'commit'

Apps/TeLaiDian/Crawler.py

@@ -410,7 +410,7 @@ class TeLaiDianCrawler(BaseCrawler):
             entered_price_path = take_screenshot(d, f"tld_detail_price_after_enter_{int(time.time())}.jpg")
             logger.info(f"[电价页] 入口点击后的电价页截图已保存: {entered_price_path}")
 
-            await asyncio.sleep(1.0)
+            await asyncio.sleep(0.5)
             
             # 1. 向上滚动到顶部（不断下拉直到看到最上面的 00:00）
             logger.info("正在向上滚动价格列表到顶部 (快速多次滚动以尽快看到 00:00)...")

Apps/YeLiTe/Test/check_last_run.py

@@ -1,44 +0,0 @@
-# coding=utf-8
-import sys
-import os
-import hashlib
-import cv2
-import numpy as np
-
-# Add project root to sys.path
-project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../"))
-sys.path.append(project_root)
-
-from Apps.YeLiTe.Kit import get_image_content_md5
-from Apps.YeLiTe.Config import Setting
-
-def check_result():
-    output_dir = os.path.join(project_root, "Output")
-    files = sorted([f for f in os.listdir(output_dir) if f.startswith("verify_step1_list_")])
-    if not files:
-        print("No verification files found.")
-        return
-
-    latest_timestamp = files[-1].split("_")[-1].replace(".jpg", "")
-    print(f"Checking latest run: {latest_timestamp}")
-
-    step1 = os.path.join(output_dir, f"verify_step1_list_{latest_timestamp}.jpg")
-    step4 = os.path.join(output_dir, f"verify_step4_after_{latest_timestamp}.jpg")
-
-    if not os.path.exists(step4):
-        print("Step 4 file not found. Script might have failed mid-way.")
-        return
-
-    md5_1 = get_image_content_md5(step1, top_ratio=Setting.SAFE_EXCLUDE_RATIO, bottom_ratio=Setting.BOTTOM_SAFE_EXCLUDE_RATIO)
-    md5_4 = get_image_content_md5(step4, top_ratio=Setting.SAFE_EXCLUDE_RATIO, bottom_ratio=Setting.BOTTOM_SAFE_EXCLUDE_RATIO)
-
-    print(f"Step 1 MD5: {md5_1}")
-    print(f"Step 4 MD5: {md5_4}")
-
-    if md5_1 != md5_4:
-        print(">>> RESULT: SUCCESS (MD5 Changed)")
-    else:
-        print(">>> RESULT: FAILURE (MD5 Identical)")
-
-if __name__ == "__main__":
-    check_result()

Apps/YeLiTe/Test/test_card_detection.py

@@ -1,82 +0,0 @@
-# coding=utf-8
-import sys
-import os
-import cv2
-import numpy as np
-import time
-
-# Add project root to sys.path
-project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../"))
-sys.path.append(project_root)
-
-try:
-    from Apps.YeLiTe.Kit import detect_cards_cv
-    from Apps.YeLiTe.Config import Setting
-except ImportError as e:
-    print(f"Import Error: {e}")
-    print(f"Current sys.path: {sys.path}")
-    sys.exit(1)
-
-def test_detection_and_click_simulation(image_path):
-    print(f"Loading image: {image_path}")
-    if not os.path.exists(image_path):
-        print(f"Error: File not found: {image_path}")
-        return
-
-    # 1. Run detection
-    print("Running detect_cards_cv...")
-    cards = detect_cards_cv(image_path, top_ratio=Setting.SAFE_EXCLUDE_RATIO, bottom_ratio=Setting.BOTTOM_SAFE_EXCLUDE_RATIO)
-    
-    if not cards:
-        print("No cards detected!")
-        return
-
-    print(f"Detected {len(cards)} cards.")
-
-    # 2. Draw results
-    img = cv2.imread(image_path)
-    
-    for i, box in enumerate(cards):
-        x1, y1, x2, y2 = box
-        
-        # Draw green box
-        cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
-        
-        # Calculate click point (center)
-        center_x = int((x1 + x2) / 2)
-        center_y = int((y1 + y2) / 2)
-        
-        # Draw click point (Red Circle)
-        cv2.circle(img, (center_x, center_y), 10, (0, 0, 255), -1)
-        
-        # Add label
-        label = f"#{i+1} ({center_x}, {center_y})"
-        cv2.putText(img, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
-        
-        print(f"Card #{i+1}: Box=[{x1}, {y1}, {x2}, {y2}], Click Point=({center_x}, {center_y})")
-
-    # 3. Save result
-    output_filename = f"result_{os.path.basename(image_path)}"
-    output_path = os.path.join(os.path.dirname(__file__), output_filename)
-    cv2.imwrite(output_path, img)
-    print(f"Result saved to: {output_path}")
-
-if __name__ == "__main__":
-    # Default to the latest list_*.jpg in Output if no argument provided
-    target_image = ""
-    
-    if len(sys.argv) > 1:
-        target_image = sys.argv[1]
-    else:
-        output_dir = os.path.join(project_root, "Output")
-        if os.path.exists(output_dir):
-            files = [f for f in os.listdir(output_dir) if f.startswith("list_") and f.endswith(".jpg")]
-            if files:
-                # Sort by time (filename usually contains timestamp)
-                files.sort(reverse=True)
-                target_image = os.path.join(output_dir, files[0])
-    
-    if target_image:
-        test_detection_and_click_simulation(target_image)
-    else:
-        print("No target image found. Please provide an image path as an argument.")

