From b49dd9bc1b2ffc74f1843602bb5d9f090f73c32e Mon Sep 17 00:00:00 2001 From: HuangHai <10402852@qq.com> Date: Thu, 15 Jan 2026 09:16:20 +0800 Subject: [PATCH] 'commit' --- Apps/TeLaiDian/Crawler.py | 61 +++++------ Apps/TeLaiDian/ReadImageKit.py | 102 ++++++++++++++++++ .../__pycache__/Crawler.cpython-310.pyc | Bin 16259 -> 16300 bytes .../__pycache__/ReadImageKit.cpython-310.pyc | Bin 14780 -> 18631 bytes 4 files changed, 130 insertions(+), 33 deletions(-) diff --git a/Apps/TeLaiDian/Crawler.py b/Apps/TeLaiDian/Crawler.py index aae575d..abeddd3 100644 --- a/Apps/TeLaiDian/Crawler.py +++ b/Apps/TeLaiDian/Crawler.py @@ -298,86 +298,81 @@ class TeLaiDianCrawler(BaseCrawler): w, h = d.window_size() # 1. 增加等待时间，确保页面加载完成 - logger.info(f"[详情页] 等待 {WAIT_DETAIL_PAGE_LOAD + 2}s 确保页面稳定 (根据要求多等会)...") - await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD + 2) + logger.info(f"[详情页] 等待 {WAIT_DETAIL_PAGE_LOAD + 1}s 确保页面稳定...") + await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD + 1) - # 2. 向上滑动一部分屏 (从屏幕底部的 85% 划到顶部的 15%) - # [优化] 避免滑过头，从全屏改为 0.7 屏幕左右 - logger.info("[详情页] 执行向上滑动操作 (y: 85% -> 15%)") - d.swipe(w // 2, int(h * 0.85), w // 2, int(h * 0.15), duration=0.8) - await asyncio.sleep(2.0) # 滑动后再次等待稳定 + # 2. 向上滑动大一些，确保“全部时段”露出来 + logger.info("[详情页] 执行大范围向上滑动 (y: 90% -> 10%)，确保显示全部时段") + d.swipe(w // 2, int(h * 0.9), w // 2, int(h * 0.1), duration=1.0) + await asyncio.sleep(2.5) # 滑动后等待稳定 + + # 3. 截图并识别 (纯 OCR 流程) + final_screen_path = take_screenshot(d, f"tld_detail_ocr_input_{int(time.time())}.jpg") + logger.info(f"[详情页] 已截取 OCR 识别用图: {final_screen_path}") - # 3. 截图并识别 - final_screen_path = take_screenshot(d, f"tld_detail_vlm_input_{int(time.time())}.jpg") - logger.info(f"[详情页] 已截取 VLM 识别用图: {final_screen_path}") - - logger.info("[详情页] 优先使用 VLM 识别顶部“价格”标签和价格入口") - price_tab_screen = final_screen_path entrance_clicked = False - try: - # 1. 尝试使用 VLM 寻找顶部“价格”标签 - tab_data = await self.read_image_kit.find_price_tab_vlm(final_screen_path) + # 1. 