dtype=np.uint8)
canvas = put_chinese_text(canvas, "计算机视觉教程", (50, 50), 40)

def draw_label_box(img, text, x, y, color=(0, 255, 0)):
    """绘制带背景的文字标签框"""
    font = cv2.FONT_HERSHEY_SIMPLEX
    scale = 0.6
    thickness = 1

    # 计算文字尺寸
    (tw, th), baseline = cv2.getTextSize(text, font, scale, thickness)

    # 绘制背景矩形
    cv2.rectangle(img, (x, y - th - 10), (x + tw + 10, y), color, -1)

    # 绘制文字
    cv2.putText(img, text, (x + 5, y - 5), font, scale,
                (0, 0, 0), thickness, cv2.LINE_AA)

"""
draw_app.py — 简易画板应用
"""
import cv2
import numpy as np

# 全局变量
drawing = False
ix, iy = -1, -1
color = (0, 255, 0)
thickness = 2
canvas = np.zeros((600, 800, 3), dtype=np.uint8)

def draw_line(event, x, y, flags, param):
    global drawing, ix, iy, canvas

    if event == cv2.EVENT_LBUTTONDOWN:
        drawing = True
        ix, iy = x, y

    elif event == cv2.EVENT_MOUSEMOVE:
        if drawing:
            cv2.line(canvas, (ix, iy), (x, y), color, thickness)
            ix, iy = x, y

    elif event == cv2.EVENT_LBUTTONUP:
        drawing = False
        cv2.line(canvas, (ix, iy), (x, y), color, thickness)

# 创建窗口并绑定回调
cv2.namedWindow("画板")
cv2.setMouseCallback("画板", draw_line)

print("操作说明: 鼠标绘图 | c:清除 | r/g/b:颜色 | +/-:粗细 | q:退出")

while True:
    cv2.imshow("画板", canvas)
    key = cv2.waitKey(1) & 0xFF

    if key == ord('q'):
        break
    elif key == ord('c'):
        canvas[:] = 0
    elif key == ord('r'):
        color = (0, 0, 255)
    elif key == ord('g'):
        color = (0, 255, 0)
    elif key == ord('b'):
        color = (255, 0, 0)
    elif key == ord('+') or key == ord('='):
        thickness = min(thickness + 1, 20)
    elif key == ord('-'):
        thickness = max(thickness - 1, 1)

cv2.destroyAllWindows()

"""
roi_selector.py — 交互式 ROI 选择
"""
import cv2

img = cv2.imread("photo.jpg")
clone = img.copy()
roi_pts = []
drawing = False

def mouse_callback(event, x, y, flags, param):
    global roi_pts, drawing, img

    if event == cv2.EVENT_LBUTTONDOWN:
        roi_pts.append((x, y))
        drawing = True

    elif event == cv2.EVENT_MOUSEMOVE and drawing:
        temp = img.copy()
        if len(roi_pts) > 0:
            cv2.line(temp, roi_pts[-1], (x, y), (0, 255, 0), 2)
        cv2.imshow("ROI 选择", temp)

    elif event == cv2.EVENT_LBUTTONUP:
        drawing = False
        cv2.circle(img, (x, y), 3, (0, 0, 255), -1)

cv2.namedWindow("ROI 选择")
cv2.setMouseCallback("ROI 选择", mouse_callback)

print("左键点击选择 ROI 点 | Enter:确认 | c:重置")

while True:
    cv2.imshow("ROI 选择", img)
    key = cv2.waitKey(1) & 0xFF

    if key == 13:  # Enter
        if len(roi_pts) >= 3:
            pts = np.array(roi_pts, np.int32).reshape((-1, 1, 2))
            mask = np.zeros(img.shape[:2], dtype=np.uint8)
            cv2.fillPoly(mask, [pts], 255)
            roi = cv2.bitwise_and(clone, clone, mask=mask)
            cv2.imshow("提取 ROI", roi)
            print(f"选择了 {len(roi_pts)} 个点的多边形 ROI")
        break
    elif key == ord('c'):
        img = clone.copy()
        roi_pts = []

cv2.waitKey(0)
cv2.destroyAllWindows()

"""
trackbar_demo.py — 滑块实时调参
"""
import cv2
import numpy as np

img = cv2.imread("photo.jpg")
if img is None:
    img = np.random.randint(0, 256, (480, 640, 3), dtype=np.uint8)

def nothing(x):
    pass  # 回调函数占位

cv2.namedWindow("调整")
cv2.createTrackbar("亮度",   "调整", 0,   100, nothing)
cv2.createTrackbar("对比度", "调整", 100, 300, nothing)
cv2.createTrackbar("模糊",   "调整", 0,   20,  nothing)

while True:
    brightness = cv2.getTrackbarPos("亮度", "调整")
    contrast   = cv2.getTrackbarPos("对比度", "调整")
    blur_k     = cv2.getTrackbarPos("模糊", "调整")