Apps/YeLiTe/Test/test_click_verification.py

@@ -1,129 +0,0 @@
-# coding=utf-8
-import sys
-import os
-import time
-import asyncio
-import uiautomator2 as u2
-import cv2
-
-# Add project root to sys.path
-project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../"))
-sys.path.append(project_root)
-
-try:
-    from Apps.YeLiTe.Kit import detect_cards_cv, draw_rectangles, take_screenshot, get_image_content_md5
-    from Apps.YeLiTe.Config import Setting
-except ImportError as e:
-    print(f"Import Error: {e}")
-    sys.exit(1)
-
-async def run_verification():
-    print(">>> [Step 0] 连接设备...")
-    try:
-        d = u2.connect()
-        info = d.info
-        print(f"设备已连接: {info.get('productName', 'Unknown Device')}")
-    except Exception as e:
-        print(f"设备连接失败: {e}")
-        return
-
-    # 这里我们假设已经在列表页，或者直接启动
-    # 为了保险，尝试回到桌面重新进? 不，用户说“获取第一屏场站列表”，假设用户已经准备好了环境，或者我们手动进一下
-    # 为了全自动化，我们调用 Opener 进一下
-    # 但是 Opener 可能会重启微信，有点慢。
-    # 我们先判断当前包名，如果是微信，就默认在列表页（或者由用户手动滑到列表页）
-    # 用户指令暗示是交互式的："获取第一屏...你去点击一下...停止程序"
-    # 所以我们假设当前就在列表页
-    
-    current_app = d.app_current()
-    print(f"当前前台应用: {current_app.get('package')}")
-    if "com.tencent.mm" not in current_app.get('package', ''):
-        print("警告：微信似乎不在前台，请确保手机显示的是【驿来特】小程序列表页")
-        print("给你 5 秒钟调整手机屏幕...")
-        time.sleep(5)
-    else:
-        print("检测到微信在前台，准备截图...")
-        time.sleep(2) # 稍微等一下稳定
-
-    # 1. 获取第一屏场站列表，然后截图
-    timestamp = int(time.time())
-    list_screenshot_path = os.path.join(project_root, "Output", f"verify_step1_list_{timestamp}.jpg")
-    print(f"\n>>> [Step 1] 截图列表页: {list_screenshot_path}")
-    d.screenshot(list_screenshot_path)
-    
-    # 2. 绿框标注，标识模拟点击点
-    print("\n>>> [Step 2] 识别卡片并标注...")
-    # 使用配置中的排除比例
-    cards = detect_cards_cv(list_screenshot_path, top_ratio=Setting.SAFE_EXCLUDE_RATIO, bottom_ratio=Setting.BOTTOM_SAFE_EXCLUDE_RATIO)
-    
-    if not cards:
-        print("!!! [Error] 未检测到任何场站卡片，测试终止")
-        print(f"请检查截图: {list_screenshot_path}")
-        return
-
-    print(f"检测到 {len(cards)} 个卡片区域")
-
-    # 在图上绘制绿框和红点
-    debug_img = cv2.imread(list_screenshot_path)
-    if debug_img is None:
-        print("读取截图失败")
-        return
-
