{"id":1044010,"date":"2024-12-31T13:10:58","date_gmt":"2024-12-31T05:10:58","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1044010.html"},"modified":"2024-12-31T13:11:00","modified_gmt":"2024-12-31T05:11:00","slug":"%e5%a6%82%e4%bd%95%e7%94%a8-python%e7%8e%a9%e8%b7%b3%e4%b8%80%e8%b7%b3","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1044010.html","title":{"rendered":"\u5982\u4f55\u7528 python\u73a9\u8df3\u4e00\u8df3"},"content":{"rendered":"

\"\u5982\u4f55\u7528<\/p>\n

\u4f7f\u7528Python\u73a9\u5fae\u4fe1\u5c0f\u6e38\u620f\u201c\u8df3\u4e00\u8df3\u201d\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5305\u62ec\u56fe\u50cf\u8bc6\u522b\u3001\u6a21\u62df\u70b9\u51fb\u3001\u81ea\u52a8\u5316\u811a\u672c\u7b49\u3002\u8fd9\u4e9b\u65b9\u6cd5\u4e3b\u8981\u5305\u62ec\uff1a\u56fe\u50cf\u8bc6\u522b\u3001\u6a21\u62df\u70b9\u51fb\u3001\u81ea\u52a8\u5316\u811a\u672c\u3002<\/strong>\u5176\u4e2d\uff0c\u56fe\u50cf\u8bc6\u522b\u662f\u901a\u8fc7\u5206\u6790\u6e38\u620f\u622a\u56fe\u6765\u786e\u5b9a\u8df3\u8dc3\u7684\u76ee\u6807\u4f4d\u7f6e\u548c\u529b\u5ea6\uff0c\u6a21\u62df\u70b9\u51fb\u662f\u901a\u8fc7\u7a0b\u5e8f\u63a7\u5236\u624b\u673a\u89e6\u6478\u5c4f\u8fdb\u884c\u8df3\u8dc3\uff0c\u81ea\u52a8\u5316\u811a\u672c\u5219\u7efc\u5408\u4e86\u524d\u4e24\u8005\uff0c\u5b9e\u73b0\u5168\u81ea\u52a8\u5316\u7684\u6e38\u620f\u64cd\u4f5c\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u5b9e\u73b0\u201c\u8df3\u4e00\u8df3\u201d\u6e38\u620f\u7684\u81ea\u52a8\u5316\u64cd\u4f5c\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u73af\u5883\u642d\u5efa<\/p>\n<\/p>\n

\u5728\u5f00\u59cb\u7f16\u5199\u4ee3\u7801\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u642d\u5efa\u4e00\u4e2a\u5408\u9002\u7684\u5f00\u53d1\u73af\u5883\u3002\u4e3b\u8981\u5305\u62ecPython\u7684\u5b89\u88c5\u548c\u5fc5\u8981\u5e93\u7684\u914d\u7f6e\u3002<\/p>\n<\/p>\n

1\u3001Python\u5b89\u88c5<\/p>\n

\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u7684\u7535\u8111\u4e0a\u5b89\u88c5\u4e86Python\uff0c\u53ef\u4ee5\u4ecePython\u7684\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u5e76\u5b89\u88c5\u6700\u65b0\u7248\u672c\u7684Python\u3002\u540c\u65f6\uff0c\u5efa\u8bae\u5b89\u88c5\u4e00\u4e2aPython IDE\uff0c\u4f8b\u5982PyCharm\u6216VSCode\uff0c\u4ee5\u4fbf\u4e8e\u4ee3\u7801\u7f16\u5199\u548c\u8c03\u8bd5\u3002<\/p>\n<\/p>\n