使用 OCR 寻找顶部“价格”标签 + tab_data = await self.read_image_kit.find_price_tab_ocr(final_screen_path) tab_x, tab_y = None, None if tab_data.get("found") and tab_data.get("point"): p = tab_data["point"] tab_x = int(p[0] * w / 1000) tab_y = int(p[1] * h / 1000) - logger.info(f"[详情页] VLM 成功找到价格标签: 归一化{p} -> 像素({tab_x}, {tab_y})") + logger.info(f"[详情页] OCR 成功找到价格标签: 归一化{p} -> 像素({tab_x}, {tab_y})") else: tab_x = int(PRICE_TAB_X_NORM * w / 1000) tab_y = int(PRICE_TAB_Y_NORM * h / 1000) - logger.warning(f"[详情页] VLM 未找到价格标签，使用固定坐标兜底: 像素({tab_x}, {tab_y})") + logger.warning(f"[详情页] OCR 未找到价格标签，使用固定坐标兜底: 像素({tab_x}, {tab_y})") logger.info(f"[详情页] 正在点击价格标签...") d.click(tab_x, tab_y) - await asyncio.sleep(2.0) # 点击标签后多等会 + await asyncio.sleep(2.5) # 点击标签后等待 price_tab_screen = take_screenshot(d, f"tld_detail_after_price_tab_{int(time.time())}.jpg") logger.info(f"[详情页] 点击价格标签后的界面截图已保存: {price_tab_screen}") - # 2. 尝试使用 VLM 寻找价格入口 (重点识别“全部时段 >”) - entry_data = await self.read_image_kit.find_price_entrance_vlm(price_tab_screen) + # 2. 寻找并点击“全部时段”入口 (纯 OCR 识别) + entry_data = await self.read_image_kit.find_price_entrance_ocr(price_tab_screen) entry_x, entry_y = None, None if entry_data.get("found") and entry_data.get("point"): p = entry_data["point"] - # 安全校验：严禁点击 y > 850 (85%) 的区域，那是底部浮动条 - if p[1] > 850: - logger.warning(f"[详情页] VLM 虽返回坐标 {p}，但 Y 轴过大 (疑似底部浮动条)，强制判定为未找到。") + # 安全校验：严禁点击 y > 900 的区域，那是底部浮动条 + if p[1] > 900: + logger.warning(f"[详情页] OCR 返回坐标 {p} 偏低 (疑似底部浮动条)，尝试使用固定坐标兜底") entry_x = int(PRICE_ENTRY_X_NORM * w / 1000) entry_y = int(PRICE_ENTRY_Y_NORM * h / 1000) else: entry_x = int(p[0] * w / 1000) entry_y = int(p[1] * h / 1000) - logger.info(f"[详情页] VLM 成功找到价格入口 (匹配全部时段标识): 归一化{p} -> 像素({entry_x}, {entry_y})，原因: {entry_data.get('reason')}") + logger.info(f"[详情页] OCR 成功找到价格入口: 归一化{p} -> 像素({entry_x}, {entry_y})") else: entry_x = int(PRICE_ENTRY_X_NORM * w / 1000) entry_y = int(PRICE_ENTRY_Y_NORM * h / 1000) - logger.warning(f"[详情页] VLM 未找到价格入口，使用固定坐标兜底: 像素({entry_x}, {entry_y})") + logger.warning(f"[详情页] OCR 未找到价格入口，使用固定坐标兜底: 像素({entry_x}, {entry_y})") click_x = max(5, min(w - 5, entry_x)) click_y = max(5, min(h - 5, entry_y)) - debug_click_path = price_tab_screen.replace( - ".jpg", - f"_click_tab_{tab_x}_{tab_y}_entry_{click_x}_{click_y}.jpg" - ) + # 绘制诊断图 + debug_click_path = price_tab_screen.replace(".jpg", f"_click_diag.jpg") try: img = read_image(price_tab_screen) if img is not None: + # 绘制两个点击位置 cv2.circle(img, (tab_x, tab_y), 20, (0, 0, 255), -1) - cv2.circle(img, (click_x, click_y), 20, (0, 0, 255), -1) + cv2.circle(img, (click_x, click_y), 20, (0, 255, 0), -1) save_image(debug_click_path, img) - logger.info(f"[详情页] 已生成价格点击诊断红点图: {debug_click_path}") + logger.info(f"[详情页] 已生成 OCR 点击诊断图 (红点:价格标签, 绿点:入口): {debug_click_path}") except Exception as e: logger.error(f"[详情页] 生成诊断图片失败: {e}") logger.info(f"[详情页] 正在点击电价入口...") d.click(click_x, click_y) entrance_clicked = True - await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD) + await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD + 1) except Exception as e: logger.error(f"[详情页] 识别或点击价格入口失败: {e}") diff --git a/Apps/TeLaiDian/ReadImageKit.py b/Apps/TeLaiDian/ReadImageKit.py index 7fcaf9f..dc24b27 100644 --- a/Apps/TeLaiDian/ReadImageKit.py +++ b/Apps/TeLaiDian/ReadImageKit.py @@ -140,6 +140,108 @@ class ReadImageKit: logger.error(f"VLM 寻找价格入口失败: {e}") return {"found": False} + async def find_price_tab_ocr(self, image_path): + """ + 使用 OCR 在详情页顶部标签栏中寻找“价格”标签 + 不再使用 VLM + """ + from Apps.TeLaiDian.Kit import draw_rectangles + img = read_image(image_path) + if img is None: + return {"found": False} + + h, w = img.shape[:2] + reader = get_easyocr_reader(gpu=True) + + # 限制只在顶部 30% 区域查找标签 + roi = img[0:int(h*0.3), :] + results = reader.read_text(roi) + + for (quad, text, prob) in results: + if '价格' in text and prob > 0.3: + # 转换坐标 (加上 ROI 的偏移，这里 y 偏移是 0) + res = reader.get_normalized_rect(quad, w, h) + center_x = (res[0] + res[2]) // 2 + center_y = (res[1] + res[3]) // 2 + + # 绘制诊断图 + actual_p = [int(center_x * w / 1000), int(center_y * h / 1000)] + bbox = [int(res[0] * w / 1000), int(res[1] * h / 1000), int(res[2] * w / 1000), int(res[3] * h / 1000)] + draw_rectangles(image_path, bboxes=[bbox], click_points=[actual_p]) + logger.info(f"[OCR] 已定位顶部价格标签并保存诊断图: {image_path.replace('.jpg', '_tab_vl.jpg')}") + + return { + "found": True, + "reason": f"OCR 定位到‘{text}’", + "point": [center_x, center_y] + } + + logger.warning(f"[OCR] 未能在顶部区域定位到‘价格’标签") + return {"found": False} + + async def find_price_tab_ocr(self, image_path): + """ + 使用 OCR 在详情页寻找顶部“价格”标签 + """ + img = read_image(image_path) + if img is None: + return {"found": False} + h, w = img.shape[:2] + + from Util.EasyOcrKit import get_easyocr_reader + reader = get_easyocr_reader(gpu=True) + + # 顶部标签栏通常在屏幕上部 10%-30% 区域 + # 我们先识别所有文字，然后过滤出“价格” + results = reader.read_text(img) + for (quad, text, prob) in results: + if "价格" in text and prob > 0.3: + # 获取中心点 + rect = reader.get_normalized_rect(quad, w, h) + center_x = (rect[0] + rect[2]) // 2 + center_y = (rect[1] + rect[3]) // 2 + + # 校验位置：必须在屏幕上半部分 + if center_y < 500: + logger.info(f"[OCR] 找到顶部价格标签: '{text}', 置信度: {prob:.4f}, 坐标: [{center_x}, {center_y}]") + return { + "found": True, + "point": [center_x, center_y] + } + + return {"found": False} + + async def find_price_entrance_ocr(self, image_path): + """ + 使用 OCR 在详情页寻找价格入口 (全部时段 >) + 不再使用 VLM 和 掩码 CV + """ + container_norm = detect_price_info_container_cv(image_path) + if container_norm: + # 找到矩形框 [x1, y1, x2, y2] + x1, y1, x2, y2 = container_norm + # 计算中心点 + center_x = (x1 + x2) // 2 + center_y = (y1 + y2) // 2 + + # 绘制诊断图 (复用之前的逻辑) + img = read_image(image_path) + if img is not None: + h, w = img.shape[:2] + actual_p = [int(center_x * w / 1000), int(center_y * h / 1000)] + bbox = [int(x1 * w / 1000), int(y1 * h / 1000), int(x2 * w / 1000), int(y2 * h / 1000)] + draw_rectangles(image_path, bboxes=[bbox], click_points=[actual_p]) + logger.info(f"[OCR] 已定位价格入口并保存诊断图: {image_path.replace('.jpg', '_vl.jpg')}") + + return { + "found": True, + "reason": "OCR 精准定位到‘全部时段’文字", + "point": [center_x, center_y] + } + + logger.warning(f"[OCR] 未能在页面中定位到‘全部时段’") + return {"found": False} + async def find_close_button_vlm(self, image_path): """ 使用 VLM 在页面上寻找关闭按钮（用于清理广告弹窗） diff --git a/Apps/TelaiDian/__pycache__/Crawler.cpython-310.pyc b/Apps/TelaiDian/__pycache__/Crawler.cpython-310.pyc index 26e8e2a131a655b18690285a31dee14ada33b92e..a72734a496bd6b998c1218813c5f5bead4527c65 100644 GIT binary patch delta 3057 zcmZ`*Yj9J?6~22V*@~Z%{E{pQUHL7rWz562Y=dl|1kwh~tAI-)gjU!xMzUAeVeHvk zIZ@p-3^XE3NQ1|Xlu+U}0h)1W!y_=${!B7WJJZh8ZU0%a>15hw`lpkbOnUYT8@q+; z@u#!roIU&Pw?