Update align.py

align.py

@@ -4,7 +4,6 @@ from fastdtw import fastdtw
 import json
 import cv2
 
-# 读取视频文件
 def read_video_frames(video_path):
     cap = cv2.VideoCapture(video_path)
     frames = []
@@ -16,7 +15,6 @@ def read_video_frames(video_path):
     cap.release()
     return frames
 
-# 提取关键点
 def extract_keypoints(sequence):
     keypoints_sequence = []
     for frame in sequence:
@@ -37,14 +35,10 @@ def calculate_distance_matrix(seq1, seq2):
 
 # 计算两个手语序列的最佳对齐路径
 def align_sequences(seq1, seq2):
-    # 提取关键点
     keypoints_seq1 = extract_keypoints(seq1)
     keypoints_seq2 = extract_keypoints(seq2)
 
-    # 计算距离矩阵
     distances = calculate_distance_matrix(keypoints_seq1, keypoints_seq2)
-
-    # 使用 DTW 进行对齐
     distance, path = fastdtw(keypoints_seq1, keypoints_seq2, dist=lambda x, y: np.linalg.norm(x - y))
     
     return distance, path
@@ -135,11 +129,7 @@ def create_aligned_videos(seq1_frames, seq2_frames, alignment_path, output_combi
         # 获取对齐的帧
         frame1 = seq1_frames[idx1]
         frame2 = seq2_frames[idx2]
-
-        # # 如果两帧高度不一致，调整frame2的高度以匹配frame1
-        # if height1 != height2:
-        #     frame2 = cv2.resize(frame2, (width2, height1))
-        
+ 
         # 等比例缩放两个视频的帧到统一尺寸
         frame1_resized = cv2.resize(frame1, (unified_width, unified_height), interpolation=cv2.INTER_AREA)
         frame2_resized = cv2.resize(frame2, (unified_width, unified_height), interpolation=cv2.INTER_AREA)