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HuangHai
@@ -151,11 +151,11 @@ def detect_price_click_point_cv(image_path):
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return [center_x, center_y]
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def detect_cards_cv(image_path, top_ratio=0.40, bottom_ratio=0.12):
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"""
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使用计算机图形学 (OpenCV) 检测列表中的场站卡片。
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"""
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from Apps.TeLaiDian.Config.Setting import MIN_CARD_HEIGHT
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def detect_cards_cv(image_path, top_ratio=0.40, bottom_ratio=0.12):
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"""
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使用计算机图形学 (OpenCV) 检测列表中的场站卡片。
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"""
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from Apps.TeLaiDian.Config.Setting import MIN_CARD_HEIGHT
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img = read_image(image_path)
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if img is None:
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@@ -183,24 +183,38 @@ def detect_cards_cv(image_path, top_ratio=0.40, bottom_ratio=0.12):
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contours, _ = cv2.findContours(closed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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cards = []
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# 降低最小宽度要求，有些卡片边缘可能没完全闭合
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min_card_width = int(w * 0.6)
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# 更严格的最小宽度要求：列表卡片通常接近整宽
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min_card_width = int(w * 0.8)
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temp_boxes = []
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for cnt in contours:
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x, y, cw, ch = cv2.boundingRect(cnt)
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center_y = y + ch // 2
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# 增加最小高度验证 MIN_CARD_HEIGHT
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if (cw > min_card_width and
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ch > MIN_CARD_HEIGHT * 0.8 and # 稍微放宽高度限制
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y > top_limit and
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y + ch < bottom_limit):
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logger.info(f"✅ 找到候选卡片: y={y}, h={ch}, w={cw}")
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# 绿色营销券区域排除
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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roi = hsv[max(0,y):min(h,y+ch), max(0,x):min(w,x+cw)]
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green_mask = cv2.inRange(roi, np.array([35, 80, 80]), np.array([85, 255, 255]))
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green_ratio = float(cv2.countNonZero(green_mask)) / (roi.shape[0]*roi.shape[1]) if roi.size > 0 else 0.0
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# 圆角矩形判断：面积占比与顶点数量
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rect_area = cw * ch
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cnt_area = cv2.contourArea(cnt)
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extent = cnt_area / rect_area if rect_area > 0 else 0
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approx = cv2.approxPolyDP(cnt, 0.02 * cv2.arcLength(cnt, True), True)
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ok_width = cw >= min_card_width
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ok_height = ch > MIN_CARD_HEIGHT * 0.8
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ok_vertical = center_y >= int(h * 0.58) and y > top_limit and y + ch < bottom_limit
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ok_shape = (len(approx) >= 6 or extent > 0.85)
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ok_color = green_ratio < 0.25
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if ok_width and ok_height and ok_vertical and ok_shape and ok_color:
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logger.info(f"✅ 找到候选卡片: y={y}, h={ch}, w={cw}, extent={extent:.2f}, verts={len(approx)}, green={green_ratio:.2f}")
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temp_boxes.append((x, y, cw, ch))
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else:
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if cw > min_card_width:
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logger.debug(f"❌ 排除候选(不符条件): y={y}, h={ch}, w={cw} (limit: {top_limit}-{bottom_limit}, min_h: {MIN_CARD_HEIGHT*0.8})")
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if ok_width:
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logger.debug(f"❌ 排除候选: y={y}, h={ch}, w={cw}, extent={extent:.2f}, verts={len(approx)}, green={green_ratio:.2f} (limit: {top_limit}-{bottom_limit})")
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if not temp_boxes:
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logger.warning(f"⚠️ CV 未能在指定范围 ({top_limit}-{bottom_limit}) 内检测到任何场站卡片")
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@@ -226,46 +240,46 @@ def detect_cards_cv(image_path, top_ratio=0.40, bottom_ratio=0.12):
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min(w, x + cw - padding),
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min(bottom_limit, y + ch - padding)
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])
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return cards
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def detect_wide_rounded_card_cv(image_path, min_width_ratio=0.8, min_y_ratio=0.5):
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img = read_image(image_path)
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if img is None:
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return []
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h, w = img.shape[:2]
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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blur = cv2.GaussianBlur(gray, (7, 7), 0)
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edges = cv2.Canny(blur, 60, 180)
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kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (15, 15))
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closed = cv2.morphologyEx(edges, cv2.MORPH_CLOSE, kernel)
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contours, _ = cv2.findContours(closed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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results = []
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for cnt in contours:
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x, y, cw, ch = cv2.boundingRect(cnt)
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center_y = y + ch // 2
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if cw < int(w * min_width_ratio):
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continue
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if center_y < int(h * min_y_ratio):
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continue
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rect_area = cw * ch
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cnt_area = cv2.contourArea(cnt)
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if rect_area <= 0:
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continue
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extent = cnt_area / rect_area
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approx = cv2.approxPolyDP(cnt, 0.02 * cv2.arcLength(cnt, True), True)
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if extent < 0.7:
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continue
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if len(approx) >= 6 or (len(approx) == 4 and extent > 0.85):
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results.append([x, y, x + cw, y + ch])
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results.sort(key=lambda b: b[1])
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return results
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def draw_rectangles(image_path, bboxes=None, click_points=None):
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"""
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使用 OpenCV 在图片上绘制矩形框和点击点，生成 _vl.jpg 和 _flag.jpg
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- _vl.jpg: 仅包含矩形框，供视觉模型参考
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- _flag.jpg: 包含矩形框和点击点，供人工调试
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return cards
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def detect_wide_rounded_card_cv(image_path, min_width_ratio=0.8, min_y_ratio=0.5):
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img = read_image(image_path)
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if img is None:
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return []
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h, w = img.shape[:2]
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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blur = cv2.GaussianBlur(gray, (7, 7), 0)
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edges = cv2.Canny(blur, 60, 180)
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kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (15, 15))
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closed = cv2.morphologyEx(edges, cv2.MORPH_CLOSE, kernel)
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contours, _ = cv2.findContours(closed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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results = []
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for cnt in contours:
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x, y, cw, ch = cv2.boundingRect(cnt)
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center_y = y + ch // 2
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if cw < int(w * min_width_ratio):
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continue
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if center_y < int(h * min_y_ratio):
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continue
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rect_area = cw * ch
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cnt_area = cv2.contourArea(cnt)
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if rect_area <= 0:
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continue
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extent = cnt_area / rect_area
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approx = cv2.approxPolyDP(cnt, 0.02 * cv2.arcLength(cnt, True), True)
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if extent < 0.7:
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continue
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if len(approx) >= 6 or (len(approx) == 4 and extent > 0.85):
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results.append([x, y, x + cw, y + ch])
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results.sort(key=lambda b: b[1])
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return results
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def draw_rectangles(image_path, bboxes=None, click_points=None):
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"""
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使用 OpenCV 在图片上绘制矩形框和点击点，生成 _vl.jpg 和 _flag.jpg
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- _vl.jpg: 仅包含矩形框，供视觉模型参考
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- _flag.jpg: 包含矩形框和点击点，供人工调试
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"""
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try:
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DEBUG_BOX_COLOR = (0, 255, 0) # 绿色矩形
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