2\u3001\u5b89\u88c5\u5fc5\u8981\u5e93<\/p>\n

\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u4e00\u4e9b\u5fc5\u8981\u7684\u5e93\uff0c\u5305\u62ecopencv-python<\/code>\u3001numpy<\/code>\u3001pillow<\/code>\u3001adb<\/code>\u7b49\u3002\u8fd9\u4e9b\u5e93\u53ef\u4ee5\u901a\u8fc7pip<\/code>\u547d\u4ee4\u6765\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install opencv-python numpy pillow adb<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u4e9b\u5e93\u5206\u522b\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u3001\u6570\u503c\u8ba1\u7b97\u3001\u56fe\u50cf\u64cd\u4f5c\u548c\u5b89\u5353\u8bbe\u5907\u7684\u8c03\u8bd5\u3002<\/p>\n<\/p>\n
3\u3001\u914d\u7f6eADB<\/p>\n
ADB\uff08Android Debug Bridge\uff09\u662f\u4e00\u4e2a\u901a\u7528\u7684\u547d\u4ee4\u884c\u5de5\u5177\uff0c\u5141\u8bb8\u6211\u4eec\u4e0e\u5b89\u5353\u8bbe\u5907\u8fdb\u884c\u901a\u4fe1\u3002\u5728\u4f7f\u7528ADB\u4e4b\u524d\uff0c\u9700\u8981\u786e\u4fdd\u4f60\u7684\u5b89\u5353\u8bbe\u5907\u5df2\u7ecf\u5f00\u542f\u4e86\u5f00\u53d1\u8005\u9009\u9879\u548cUSB\u8c03\u8bd5\u6a21\u5f0f\uff0c\u5e76\u901a\u8fc7USB\u8fde\u63a5\u5230\u7535\u8111\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u622a\u56fe\u83b7\u53d6<\/p>\n<\/p>\n
\u4e3a\u4e86\u5b9e\u73b0\u81ea\u52a8\u5316\u8df3\u8dc3\uff0c\u6211\u4eec\u9996\u5148\u9700\u8981\u83b7\u53d6\u6e38\u620f\u7684\u5b9e\u65f6\u622a\u56fe\u3002\u53ef\u4ee5\u901a\u8fc7ADB\u547d\u4ee4\u6765\u83b7\u53d6\u622a\u56fe\u5e76\u4fdd\u5b58\u5230\u672c\u5730\u3002<\/p>\n<\/p>\n
import os<\/p>\n
import cv2<\/p>\n
import numpy as np<\/p>\n
from PIL import Image<\/p>\n
def get_screenshot():<\/p>\n
    os.system('adb shell screencap -p \/sdcard\/screen.png')<\/p>\n
    os.system('adb pull \/sdcard\/screen.png .')<\/p>\n
    img = Image.open('screen.png')<\/p>\n
    img = np.array(img)<\/p>\n
    return img<\/p>\n
screenshot = get_screenshot()<\/p>\n
cv2.imshow('Screenshot', screenshot)<\/p>\n
cv2.wAI<\/a>tKey(0)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u4ee3\u7801\uff0c\u6211\u4eec\u53ef\u4ee5\u83b7\u53d6\u5f53\u524d\u6e38\u620f\u7684\u622a\u56fe\u5e76\u663e\u793a\u51fa\u6765\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u5bf9\u622a\u56fe\u8fdb\u884c\u5904\u7406\uff0c\u4ee5\u8bc6\u522b\u5f53\u524d\u7684\u6e38\u620f\u72b6\u6001\u548c\u76ee\u6807\u4f4d\u7f6e\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u56fe\u50cf\u8bc6\u522b<\/p>\n<\/p>\n
\u56fe\u50cf\u8bc6\u522b\u662f\u5b9e\u73b0\u81ea\u52a8\u5316\u8df3\u8dc3\u7684\u5173\u952e\u6b65\u9aa4\u3002\u901a\u8fc7\u5bf9\u622a\u56fe\u8fdb\u884c\u5904\u7406\uff0c\u6211\u4eec\u53ef\u4ee5\u8bc6\u522b\u51fa\u5f53\u524d\u7684\u89d2\u8272\u4f4d\u7f6e\u548c\u76ee\u6807\u4f4d\u7f6e\u3002<\/p>\n<\/p>\n
