可以稳刷的单机版本
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utils/10.21_820.jpg
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utils/10.21_820.jpg
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115
utils/WindowsAPI.py
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115
utils/WindowsAPI.py
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import numpy, cv2
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import win32gui, win32api, win32con, win32ui
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import time
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from PIL import Image
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def get_window_position(window_title):
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"""
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获取指定窗口的左上角在桌面的位置
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:param window_title: 窗口标题(支持模糊匹配)
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:return: (x, y) 坐标元组,未找到返回 None
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"""
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# 查找目标窗口句柄
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target_hwnd = None
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def enum_windows_callback(hwnd, _):
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nonlocal target_hwnd
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if win32gui.IsWindowVisible(hwnd):
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title = win32gui.GetWindowText(hwnd)
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if window_title.lower() in title.lower():
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# 检查是否是顶级窗口(排除子窗口)
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if win32gui.GetParent(hwnd) == 0:
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target_hwnd = hwnd
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return False # 停止枚举
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return True # 继续枚举
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# 枚举所有窗口
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win32gui.EnumWindows(enum_windows_callback, None)
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# 获取窗口位置
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if target_hwnd:
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rect = win32gui.GetWindowRect(target_hwnd)
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return rect[0], rect[1]
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return None, None
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class WindowsAPI():
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def __init__(self, hwnd=None, region=None):
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# 如果传入 hwnd 则直接使用传入的句柄,否则设为 None
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self.hWnd = hwnd
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self.region = region # region 格式为 (left, top, right, bottom)
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def setRegion(self, region):
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"""设置截图区域"""
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self.region = region
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def getDesktopImg(self):
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if not self.region:
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print("请传入有效的截图区域")
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return None
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left, top, right, bottom = self.region
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width = right - left
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height = bottom - top
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# 获取桌面的设备上下文句柄
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hWndDC = win32gui.GetWindowDC(win32gui.GetDesktopWindow())
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# 创建设备描述表
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mfcDC = win32ui.CreateDCFromHandle(hWndDC)
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# 内存设备描述表
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saveDC = mfcDC.CreateCompatibleDC()
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# 创建位图对象
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saveBitMap = win32ui.CreateBitmap()
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# 分配存储空间
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saveBitMap.CreateCompatibleBitmap(mfcDC, width, height)
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# 将位图对象选入到内存设备描述表
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saveDC.SelectObject(saveBitMap)
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# 截取指定区域
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saveDC.BitBlt((0, 0), (width, height), mfcDC, (left, top), win32con.SRCCOPY)
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# 获取位图信息
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signedIntsArray = saveBitMap.GetBitmapBits(True)
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im_opencv = numpy.frombuffer(signedIntsArray, dtype='uint8')
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im_opencv.shape = (height, width, 4)
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# 内存释放
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win32gui.DeleteObject(saveBitMap.GetHandle())
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saveDC.DeleteDC()
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mfcDC.DeleteDC()
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win32gui.ReleaseDC(win32gui.GetDesktopWindow(), hWndDC)
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im_opencv = cv2.cvtColor(im_opencv, cv2.COLOR_BGR2RGB) # rgb 修改通道数并转换图像
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# im_opencv=im_opencv[40:-1, 2:]
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im_PIL = Image.fromarray(im_opencv) # 图像改成对象类型
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return [im_opencv,im_PIL]
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def showDesktopImg(self):
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imgs = self.getDesktopImg()
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if imgs is None:
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print("无法获取截图")
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return
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im_opencv = imgs[0] # 取 OpenCV 图像
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cv2.imshow("Desktop Screenshot", im_opencv)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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# window_title = "Torchlight:Infinite"
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# left, top = get_window_position(window_title)
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#
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# if left is None or top is None:
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# print(f"错误: 未找到标题包含 '{window_title}' 的窗口")
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# exit(1)
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#
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# print(f"找到窗口 '{window_title}' 位置: ({left}, {top})")
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# 2. 设置截图区域 (左上角x, 左上角y, 右下角x, 右下角y)
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# width, height = 1282, 761
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custom_region = (0, 30, 1280, 30+720)
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winApi = WindowsAPI(region=custom_region)
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print(winApi.region)
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# winApi.showDesktopImg()
