164 lines
5.7 KiB
Python
164 lines
5.7 KiB
Python
# coding=utf-8
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import asyncio
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import logging
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import os
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import sys
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import time
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import cv2
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import uiautomator2 as u2
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# 添加项目根目录到 sys.path
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project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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if project_root not in sys.path:
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sys.path.append(project_root)
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from WeiXin.WxUtil import get_vlm_analysis
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from Util.EasyOcrKit import EasyOcrKit
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# 配置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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logger = logging.getLogger("T6_Debug")
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async def main():
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logger.info("🚀 T6 VLM 语音坐标调试工具启动...")
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# 连接设备
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try:
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d = u2.connect()
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logger.info(f"设备已连接: {d.info.get('serial')}")
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except Exception as e:
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logger.error(f"设备连接失败: {e}")
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return
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# 截图目录
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screenshots_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "Screenshots")
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if not os.path.exists(screenshots_dir):
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os.makedirs(screenshots_dir)
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# 截图
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screenshot_path = os.path.join(screenshots_dir, "t6_debug_temp.jpg")
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logger.info("📸 正在截图...")
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d.screenshot(screenshot_path)
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# 调用 VLM 分析
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logger.info("🧠 正在调用 VLM 分析图片...")
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result_data = await get_vlm_analysis(screenshot_path)
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if not result_data:
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logger.error("❌ VLM 分析返回为空")
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return
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logger.info(f"VLM 返回结果: {result_data}")
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# 读取图片用于绘制
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img = cv2.imread(screenshot_path)
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if img is None:
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logger.error("❌ 无法读取截图文件")
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return
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messages = result_data.get("messages", [])
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voice_count = 0
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for msg in messages:
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msg_type = msg.get("type")
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content = msg.get("content")
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coords = msg.get("coordinates") or msg.get("center")
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if not coords:
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continue
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x, y = coords
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if msg_type == "voice":
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voice_count += 1
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logger.info(f"🎤 发现语音消息: {content}, 坐标: ({x}, {y})")
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# 绘制绿框 (语音)
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w, h = 300, 80
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top_left = (int(x - w/2), int(y - h/2))
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bottom_right = (int(x + w/2), int(y + h/2))
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cv2.rectangle(img, top_left, bottom_right, (0, 255, 0), 3)
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cv2.circle(img, (int(x), int(y)), 5, (0, 0, 255), -1)
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label = f"Voice ({x},{y})"
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cv2.putText(img, label, (top_left[0], top_left[1] - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2)
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# 保存结果图片
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output_path = os.path.join(screenshots_dir, "t6_debug_result.jpg")
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cv2.imwrite(output_path, img)
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logger.info(f"✅ 结果已保存至: {output_path}")
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logger.info(f"共标记了 {voice_count} 条语音消息。请检查图片是否准确。")
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# --- 验证转文字功能 (处理最后一条未转换语音) ---
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logger.info("="*30)
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logger.info("🔍 开始验证“转文字”功能 (仅针对最后一条未转换语音)...")
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# 筛选未转换的语音
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unconverted_voices = []
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for msg in messages:
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if msg.get("type") == "voice" and msg.get("status") == "unconverted":
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coords = msg.get("coordinates") or msg.get("center")
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if coords:
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msg["coordinates"] = coords
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unconverted_voices.append(msg)
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if not unconverted_voices:
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logger.info("⚠️ 没有发现未转换的语音消息，跳过验证。")
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else:
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last_voice = unconverted_voices[-1]
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vx, vy = last_voice['coordinates']
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content = last_voice.get('content', '0"')
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logger.info(f"🎯 目标语音: {content}, 坐标: ({vx}, {vy})")
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# 1. 长按
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logger.info(f"👆 长按语音消息...")
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d.long_click(vx, vy, 1.5)
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time.sleep(1.0)
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# 2. 截图菜单
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menu_shot_path = os.path.join(screenshots_dir, "t6_menu_shot.jpg")
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logger.info(f"📸 截取菜单: {menu_shot_path}")
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d.screenshot(menu_shot_path)
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# 3. OCR 识别
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logger.info("🧠 正在进行 OCR 识别菜单...")
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ocr_kit = EasyOcrKit()
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ocr_results = ocr_kit.read_text(menu_shot_path)
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convert_btn_center = None
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for bbox, text, conf in ocr_results:
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if "转文字" in text or "转换为文字" in text:
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c_x = int((bbox[0][0] + bbox[2][0]) / 2)
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c_y = int((bbox[0][1] + bbox[2][1]) / 2)
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convert_btn_center = (c_x, c_y)
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logger.info(f"✅ OCR 找到 '{text}' 按钮: {convert_btn_center}")
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break
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if convert_btn_center:
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# 4. 点击转文字
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logger.info(f"👆 点击转文字按钮: {convert_btn_center}")
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d.click(convert_btn_center[0], convert_btn_center[1])
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# 5. 动态等待
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duration_str = content.replace('"', '').strip()
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try:
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duration = int(duration_str)
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except:
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duration = 10
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wait_seconds = max(2, duration / 5.0)
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logger.info(f"⏳ 语音时长 {duration}s，模拟等待 {wait_seconds:.1f}s...")
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time.sleep(wait_seconds)
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logger.info("✅ 流程执行完毕！请检查手机屏幕是否已开始转换。")
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else:
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logger.error("❌ OCR 未找到 '转文字' 按钮！")
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# 点击空白处关闭
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d.click(vx + 200, vy)
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if __name__ == "__main__":
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if sys.platform.startswith('win'):
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asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
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asyncio.run(main())
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