|hSkG&r&iWC;+3GfVh2SPWGe^At)kNRg{$Tt^Pc7m65acJk@;n2;Y zhs{*ld$)l(rwg6-_Xp>6r~PtZU@mvSAN9*JA-z177m9|$QQ0331n0Ck6p+al?$!>4 zqVk+h9vvPE&S{2%Ve&LDx{H-rz2!T&`7I7R)!Y-2$Pn4e2CXi%on5rlySc zJ79Y@=i5B*JM5}$G$+8#-dU$z5z#^RmcyCP*UA$2vQHdcXpHHlLulLV^U`G$Ggb;R zqWRcVD#Q`Z!%O25KE|cE?7R*MvME`D%Ts8#fc3is7z-5P3K_{_QcOYKlz_!)OMH_Y{<6=YF72R3AS2OYKqoZ-R!!$}B4HcQEni(j zuAs5i1yOPZ)!R8kYyg2k&Xu?#H% z39{P;JG*VzG;9#ppVERbzkwQN+@NmGHLX!uA=$cOJEgF)ZG{|V;qJ!>2U*#=D>Exq zf@>ctSE?#kmQ{{@UEPxFr0R%mu4#^$k`655rj)3d$KA3-O>i0(YQg$Zln}{o*_o`O zszfJ6?8eP_eTuhF)>}?1RBy{eZ#6YjOPou|n`Q$wF9~#52wSy+oR<*Cf=Ey*kuY8a zIr(@a^Vdqd)bvfu=K*E;dEm`TA@5TebgK}S`V0vxioLn2SSu8B<`*V(#IE*p8#`ZX ziM3Pf5)HNMOCMEI*Y)sqv0kxZyJE*3${K1_9C8g^6GuCQ=ME~8TB~zaA9PU(+m+b9q%~5)T%2sk`PBeVdv}Cd9J8rcm5CAnq{&LaxHCm zL=G5LtBf%FvaSLJ*i-e@sE9Sydz+uI60K30*U%bTdrC-XqOG(pp(ShCRJ{XjW_Rix zPyZfvm5+Prx+Ospnvwf-9b`4obs*_J#RxBvMp^}SkJ3bq@KxEDLbNIS34FA~Mvctb zP!h926Exxjkm*$1Jd?UpNYztI%zVbfv5?S4P0M4uTEk3@)D3TxChG12rX&9WMM3?M zztTp?uA^1SdTQi{557Nfj?0au9ow00EH>NF89PK>$)*&%Boo?^XJ|ceu_(=Q!C+ys zh&IEUO-n|`^>RV7n2&gSLf%mX`A9gb+I$>tq;)W}Kyg8}#uVrK;)=R2JhtvMuUogO z@Z^fZlTdi_j6kb^!sm>+La3O1?ef9_Zdu!j9BgcD1O;Xvti6h2>){t;v;rV1Eu^l` z-=BVvy7^%G?S+}y^!3Ybw|jIy#J;z9<7y^838Ckt%q#CMrp~3Wyt{ZVo}T(JowzXn z(b>$M3+b~nQo~q>M#EVBDJBS}lg$958v$1C0cNu=n>x$~d2sh*g4^A{ zJsA3d2BP-=k4lU8FQ%t{nx0N%k}pf6-H;)rUwn1`;~z^63zsg;-@Ti@{W{<2&Fdga zW;(@%NdIzr@y6@ynA=?X1Ue

B*m^Uwx-TN`L&?{6`b%bC({=E#BPO=7TlIi+zEi zP~emghy4BS!Qp;#2)yLG9F73EG+6}>a|hRAw3q#(+3b&z5ZT9Cx=NUB(^F_}wre6WF27;*RjkMe zhGoL&}*{#-QMA(B?hT=?VtFmS9Vi4;yLT&$$ zFB%}hVAwb8mj~EqZEmCC5ua>`ebwg3`97}}V~%z!-03>okDv*5vHcbF3|r%|V%legfoB=m2#zw3169`2~; zFvfusA@6Z`pZ&ROw|u5DkS017RWI0c+QDcfOl0=AE&tlv10fRP@m&9jDA$h+@=?Jsi3|nRxyEeXe256@K?gvK23~Elb9-CG@;oUS!PT9fVoqgv|-7Q!0d?vE@awpPryL_l=!6 zG{E2@xP+z#4^r9^&m_Qr3xu*wrZer2x~0vpj`}ZS$&l%E`PKaCa?Ud{m=~be?V3 zMi8Sq?