Editing Openai/692fcfd8-4b44-800f-a184-fa098175a6d5 (section)

=== 直接複製即可執行： ===

<syntaxhighlight lang="python"># hand_gesture_1_10_no_sound.py
=== Python 3.7 無聲版：手勢 1～10 辨識＋教學面板（無語音、無 pygame） ===

from cvzone.HandTrackingModule import HandDetector
import cv2
import os
import numpy as np

=== ========= 小工具：2D 距離 ========= ===
def euclidean(a, b):
    return ((a[0] - b[0])'''2 + (a[1] - b[1])'''2)**0.5

=== ========= 初始設定 ========= ===
cap = cv2.VideoCapture(0)
detector = HandDetector(detectionCon=0.7, maxHands=2)

zh_map = {
    1: "一",
    2: "二",
    3: "三",
    4: "四",
    5: "五",
    6: "六",
    7: "七",
    8: "八",
    9: "九",
    10: "十",
}

=== ========= 讀取手勢示意圖 ========= ===
gesture_images = {}
for n in range(1, 11):
    path = os.path.join("gestures", f"{n}.png")
    if os.path.exists(path):
        img = cv2.imread(path)
        if img is not None:
            gesture_images[n] = img
    else:
        print(f"[提示] 找不到手勢圖片 gestures/{n}.png")

=== ========= 單手手勢判斷（1～9） ========= ===
def classify_single_hand_number(hand, fingers):
    pattern = tuple(fingers)

    mapping = {
        (0, 1, 1, 0, 0): (2, "2"),
        (1, 1, 1, 0, 0): (3, "3"),
        (0, 1, 1, 1, 1): (4, "4"),
        (1, 1, 1, 1, 1): (5, "5"),
        (1, 0, 0, 0, 1): (6, "6"),
        (1, 1, 0, 0, 1): (7, "7"),
        (1, 1, 0, 0, 0): (8, "8"),
    }

    if pattern in mapping:
        return mapping[pattern]

    # ---- 特判 1 / 9：只伸食指 ----
    if pattern == (0, 1, 0, 0, 0):
        lm = hand["lmList"]
        mcp = lm[5]
        pip = lm[6]
        dip = lm[7]
        tip = lm[8]

        dist_mcp_tip = euclidean(mcp, tip)

        poly = (
            euclidean(mcp, pip) +
            euclidean(pip, dip) +
            euclidean(dip, tip)
        )

        if dist_mcp_tip > 0 and poly / dist_mcp_tip > 1.25:
            return (9, "9")
        else:
            return (1, "1")

    return (None, "None")

=== ========= 整體判斷（含 10） ========= ===
def classify_number(hands):
    if not hands:
        return None, "No Hand", None

    # 判斷 10（兩手都是 1）
    if len(hands) >= 2:
        nums = []
        for h in hands[:2]:
            f = detector.fingersUp(h)
            n, _ = classify_single_hand_number(h, f)
            nums.append(n)

        if nums[0] == 1 and nums[1] == 1:
            return 10, "10", hands[0]["bbox"]

    # 判斷 1～9
    main = hands[0]
    bbox = main["bbox"]
    fingers = detector.fingersUp(main)
    number, label = classify_single_hand_number(main, fingers)

    return number, label, bbox

=== ========= 主迴圈 ========= ===
while True:
    success, img = cap.read()
    if not success:
        break

    hands, img = detector.findHands(img)

    number, label, bbox = classify_number(hands)

    h, w, _ = img.shape
    panel_width = 320
    panel = 255 * np.ones((h, panel_width, 3), dtype="uint8")

    # ===== 教學面板 =====
    if number in zh_map:
        # 示意圖
        if number in gesture_images:
            g = gesture_images[number]
            gh, gw, _ = g.shape
            scale = min((h '' 0.6) / gh, (panel_width '' 0.9) / gw)
            nw = int(gw * scale)
            nh = int(gh * scale)
            g2 = cv2.resize(g, (nw, nh))

            xo = (panel_width - nw) // 2
            yo = 20
            panel[yo:yo+nh, xo:xo+nw] = g2

        # 文本
        ty = int(h * 0.75)
        cv2.putText(panel, str(number),
                    (30, ty),
                    cv2.FONT_HERSHEY_SIMPLEX, 1.2, (0, 0, 0), 2)
        cv2.putText(panel, f"中文：{zh_map[number]}",
                    (30, ty + 40),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 0), 2)

    else:
        cv2.putText(panel, "請比出 1~10 的手勢",
                    (20, h // 2),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.8, (80, 80, 80), 2)

    # 偵測框
    if bbox and number:
        x, y, bw, bh = bbox
        cv2.rectangle(img, (x, y), (x + bw, y + bh), (0, 255, 0), 2)
        cv2.putText(img, label, (x, y - 10),
                    cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

    # 合併畫面
    panel = cv2.resize(panel, (panel_width, h))
    combined = cv2.hconcat([img, panel])

    cv2.imshow("Hand Number Teaching (1-10) - 無聲版", combined)

    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

cap.release()
cv2.destroyAllWindows()

</syntaxhighlight>