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102
utils/caiji.py
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102
utils/caiji.py
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import cv2
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from PIL import Image
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import numpy as np
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import time
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import os
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class CaptureCard:
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def __init__(self, device_index=0, width=1920, height=1080, save_dir="screenshots"):
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"""
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初始化采集卡(或摄像头)
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:param device_index: 设备索引号(一般是 0/1/2)
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:param width: 采集宽度
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:param height: 采集高度
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:param save_dir: 截图保存目录
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"""
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self.device_index = device_index
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self.width = width
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self.height = height
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self.cap = None
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self.region = None
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self.save_dir = save_dir
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os.makedirs(save_dir, exist_ok=True)
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def open(self):
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"""打开采集卡"""
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self.cap = cv2.VideoCapture(self.device_index, cv2.CAP_DSHOW)
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if not self.cap.isOpened():
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self.cap = cv2.VideoCapture(self.device_index)
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if not self.cap.isOpened():
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raise RuntimeError(f"无法打开采集设备 index={self.device_index}")
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self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
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self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
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print(f"采集卡已打开:{self.width}x{self.height}")
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def close(self):
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"""关闭采集卡"""
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if self.cap:
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self.cap.release()
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self.cap = None
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print("采集卡已关闭。")
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cv2.destroyAllWindows()
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def getDesktopImg(self):
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"""从采集卡获取一帧图像"""
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if self.cap is None:
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self.open()
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ret, frame = self.cap.read()
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if not ret:
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print("无法从采集卡读取帧")
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return None
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im_opencv = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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if self.region:
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left, top, right, bottom = self.region
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im_opencv = im_opencv[top:bottom, left:right]
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im_PIL = Image.fromarray(im_opencv)
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return [im_opencv, im_PIL]
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def preview(self):
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"""实时预览 + 每5秒自动截图"""
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if self.cap is None:
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self.open()
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print("按 'q' 退出实时预览")
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last_capture_time = time.time()
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screenshot_count = 0
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while True:
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ret, frame = self.cap.read()
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if not ret:
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print("无法读取视频帧")
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break
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if self.region:
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left, top, right, bottom = self.region
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frame = frame[top:bottom, left:right]
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# 显示视频
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cv2.imshow("CaptureCard Preview", frame)
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# 每5秒自动截图
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now = time.time()
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if now - last_capture_time >= 5:
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screenshot_count += 1
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filename = os.path.join(self.save_dir, f"screenshot_{screenshot_count}.jpg")
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cv2.imwrite(filename, frame)
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print(f"[截图] 已保存:{filename}")
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last_capture_time = now
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# 按 'q' 退出
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key = cv2.waitKey(1) & 0xFF
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if key == ord('q'):
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break
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self.close()
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if __name__ == "__main__":
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card = CaptureCard(device_index=0, width=1920, height=1080)
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card.preview()
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73
utils/get_image.py
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73
utils/get_image.py
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import time
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from PIL import Image
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import cv2
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# class GetImage:
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# def __init__(self, cam_index=0, width=1920, height=1080):
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# self.cap = cv2.VideoCapture(cam_index,cv2.CAP_DSHOW)
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#
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# if not self.cap.isOpened():
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# raise RuntimeError(f"无法打开摄像头 {cam_index}")
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# self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