|`SfE2N1j(aKIfY%q0J-*Jas8;lL%F;SiYx}(cIjWO` zgZ*7mO@Eh9dJ}`TF>}5vXETah5VoqehyDJ3$;Eo}9b^-`kiUhjXMfH=Ms~1wt=p5f zq1|?N)f!9^QEZ-s1QZd&8@%8Mt_7*b2^uiwEocX>mNtz9LoJ?q{m}TO| z2~80bYa_13Y|%8KBb;muXN%?tY2!rwn;fh;O2ix%Dajs9leJ-;xQwP<;->frfjwO3 zqD0e_bkU+1LS)2Gx!$C(nWiOTC>dhj_jn~!$)XuyjhG)HAtG&6Wotqftrku(0z0E< zvv4%U#EHxEft8Y}>g=FP9bHsrsfh(@yu^tGG!w9pW&svWB_kQ1RVH%I(jf9On!3b4 zS1exQsaq_lL@kJfEi{v6Mfk;*WGwATDfYyYu2LzZ>4~1G)#uT4HdJKu{E=ou#S2w} z{Msr_FREN5X;vebKQGdx7HI}_s4*)d1TyMbS#fQ0Aw_)=a~Ic)ribk!FIKCiIn}1r z&>Yxx(q(}B)Eg0A$sKXZ0!@eRTBt?T2T6#RTIGUpAyrF0!iy`!T5)9rr(r>xLzgYl z7SUX48OPS(1gxUDiR$zAalU*lC#Qt?;e&)z@(4F#0HaiKHFH-K*wK8=Vt*kl_E)S^ z3^;aj7HcmtXPjN)SI?f53u)94(n;CsEH*&jEu)PzKao?N*rvp^J?GSnNkqM36>W-5 zY*Ciee8nyo)8*r26L)a8BB-&}!l3YBJ_3`b_DE2Bq#NhK7OAeI_QfnE)GoT zv9s1PSIuj3(_)oo|M@~f1^IhU9>XMl#piVHmwA! z<+Kvo+O8Pk5U8SsAh#;j)Cj}h9wD@P;TITcC8Mf+=eZVs7ql<~RpPtgSD-l2f;uBa z?XXrdpg*p6gMtfb1NwwQw5iSpYNSp$A*!jf1&9y*6^;OSAVXi%DzLWF!f+WiVoN|b ziGFw zKsZftfOk~{nH_s6PCv$}Wd9TA_)Bq)L!9HsI9dpe`8E5@;UzkjRpBC9)?U#}%xt2< zPsEvjRa_;byWwOH)&K;A`N;LT$5YQDx1UXYIzK%VyFMwD$HVvH6W5G=I~vD4FYUyj8;{zdHO z**Ke+dw5wWA8ryFSCk0V>x9}BC64aj&CbrQnVtQMt9$Y%__^njI`BR79zp{^hgt3y z-C~#Q@%Foq_7AwdzQLgE4wkcBmARwB-fi23r#F5WJNfzih3VL(M@>TTtyf6RJ@_Pc z;^f@J$6)c2{jWa}@Xgp%Jp9r8wMVh@XBITE6F-lg{pl75zhg&K zcf=p`iRxQeB1mlw!U`6yHfewYyIb9qy9ZRkwpWtl<{QpmnSwk1&&IYI%PyfjcIMu* z6BDr$(?BQw<2&)|w}A-Mz4UVexyr6Qa5IC$ez^hCx=<}%CCv%)~YI^ z$18(_Nbj(nF0;PhGjLe+tozeU`|2KIesLFiaj$4%zh6_l+Ye6CAi}~m2Bn2t5=wYU zk~Sf@5Hb-KuQ$>UVA)|j;`NE{LCM?Mr4|oU!?x6wB&|o=&1|U7qCwR}-Kt_4RmliJ zgrf+0gk}T{!f`fNS3?5KRL{tVY`VTMaZCC`eQxH9B!Nz;tINmY^-fmWusmrLUB}p4 z4f$}jI?}M8yw4stoFZ?twnl5xIo#a9`Wnkp6cAHjq5^l=<;H#b6kbc<%d>wrmI@|f zA{8W)&m_6T#G63P6D!gFo7d_|3dteN)s#a_Gkf8XC*QK~ns*sL$G`;u4qmdM9A+IY z0{I6!-ZGH46BT6$BM6vT`U2q^P`4ON(|uw!p8_^1WYeoXPaGzlK1PinMC`a{{q`=aNz&| diff --git a/Apps/TelaiDian/__pycache__/ReadImageKit.cpython-310.pyc b/Apps/TelaiDian/__pycache__/ReadImageKit.cpython-310.pyc index 9f46d8fc2988f26f1c57f7471be71972a52b54f5..13622b7e172754990b5e005dc918522418bc1703 100644 GIT binary patch delta 6247 