-    first_card = cards[0]
-    # 计算点击点：中心点
-    click_x = int((first_card[0] + first_card[2]) / 2)
-    click_y = int((first_card[1] + first_card[3]) / 2)
-    
-    # 绘制所有卡片
-    for i, box in enumerate(cards):
-         # 绿框
-         cv2.rectangle(debug_img, (int(box[0]), int(box[1])), (int(box[2]), int(box[3])), (0, 255, 0), 2)
-         # 标号
-         cv2.putText(debug_img, str(i+1), (int(box[0]), int(box[1])+30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
-    
-    # 绘制第一个卡片的点击点 (实心红圆)
-    cv2.circle(debug_img, (click_x, click_y), 15, (0, 0, 255), -1)
-    # 绘制同心圆
-    cv2.circle(debug_img, (click_x, click_y), 25, (0, 0, 255), 2)
-    
-    marked_path = os.path.join(project_root, "Output", f"verify_step2_marked_{timestamp}.jpg")
-    cv2.imwrite(marked_path, debug_img)
-    print(f">>> 已生成标注图 (绿框+红点): {marked_path}")
-    print(f">>> 模拟点击目标: 第 1 个卡片, 坐标 ({click_x}, {click_y})")
-
-    # 计算点击前的 MD5
-    before_md5 = get_image_content_md5(list_screenshot_path, top_ratio=Setting.SAFE_EXCLUDE_RATIO, bottom_ratio=Setting.BOTTOM_SAFE_EXCLUDE_RATIO)
-
-    # 3. 你去点击一下，等一会
-    print(f"\n>>> [Step 3] 执行点击操作...")
-    # 使用 shell input tap
-    cmd = f"input tap {click_x} {click_y}"
-    print(f"执行命令: {cmd}")
-    d.shell(cmd)
-    
-    print(">>> 点击完成，等待 5 秒让页面跳转...")
-    await asyncio.sleep(5)
-
-    # 4. 再继续截图，判断是否进入
-    after_screenshot_path = os.path.join(project_root, "Output", f"verify_step4_after_{timestamp}.jpg")
-    print(f"\n>>> [Step 4] 截图当前页面: {after_screenshot_path}")
-    d.screenshot(after_screenshot_path)
-    
-    after_md5 = get_image_content_md5(after_screenshot_path, top_ratio=Setting.SAFE_EXCLUDE_RATIO, bottom_ratio=Setting.BOTTOM_SAFE_EXCLUDE_RATIO)
-
-    print("\n>>> [Step 5] 结果验证")
-    print("-" * 30)
-    print(f"点击前 MD5: {before_md5}")
-    print(f"点击后 MD5: {after_md5}")
-    
-    if before_md5 != after_md5:
-        print(">>> [SUCCESS] 判定结果: 成功进入详情页！ (MD5发生变化)")
-    else:
-        print(">>> [FAILURE] 判定结果: 未进入详情页 (MD5未变化)")
-        print("可能原因: 1. 点击无效 2. 页面加载极慢 3. 已经是详情页(误判)")
-    print("-" * 30)
-
-if __name__ == "__main__":
-    loop = asyncio.new_event_loop()
-    asyncio.set_event_loop(loop)
-    loop.run_until_complete(run_verification())