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# self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
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# print(f"✅ 摄像头 {cam_index} 打开成功,分辨率 {width}x{height}")
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# def get_frame(self):
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# ret, im_opencv = self.cap.read()
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# im_opencv = cv2.cvtColor(im_opencv, cv2.COLOR_BGR2RGB) # rgb 修改通道数并转换图像
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# im_opencv = im_opencv[30:30+720, 0:1280]#裁剪尺寸
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# im_PIL = Image.fromarray(im_opencv) # 图像改成对象类型
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#
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# return [im_opencv, im_PIL]
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# def release(self):
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# self.cap.release()
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# cv2.destroyAllWindows()
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# print("🔚 摄像头已释放")
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# def __del__(self):
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# # 以防忘记手动释放
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# if hasattr(self, "cap") and self.cap.isOpened():
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# self.release()
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#
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# get_image = GetImage()
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#
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# if __name__ == '__main__':
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# while True:
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# if cv2.waitKey(1) & 0xFF == ord('q'):
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# break
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# a=get_image.get_frame()
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# cv2.imshow('image',a[0])
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# print(a[0].shape)
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#
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#
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# cv2.destroyAllWindows()
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import threading
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class GetImage:
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def __init__(self, cam_index=0, width=1920, height=1080):
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self.cap = cv2.VideoCapture(cam_index, cv2.CAP_DSHOW)
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self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
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self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
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self.frame = None
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self.running = True
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threading.Thread(target=self.update, daemon=True).start()
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def update(self):
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while self.running:
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ret, frame = self.cap.read()
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if ret:
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self.frame = frame
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def get_frame(self):
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if self.frame is None:
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return None
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im_opencv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2RGB)
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im_opencv = im_opencv[30:30+720, 0:1280]
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im_PIL = Image.fromarray(im_opencv)
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return [im_opencv, im_PIL]
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def release(self):
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self.running = False
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time.sleep(0.2)
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self.cap.release()
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cv2.destroyAllWindows()
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get_image = GetImage()
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57
utils/mouse.py
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57
utils/mouse.py
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import random
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import time
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import ch9329Comm
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import time
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import random
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import serial
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serial.ser = serial.Serial('COM6', 9600) # 开启串口
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mouse = ch9329Comm.mouse.DataComm(1920, 1080)
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def bezier_point(t, p0, p1, p2, p3):
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"""计算三次贝塞尔曲线上的点"""
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x = (1-t)**3 * p0[0] + 3*(1-t)**2*t*p1[0] + 3*(1-t)*t**2*p2[0] + t**3*p3[0]
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y = (1-t)**3 * p0[1] + 3*(1-t)**2*t*p1[1] + 3*(1-t)*t**2*p2[1] + t**3*p3[1]
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return (x, y)
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def move_mouse_bezier(mouse, start, end, duration=1, steps=120):
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"""
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用贝塞尔曲线模拟鼠标移动(安全版)
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"""
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x1, y1 = start
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x2, y2 = end
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# 控制点(轻微随机)
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ctrl1 = (x1 + (x2 - x1) * random.uniform(0.2, 0.4) + random.randint(-20, 20),
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y1 + (y2 - y1) * random.uniform(0.1, 0.4) + random.randint(-20, 20))
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ctrl2 = (x1 + (x2 - x1) * random.uniform(0.6, 0.8) + random.randint(-20, 20),
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y1 + (y2 - y1) * random.uniform(0.6, 0.9) + random.randint(-20, 20))
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# 生成轨迹
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points = [bezier_point(t, (x1, y1), ctrl1, ctrl2, (x2, y2)) for t in [i/steps for i in range(steps+1)]]
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delay = duration / steps
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for (x, y) in points:
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# 坐标裁剪,防止越界或负数
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x_safe = max(0, min(1919, int(x)))
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y_safe = max(0, min(1079, int(y)))
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mouse.send_data_absolute(x_safe, y_safe)
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time.sleep(delay * random.uniform(0.6, 1.0))
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# 最后一步确保到达终点
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x2_safe = max(0, min(1919, int(x2)))
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y2_safe = max(0, min(1079, int(y2)))