zcmZ`-Yj6`+mhRi#l3Gv8vSbVLKv}{=#_{rouq@e3LIS&lOagg1uo~ejj6k+EEy-X{ zYa}3k0ZvRhAw2A0=RwS7!6YnT-dnXlwrXm(GF4NxKYDBTN1~Rj*{WrJ%=}61%2%sS_`UJmzNjy9()Bp``;*Ilv8CPJ;wBvB zs2Hnl_q2H0>sspCy)9nCMO@T$l(hI>=BSyP-s9kjZ>gtb2N$#yair}*qM6^^_R8Nx zlR@$1ZJ_Nm@`y zT2y%Xc#^O>lVYNLipa+m(|(@vROsdBal81mIc-S_3Qxs(oMQ39raZ>M2okF^L!G%? zXJvK5j9!K*+E}G!mZDve6q_RXIV#NO8o0DWA!8zysCArAJE=(dm?`a2Ok?J8E?uLz z#w{sHht<_6o^g_{ zOS;Eul{zSS74Mjby2r^dktJ5Hohj4Wd0Zy#o4vJ6ZLZDr&E8ztF&~|^wQYR5Ua3bd z>hW_>f>v6`O02G-T-U(0iRp%9okEmMLmN@*+X(dz38i=Ul{UJ5oG%-lP$BWeFH!61$ML2?jGGxZJHTA=jH-MwG< zXhMC)Evd_`XEPeNU9N+6nV|5Z@PQ}_Sb7XZkE`TBdpZv_?~k_y1*Tg3UsS+O;CHq} zxC=b2J=_*at%Is}UwCtOK)>;A{_|}9+Hrm0O78ZJ{Ma4+@=g8BgnsjS?*6EL>2%@t z{d{J;Z+h}r{?sM?+`SEf)PF!{TVvz&SAEl84Nl+d)sJ0lYxC%?~*>L+gL=g}wdU_{l#MzRsK~+`6w1^yQ{*={GLuA6(5%eW8zj!nAJ``-cigZbEDR(_xqu z6ms{z(ua;Qg_95N4Cq5wVLtt?st*pqtT0)AFsqMD6wba^ID7?`IDPa){>-E?>w`Ok zFl+sf-`Y|Kr43Fc5dGpr9>&rQ9b zfB(bcnJ?IkWu+C(0j5{DaJZNq%pboP=niZOtY5P{fG^LE6g%J%=-+&x-~2c~lGSg0 z3>yONffZ{O1(;Iiys_=&abXi?k6Z4Pzjj$aHjy74XA3Dm6|-mcsVQT>;IQ+9Ul+y> z>%F~&kFMc)pBOBDco{YWUI~^ueg7l<+^2f)b$xUg_VI`8t4GQ+uWAnH7mnmV9Vs2- zrPE+3&~tk7M()mOy>|c&hn+CILB-rk)_c-8VfEMb8`U?=%buD3>hog%vE1D;W5>br zbGNg(n*%Ul{`90ie4#uV*o)fYdO|(z+Fmc$g7wKB6!jpAOR?lvYipLN&(}PY3D(PI ztTCZjh~jA!OF(EsYu8FmZ0(G9YgQR(HQdn_i)dmD*i`d8ACD)RcSg2_qc29o9nHYO z@5gsd}c7L~Dzy zE7opcPbeNv?vqzw&y^@vVR!z}3XSiE>(ENLuWWI*rerzNF%uRXS_upv4Yy(6t^4HX zpbJnxRz%y|jF)J_v7SNEjN;ExEJv{##TpcAQB+g>do@qJ(E^oxRx*nO{=CFX#6!HL zzgu*O5|PM!_&bP=xQQr;gomH>C%)dx>ihy~*r3-^(ge~^%)DFuRn5i>o}vU73m%RD z2p=Yt05fy#5Iz8%@GNK$6oCpUPObySHANv(QiT0bL(Qe&K}?&HBDGLyh@{P+OOhr< zq*gD45WNs$V34sF!i=;X=~b+wo{v8>*C}aik(^yh;TPU zIAB#^m~jCD2L~k(S~!pp8z5|(&!wI4WM_4ba-9pNbt)!^RGb);z!UKM%oC7n4b&JT z&FExM$rz}t$ZC+6XOs*bn5JqlG3{1hZxlC>Zw-*Ii;=H1W~DVizBY{XD&z}0<56r7 zden^yus~NEPrV}o&k=6<4({h`lhT--`Y=+N+1_A%Dh7vAc6ftn1FydDy82(jx=f{h zYDn)JDz!qyT5c%ODf5Qy%vE1v+`RK5(S){ms<4Xve)HTP&`S+uW^65QfM9k>FhohA6Bx7RNB#~;VPvAnCM_Xx^+3itU?f0ESW3_#zW}`r94MoY z=4p#0Loh>kXR927sc1xIh=d3frlDlyP*STy9R!AOEZP&Hpw^nK!X1WPmV;qA(-G}x z3)WVE#hC0Nw7?gFSu{cJjA|A+l1Rmp2~GTYDoizz%_qj?