Apps/YeLiTe/Test/test_cv.py

@@ -1,111 +0,0 @@
-import sys
-import os
-import cv2
-import numpy as np
-
-# Add project root to path
-project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
-sys.path.append(project_root)
-
-from Apps.YeLiTe.Kit import detect_cards_cv, read_image
-
-def test_detection():
-    image_path = r"d:\dsWork\aiData\Output\list_1768309287.jpg"
-    if not os.path.exists(image_path):
-        print(f"Error: Image not found at {image_path}")
-        # Try to list files in Output to see what's available
-        output_dir = os.path.dirname(image_path)
-        if os.path.exists(output_dir):
-            print(f"Files in {output_dir}:")
-            for f in os.listdir(output_dir):
-                print(f)
-        return
-
-    print(f"Testing detection on {image_path}")
-    
-    # Debug mode: copy logic from Kit.py but add debug prints and saves
-    img = read_image(image_path)
-    if img is None: return
-    h, w = img.shape[:2]
-    print(f"Image size: {w}x{h}")
-    
-    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-    blurred = cv2.GaussianBlur(gray, (5, 5), 0)
-    
-    # Try different thresholds
-    edges = cv2.Canny(blurred, 10, 50) # Lower thresholds
-    
-    # Save edges
-    debug_edges_path = os.path.join(os.path.dirname(__file__), "debug_edges.jpg")
-    cv2.imencode('.jpg', edges)[1].tofile(debug_edges_path)
-    print(f"Saved edges to {debug_edges_path}")
-    
-    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    print(f"Found {len(contours)} contours")
-    
-    # Draw all contours on a debug image
-    debug_contours_img = img.copy()
-    cv2.drawContours(debug_contours_img, contours, -1, (0, 0, 255), 1)
-    debug_contours_path = os.path.join(os.path.dirname(__file__), "debug_contours.jpg")
-    cv2.imencode('.jpg', debug_contours_img)[1].tofile(debug_contours_path)
-    print(f"Saved all contours to {debug_contours_path}")
-
-    min_card_width = int(w * 0.8)
-    print(f"Min card width (strict): {min_card_width}")
-    
-    for i, cnt in enumerate(contours):
-        x, y, cw, ch = cv2.boundingRect(cnt)
-        if cw > 100 and ch > 50: # Only print somewhat large ones
-            print(f"Contour {i}: pos=({x},{y}), size={cw}x{ch}, aspect_ratio={cw/ch:.2f}")
-
-    # Run actual detection
-    try:
-        cards = detect_cards_cv(image_path)
-        print(f"Detected {len(cards)} cards")
-    except Exception as e:
-        print(f"Error during detection: {e}")
-        import traceback
-        traceback.print_exc()
-        return
-    
-    # Read image for drawing
-    img_lv = read_image(image_path)
-    img_flag = read_image(image_path)
-    if img_lv is None:
-        print("Failed to read image")
-        return
-
-    for i, card in enumerate(cards):
-        x1, y1, x2, y2 = card
-        print(f"Card {i+1}: [{x1}, {y1}, {x2}, {y2}]")
-        
-        # Draw green rectangle on img_lv
-        cv2.rectangle(img_lv, (x1, y1), (x2, y2), (0, 255, 0), 2)
-        cv2.putText(img_lv, f"Card {i+1}", (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
-        
-        # Calculate click point (center)
-        center_x = (x1 + x2) // 2
-        center_y = (y1 + y2) // 2
-        
-        # Draw red click point on img_flag
-        cv2.circle(img_flag, (center_x, center_y), 5, (0, 0, 255), -1)
-        # Also draw a crosshair for better visibility
-        cv2.line(img_flag, (center_x - 10, center_y), (center_x + 10, center_y), (0, 0, 255), 1)
-        cv2.line(img_flag, (center_x, center_y - 10), (center_x, center_y + 10), (0, 0, 255), 1)
-        cv2.putText(img_flag, f"Click {i+1}", (center_x + 10, center_y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1)
-        
-        print(f"Click Point {i+1}: ({center_x}, {center_y})")
-
-    # Save _lv.jpg
-    base_name = os.path.splitext(os.path.basename(image_path))[0]
-    output_lv = os.path.join(os.path.dirname(__file__), f"{base_name}_lv.jpg")
-    cv2.imencode('.jpg', img_lv)[1].tofile(output_lv)
-    print(f"Green box image saved to {output_lv}")
-
-    # Save _flag.jpg
-    output_flag = os.path.join(os.path.dirname(__file__), f"{base_name}_flag.jpg")
-    cv2.imencode('.jpg', img_flag)[1].tofile(output_flag)
-    print(f"Click point image saved to {output_flag}")
-
-if __name__ == "__main__":
-    test_detection()