1\u3001\u8bc6\u522b\u89d2\u8272\u4f4d\u7f6e<\/p>\n
\u89d2\u8272\u7684\u4f4d\u7f6e\u901a\u5e38\u662f\u56fa\u5b9a\u7684\uff0c\u53ef\u4ee5\u901a\u8fc7\u989c\u8272\u6216\u5f62\u72b6\u7279\u5f81\u6765\u8bc6\u522b\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u989c\u8272\u8bc6\u522b\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
def find_character(img):<\/p>\n
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)<\/p>\n
    lower_color = np.array([100, 43, 46])<\/p>\n
    upper_color = np.array([124, 255, 255])<\/p>\n
    mask = cv2.inRange(hsv, lower_color, upper_color)<\/p>\n
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)<\/p>\n
    if contours:<\/p>\n
        c = max(contours, key=cv2.contourArea)<\/p>\n
        x, y, w, h = cv2.boundingRect(c)<\/p>\n
        return (x + w \/\/ 2, y + h)<\/p>\n
    return None<\/p>\n
character_pos = find_character(screenshot)<\/p>\n
print('Character Position:', character_pos)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bc6\u522b\u76ee\u6807\u4f4d\u7f6e<\/p>\n
\u76ee\u6807\u4f4d\u7f6e\u901a\u5e38\u662f\u6e38\u620f\u4e2d\u5176\u4ed6\u65b9\u5757\u7684\u4e2d\u5fc3\u4f4d\u7f6e\uff0c\u53ef\u4ee5\u901a\u8fc7\u8fb9\u7f18\u68c0\u6d4b\u548c\u5f62\u72b6\u5206\u6790\u6765\u8bc6\u522b\uff1a<\/p>\n<\/p>\n
def find_target(img, character_pos):<\/p>\n
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)<\/p>\n
    edges = cv2.Canny(gray, 50, 150)<\/p>\n
    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)<\/p>\n
    for c in contours:<\/p>\n
        if cv2.contourArea(c) > 500:<\/p>\n
            x, y, w, h = cv2.boundingRect(c)<\/p>\n
            if abs(x + w \/\/ 2 - character_pos[0]) > 50:<\/p>\n
                return (x + w \/\/ 2, y + h \/\/ 2)<\/p>\n
    return None<\/p>\n
target_pos = find_target(screenshot, character_pos)<\/p>\n
print('Target Position:', target_pos)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u8ba1\u7b97\u8df3\u8dc3\u8ddd\u79bb<\/p>\n<\/p>\n
\u6839\u636e\u89d2\u8272\u4f4d\u7f6e\u548c\u76ee\u6807\u4f4d\u7f6e\uff0c\u6211\u4eec\u53ef\u4ee5\u8ba1\u7b97\u51fa\u9700\u8981\u8df3\u8dc3\u7684\u8ddd\u79bb\u3002\u8df3\u8dc3\u8ddd\u79bb\u901a\u5e38\u662f\u4e24\u8005\u4e4b\u95f4\u7684\u6b27\u51e0\u91cc\u5f97\u8ddd\u79bb\u3002<\/p>\n<\/p>\n
import math<\/p>\n
def calculate_jump_distance(character_pos, target_pos):<\/p>\n
    return math.sqrt((target_pos[0] - character_pos[0]) <strong> 2 + (target_pos[1] - character_pos[1]) <\/strong> 2)<\/p>\n
distance = calculate_jump_distance(character_pos, target_pos)<\/p>\n
