110 lines
3.7 KiB
Python
110 lines
3.7 KiB
Python
import os
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import time
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import cv2
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import numpy as np
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from PIL import Image
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# 工具类
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class AiTools(object):
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@classmethod
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def find_image_in_image(
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cls,
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smallImageUrl,
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bigImageUrl,
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match_threshold=0.90,
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consecutive_required=3,
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scales=None
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):
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if scales is None:
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scales = [0.5, 0.75, 1.0, 1.25, 1.5]
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template = cv2.imread(smallImageUrl, cv2.IMREAD_COLOR)
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# if template is None:
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# raise Exception(f"❌ 无法读取模板 '{smallImageUrl}'")
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template_gray = cv2.cvtColor(template, cv2.COLOR_BGR2GRAY)
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cap = cv2.imread(bigImageUrl, cv2.IMREAD_COLOR)
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# if not cap.isOpened():
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# print(f"❌ 无法打开视频流: {bigImageUrl}")
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# return None
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detected_consecutive_frames = 0
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print("🚀 正在检测爱心图标...")
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while True:
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print("死了")
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ret, frame = cap.read()
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if not ret or frame is None:
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time.sleep(0.01)
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continue
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print("哈哈哈")
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frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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current_frame_has_match = False
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best_match_val = 0
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best_match_loc = None
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best_match_w_h = None
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print("aaaaaaaaaaaa")
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for scale in scales:
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resized_template = cv2.resize(template_gray, (0, 0), fx=scale, fy=scale)
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th, tw = resized_template.shape[:2]
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if th > frame_gray.shape[0] or tw > frame_gray.shape[1]:
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continue
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result = cv2.matchTemplate(frame_gray, resized_template, cv2.TM_CCOEFF_NORMED)
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_, max_val, _, max_loc = cv2.minMaxLoc(result)
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if max_val > best_match_val:
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best_match_val = max_val
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best_match_loc = max_loc
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best_match_w_h = (tw, th)
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if max_val >= match_threshold:
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current_frame_has_match = True
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print("break 了")
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break
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print("bbbbbbbbbbbbbbbbbbbbbb")
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if current_frame_has_match:
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print("111111")
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detected_consecutive_frames += 1
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last_detection_info = (best_match_loc, best_match_w_h, best_match_val)
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else:
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print("2222222")
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detected_consecutive_frames = 0
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last_detection_info = None
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if detected_consecutive_frames >= consecutive_required and last_detection_info:
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print("333333333")
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top_left, (w, h), match_val = last_detection_info
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center_x = top_left[0] + w // 2
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center_y = top_left[1] + h // 2
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print(f"🎯 成功识别爱心图标: 中心坐标=({center_x}, {center_y}), 匹配度={match_val:.4f}")
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return center_y, center_y
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else:
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return -1, -1
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cap.release()
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print("释放了")
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return -1, -1
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@classmethod
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def imagePath(cls, name):
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current_file_path = os.path.abspath(__file__)
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# 获取当前文件所在的目录（即script目录）
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current_dir = os.path.dirname(current_file_path)
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# 由于script目录位于项目根目录下一级，因此需要向上一级目录移动两次
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project_root = os.path.abspath(os.path.join(current_dir, '..'))
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# 构建资源文件的完整路径，向上两级目录，然后进入 resources 目录
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resource_path = os.path.abspath(os.path.join(project_root, 'resources', name + ".png")).replace('/', '\\\\')
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return resource_path
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