    # 应用亮度和对比度
    result = cv2.convertScaleAbs(img, alpha=contrast/100.0,
                                 beta=brightness)

    # 应用模糊（核大小必须为奇数）
    if blur_k > 0:
        k = blur_k * 2 + 1
        result = cv2.GaussianBlur(result, (k, k), 0)

    cv2.imshow("调整", result)
    if cv2.waitKey(30) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()

"""
hsv_picker.py — 交互式 HSV 颜色范围选取器
"""
import cv2
import numpy as np

img = cv2.imread("photo.jpg")
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

def nothing(x):
    pass

cv2.namedWindow("HSV 选取器")

# H: 0-179, S: 0-255, V: 0-255
cv2.createTrackbar("H_min", "HSV 选取器", 0,   179, nothing)
cv2.createTrackbar("H_max", "HSV 选取器", 179, 179, nothing)
cv2.createTrackbar("S_min", "HSV 选取器", 0,   255, nothing)
cv2.createTrackbar("S_max", "HSV 选取器", 255, 255, nothing)
cv2.createTrackbar("V_min", "HSV 选取器", 0,   255, nothing)
cv2.createTrackbar("V_max", "HSV 选取器", 255, 255, nothing)

while True:
    h_min = cv2.getTrackbarPos("H_min", "HSV 选取器")
    h_max = cv2.getTrackbarPos("H_max", "HSV 选取器")
    s_min = cv2.getTrackbarPos("S_min", "HSV 选取器")
    s_max = cv2.getTrackbarPos("S_max", "HSV 选取器")
    v_min = cv2.getTrackbarPos("V_min", "HSV 选取器")
    v_max = cv2.getTrackbarPos("V_max", "HSV 选取器")

    lower = np.array([h_min, s_min, v_min])
    upper = np.array([h_max, s_max, v_max])
    mask = cv2.inRange(hsv, lower, upper)
    result = cv2.bitwise_and(img, img, mask=mask)

    # 显示信息
    info = f"H:[{h_min},{h_max}] S:[{s_min},{s_max}] V:[{v_min},{v_max}]"
    cv2.putText(result, info, (10, 30),
                cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)

    # 并排显示
    mask_bgr = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
    combined = np.hstack([img, mask_bgr, result])
    cv2.imshow("HSV 选取器", combined)

    if cv2.waitKey(30) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()

"""
bbox_drawer.py — 绘制标准检测框（带置信度标签）
"""
import cv2
import numpy as np

def draw_detection(img, bbox, label, confidence, color=(0, 255, 0)):
    """
    绘制目标检测标准框

    参数:
        img: 图像
        bbox: (x1, y1, x2, y2) 边界框坐标
        label: 类别标签
        confidence: 置信度 (0-1)
        color: 框颜色 (B, G, R)
    """
    x1, y1, x2, y2 = map(int, bbox)

    # 绘制边框（角点增强效果）
    corner_len = min(20, (x2 - x1) // 4, (y2 - y1) // 4)
    t = 2  # 线宽

    # 四个角
    cv2.line(img, (x1, y1), (x1 + corner_len, y1), color, t)
    cv2.line(img, (x1, y1), (x1, y1 + corner_len), color, t)
    cv2.line(img, (x2, y1), (x2 - corner_len, y1), color, t)
    cv2.line(img, (x2, y1), (x2, y1 + corner_len), color, t)
    cv2.line(img, (x1, y2), (x1 + corner_len, y2), color, t)
    cv2.line(img, (x1, y2), (x1, y2 - corner_len), color, t)
    cv2.line(img, (x2, y2), (x2 - corner_len, y2), color, t)
    cv2.line(img, (x2, y2), (x2, y2 - corner_len), color, t)

    # 标签背景
    text = f"{label} {confidence:.0%}"
    font = cv2.FONT_HERSHEY_SIMPLEX
    scale = 0.5
    (tw, th), baseline = cv2.getTextSize(text, font, scale, 1)
    cv2.rectangle(img, (x1, y1 - th - 8), (x1 + tw + 4, y1), color, -1)
    cv2.putText(img, text, (x1 + 2, y1 - 4), font, scale,
                (0, 0, 0), 1, cv2.LINE_AA)

# 示例
img = np.zeros((500, 700, 3), dtype=np.uint8)
draw_detection(img, (50, 50, 250, 200), "猫", 0.95, (0, 255, 0))
draw_detection(img, (300, 100, 550, 350), "狗", 0.87, (0, 165, 255))
draw_detection(img, (100, 300, 350, 450), "人", 0.92, (255, 0, 0))