print('Jump Distance:', distance)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u6a21\u62df\u70b9\u51fb<\/p>\n<\/p>\n
\u6839\u636e\u8ba1\u7b97\u51fa\u7684\u8df3\u8dc3\u8ddd\u79bb\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7ADB\u547d\u4ee4\u6765\u6a21\u62df\u70b9\u51fb\u64cd\u4f5c\uff0c\u5b9e\u73b0\u8df3\u8dc3\u3002\u70b9\u51fb\u7684\u65f6\u95f4\u4e0e\u8df3\u8dc3\u8ddd\u79bb\u6210\u6b63\u6bd4\u3002<\/p>\n<\/p>\n
def jump(distance):<\/p>\n
    press_time = int(distance * 1.35)  # \u8c03\u6574\u7cfb\u6570\u4ee5\u83b7\u5f97\u6700\u4f73\u6548\u679c<\/p>\n
    os.system(f'adb shell input swipe 500 1600 500 1600 {press_time}')<\/p>\n
jump(distance)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u4e3b\u5faa\u73af<\/p>\n<\/p>\n
\u5c06\u4e0a\u8ff0\u6b65\u9aa4\u6574\u5408\u5230\u4e00\u4e2a\u4e3b\u5faa\u73af\u4e2d\uff0c\u4f7f\u7a0b\u5e8f\u53ef\u4ee5\u8fde\u7eed\u4e0d\u65ad\u5730\u8fdb\u884c\u622a\u56fe\u3001\u8bc6\u522b\u3001\u8ba1\u7b97\u548c\u8df3\u8dc3\uff0c\u76f4\u5230\u6e38\u620f\u7ed3\u675f\u3002<\/p>\n<\/p>\n
import time<\/p>\n
while True:<\/p>\n
    screenshot = get_screenshot()<\/p>\n
    character_pos = find_character(screenshot)<\/p>\n
    target_pos = find_target(screenshot, character_pos)<\/p>\n
    if character_pos and target_pos:<\/p>\n
        distance = calculate_jump_distance(character_pos, target_pos)<\/p>\n
        jump(distance)<\/p>\n
        time.sleep(1)  # \u9632\u6b62\u8df3\u8dc3\u8fc7\u5feb<\/p>\n
    else:<\/p>\n
        break<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u4f7f\u7528Python\u5b9e\u73b0\u5fae\u4fe1\u5c0f\u6e38\u620f\u201c\u8df3\u4e00\u8df3\u201d\u7684\u81ea\u52a8\u5316\u64cd\u4f5c\u4e86\u3002\u5f53\u7136\uff0c\u5b9e\u9645\u5e94\u7528\u4e2d\u53ef\u80fd\u9700\u8981\u6839\u636e\u5177\u4f53\u60c5\u51b5\u8fdb\u884c\u4e00\u4e9b\u8c03\u6574\u548c\u4f18\u5316\uff0c\u4f8b\u5982\u8c03\u6574\u989c\u8272\u8bc6\u522b\u7684\u9608\u503c\u3001\u4f18\u5316\u8fb9\u7f18\u68c0\u6d4b\u7684\u53c2\u6570\u7b49\u3002<\/p>\n<\/p>\n
\u4e03\u3001\u4f18\u5316\u548c\u6269\u5c55<\/p>\n<\/p>\n
\u5728\u5b9e\u73b0\u4e86\u57fa\u672c\u7684\u81ea\u52a8\u5316\u8df3\u8dc3\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u4e00\u6b65\u4f18\u5316\u548c\u6269\u5c55\u7a0b\u5e8f\uff0c\u4ee5\u63d0\u9ad8\u5176\u7a33\u5b9a\u6027\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n
1\u3001\u4f18\u5316\u56fe\u50cf\u8bc6\u522b<\/p>\n
\u56fe\u50cf\u8bc6\u522b\u7684\u51c6\u786e\u6027\u76f4\u63a5\u5f71\u54cd\u5230\u8df3\u8dc3\u7684\u6210\u529f\u7387\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u65b9\u5f0f\u6765\u4f18\u5316\u56fe\u50cf\u8bc6\u522b\uff1a<\/p>\n<\/p>\n