feat: 上传我的配置

.config/waybar/scripts/longshot-sh/stitch.py

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+#!/usr/bin/env python3
+import cv2
+import numpy as np
+import sys
+import os
+
+def stitch_video(video_path, output_path):
+    if not os.path.exists(video_path):
+        return
+
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        print("❌ 无法打开视频")
+        return
+
+    frames = []
+    ret, prev_frame = cap.read()
+    if not ret: return
+
+    frames.append(prev_frame)
+    anchor_frame = prev_frame.copy()
+
+    # ==========================
+    # 核心参数 (手动滚动优化)
+    # ==========================
+    MIN_SCROLL = 2
+    MATCH_CONFIDENCE = 0.5 
+    
+    # 忽略上下边缘 (防止浏览器地址栏/状态栏干扰)
+    IGNORE_Y_TOP = 0.15 
+    IGNORE_Y_BOTTOM = 0.15
+    IGNORE_X = 0.15 
+
+    h, w, _ = anchor_frame.shape
+    
+    # 有效特征区
+    x1 = int(w * IGNORE_X)
+    x2 = int(w * (1 - IGNORE_X))
+    y1 = int(h * IGNORE_Y_TOP)
+    template_h = int(h * 0.2)
+
+    print(f"⚡ 正在分析 (梯度匹配模式)...")
+    
+    last_shift = 0
+    SEARCH_WINDOW = 50 
+
+    while True:
+        ret, curr_frame = cap.read()
+        if not ret: break
+
+        # 1. 梯度处理 (解决白底黑字问题)
+        curr_gray = cv2.cvtColor(curr_frame, cv2.COLOR_BGR2GRAY)
+        anchor_gray = cv2.cvtColor(anchor_frame, cv2.COLOR_BGR2GRAY)
+
+        curr_grad = cv2.Sobel(curr_gray, cv2.CV_8U, 0, 1, ksize=3)
+        anchor_grad = cv2.Sobel(anchor_gray, cv2.CV_8U, 0, 1, ksize=3)
+
+        # 2. 提取模板
+        template = curr_grad[y1 : y1 + template_h, x1:x2]
+        roi = anchor_grad[y1:, x1:x2]
+
+        # 3. 匹配
+        res = cv2.matchTemplate(roi, template, cv2.TM_CCOEFF_NORMED)
+        
+        # 4. 惯性约束
+        if last_shift > 0:
+            mask = np.zeros_like(res)
+            target_y = last_shift 
+            y_min = max(0, target_y - SEARCH_WINDOW)
+            y_max = min(res.shape[0], target_y + SEARCH_WINDOW)
+            mask[y_min:y_max, :] = 1
+            res = np.multiply(res, mask)
+
+        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
+        shift = max_loc[1]
+
+        # 5. 判定
+        if max_val > MATCH_CONFIDENCE and shift > MIN_SCROLL and shift < (roi.shape[0] - 5):
+            new_content_start_y = h - shift
+            if new_content_start_y < h:
+                new_part = curr_frame[new_content_start_y:, :, :]
+                frames.append(new_part)
+                anchor_frame = curr_frame.copy()
+                
+                if last_shift == 0: last_shift = shift
+                else: last_shift = int(last_shift * 0.6 + shift * 0.4)
+
+    cap.release()
+
+    if len(frames) > 1:
+        try:
+            full_image = np.vstack(frames)
+            cv2.imwrite(output_path, full_image, [cv2.IMWRITE_PNG_COMPRESSION, 3])
+            print(f"🎉 处理完成")
+        except Exception as e:
+            print(f"❌ 保存失败: {e}")
+    else:
+        print("⚠️ 未检测到滚动，保存第一帧")
+        cv2.imwrite(output_path, frames[0])
+
+if __name__ == "__main__":
+    if len(sys.argv) < 3:
+        print("Usage: python stitch.py <input_video> <output_image>")
+    else:
+        stitch_video(sys.argv[1], sys.argv[2])