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mouse.send_data_absolute(x2_safe, y2_safe)
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class Mouse_guiji():
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def __init__(self):
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self.point=(0,0)
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def send_data_absolute(self, x, y,may=0):
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move_mouse_bezier(mouse, self.point, (x,y), duration=1, steps=120)
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if may == 1:#点击左
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mouse.click()
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elif may == 2:
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mouse.click1()#点击右
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self.point=(x,y)
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mouse_gui = Mouse_guiji()
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115
utils/shizi.py
Normal file
115
utils/shizi.py
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import ddddocr
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import cv2
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ocr = ddddocr.DdddOcr()
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def fuhuo(image):
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image = image[603:641, 460:577]
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image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
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# 将裁剪后的图像编码成二进制格式
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_, img_encoded = cv2.imencode('.png', image)
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# 将图像编码结果转换为字节流
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img_bytes = img_encoded.tobytes()
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result = ocr.classification(img_bytes)
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print(result)
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if result == "记录点复活" or result == "记灵点复活":
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return True
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else:
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return False
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def jieshu(image):
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image=image[623:623+41, 472:472+167]
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image=cv2.cvtColor(image,cv2.COLOR_RGB2BGR)
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# 将裁剪后的图像编码成二进制格式
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_, img_encoded = cv2.imencode('.png', image)
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# 将图像编码结果转换为字节流
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img_bytes = img_encoded.tobytes()
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result = ocr.classification(img_bytes)
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if result=="结束挑战":
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return True
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else:
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return False
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def tiaozhan(image):
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image = image[576:614, 1023:1138]
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image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
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# 将裁剪后的图像编码成二进制格式
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_, img_encoded = cv2.imencode('.png', image)
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# 将图像编码结果转换为字节流
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img_bytes = img_encoded.tobytes()
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result = ocr.classification(img_bytes)
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if result == "开启挑战":
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return True
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else:
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return False
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def tuichu(image):
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image = image[24:58, 569:669]
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image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
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# 将裁剪后的图像编码成二进制格式
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_, img_encoded = cv2.imencode('.png', image)
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# 将图像编码结果转换为字节流
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img_bytes = img_encoded.tobytes()
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result = ocr.classification(img_bytes)
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print(result)
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if result[1:] == "出挑战" or result[0:2] == "退出" :
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return True
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else:
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return False
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def tuwai(image):
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image = image[59:93, 1226:1275]
|
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image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
|
||||
# 将裁剪后的图像编码成二进制格式
|
||||
_, img_encoded = cv2.imencode('.png', image)
|
||||
# 将图像编码结果转换为字节流
|
||||
img_bytes = img_encoded.tobytes()
|
||||
result = ocr.classification(img_bytes)
|
||||
print(result)
|
||||
if result == "tap" or result=='tqp' or result=='top':
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
def daoying(image):
|
||||
image = image[260:289, 570:628]
|
||||
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
|
||||
# 将裁剪后的图像编码成二进制格式
|
||||
_, img_encoded = cv2.imencode('.png', image)
|
||||
# 将图像编码结果转换为字节流
|
||||
img_bytes = img_encoded.tobytes()
|
||||
result = ocr.classification(img_bytes)
|
||||
print(result)
|
||||
if result == "倒影" or result=="到影" :
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
def shuzi(image):
|
||||
image=image[50:91,610:666]
|
||||
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
|
||||
# 将裁剪后的图像编码成二进制格式
|
||||
_, img_encoded = cv2.imencode('.png', image)
|
||||
# 将图像编码结果转换为字节流
|
||||
img_bytes = img_encoded.tobytes()
|
||||
result = ocr.classification(img_bytes)
|
||||
print(result)
|
||||
if result=="40":
|
||||
return True
|
||||
|
||||
def test(image):
|
||||
# 将裁剪后的图像编码成二进制格式
|
||||
_, img_encoded = cv2.imencode('.png', image)
|
||||
# 将图像编码结果转换为字节流
|
||||
img_bytes = img_encoded.tobytes()
|
||||
result = ocr.classification(img_bytes)
|
||||
print(result)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
image=cv2.imread('10.21_820.jpg')
|
||||
shuzi(image)
|
||||
test(image)
|
||||
BIN
utils/城镇.jpg
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utils/城镇.jpg
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utils/开启挑战.jpg
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utils/开启挑战.jpg
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utils/结束挑战.jpg
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utils/结束挑战.jpg
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utils/记录点复活.jpg
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utils/记录点复活.jpg
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After Width: | Height: | Size: 3.2 KiB |
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utils/退出挑战.jpg
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utils/退出挑战.jpg
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After Width: | Height: | Size: 3.5 KiB |
Reference in New Issue
Block a user