&OOi`NoZ0l;0WXrhsvey zDom(?19&wp^I5&&6>W4k48x#&4leNjD&UAb=81Oe+{l z@cR)>#1cvf5QdwmImWjOX^iVlWyCO#L5c#XU{Nf93R?gaB!mTORjdFCam7Y$019yc z1ruZl8Bq}c73_c&CU8nS2F!p8BA^1K2MiVL)IbHSb1F{iJOINa0aG9cuwo7XL%Pq2 zv{rGzlLvDJa84`pK?|fBPUfOKx+r+)(wP?u`cf}*+>*H*GXOR^J$WI26ylg`C5HXf z?63H0wHwa3=TBk#cFKPZQho)+HWU~%GdGO>9`HDY)K>C^!F%94h9gva--f`F6dVh; zq$vOa5=5)|tqU6hJwo&9y{QbcWmCWiA~pox?ctjOKa$-+zQW%@slw7)%^S&Rta&py z%B!t1k}ob%ehtOzD9SV(bXD2^Y|}UT>_qi984b_RfH~Vl7x0^5%#yGeSPsniPoQIZ*hV=EbOsa6aEbqcQniiBDTUu9 zrokH1CS)tc1ja+aP%MxPnoDJ=l+%F)vUIs!v9fd-_>85?Kv|H#Srj|ai@?Z6z-)Ks z3CP9)?Shi2RuC%+&}f>~*<5LZ)Xtd{fn1zGE)F0Uk&z1|%G3npVu8;VmMU_Agc=qi zfyLTJgdJScG$v6yvt;=E@Fezn~A zvQ)+BS^O&RfVx@c{~{`FM)48~fCx_Bf}&#M4|zx>-g9!`D5cLi&_!#g!e8J7IottX zoB-he4H^>||Dv^v;0^F662x^L5+EB(u+9UloBxQQuKuQGp#a^~kas?DU-i1T2@C3Q zNdPI;$vKN|8?er=X6l;En5WB|)NksR`kugIBZ?{qRsXwgKKX-c^~Pb;9`7&a9+iQ{ zUmBx&{VU01>dXF(tLGdLlr(SazDVnV5KwD-DBc-Q#X}H?FMyTG>#yGM^Wxk8Z^+NG z4u(lA*tb++(p<6jBf)j;6Z81Ze59!-IWCx0H~f= z~dsxueVh^__ zQ{h->4}56T_&8qObK#TvyS3YVC$Re?2J+gvdE_6}1M9vcF7+?gFUr)Q);bhhQS3$$ zMiD`=55)l#M^GF^aRx;NIamp!6xjv>jV>`Cgv3FpDoBf^*QF&=Kw2O*LisUitD_;< zpjl#_ZEX;1%Uw9VCM3EOasW#5LG?e^H#gySw%A#~VtlQa(HyG6e`b2@z|87To?RGZ dC&mto9S3t|T+JiPRNsGgvE+w{SrR<_{{eJKI%og@ delta 2475 zcmZ{mX;2$g9KiQ&5|WS*NC;5r!I8E!0b;q7j@4;tk*WpJUK)=yu#rYX!fetCbsRzq z7J6{_+6tA9R4J`in%1;(O2-e5<0r?D?l_}UvpK#Lb@Yof9{>NQr5&Kj>~G(`_kaKU zZSw5^nf2+sDJjVed>o|*T&rsbbgRhafx>sT6NY0rxjU^{Z__s$Y=-7^TRLH!I!1o}>ppQ} zEIfB9(tS2OIUb%o9zS|n49-M)=E9SK@Z@LVnTg2AY-DgQIyx<$oEAU&=-0rJGG;umJb@j=)?yHjhE zVz-9CJ!;iv)A`iYI`MozXazwCBo^oryS_~Lvq&w(DBe1n5XL|jA_057@5hHmW0yL` z?jibSuBknK;Y&yc_yUTf<8zUbzWLd1aqI|qozM!=MQ6IBSAsY=eKUGx2nMlWXYA_q z{A|ynJcTDOM#nnhfu6{TPsQtf;?x;T$Ml(mi5NW}>-hqFk4}G#19~dl{?%~gWKaD4 zs|!{mJy)V59b#7(7(S&h_MzPtXucakS- zQ7h~93Gx<)|A3%saQK`aN3(O0??ST6=koac4o{;~kh@(zzaVe)wzTo<=nv&Nc~WFj zP}=2#qWX#)Vx=V&nT5-SR`3u5IA{h_Lu)^1PJY)0L8oBqJ|+6;WIW4zYejU zf$mPU^xEaCL|>~e)I5r^8xbXxR-2yK4?{u5JAJ$rN2GzrQ*F~Y8vO?yZhJ$6w^d+U z@M;s-))IkjgR8X^?xpmv>Ydqdfb^2uqb4K$rOHS)(UzybCtA9tW?j1uMJo`S5Kkhu zAhsc1LA;7+L)<@c(kKPzpnaHhxO`Yj6$5WGnQFbNL}dZ4R6V23GG_`(x3{SY(^UsD zg3QJm-h?aY S!4lW#(2n&gBfdyw2KIkRP9ekq