注释注释注释

StereoVidComfort.py

@@ -5,6 +5,7 @@ import cv2
 import os
 import sys
 from matplotlib import pyplot as plt
+from scipy import stats
 
 
 '''
@@ -19,10 +20,15 @@ TODO:
 
 # 打开视频文件
 def openVid():
-    fileName = input("video path:")
+    fileName = input("video path: ./vid/")
+    fileName = "./vid/" + fileName
     while not os.path.isfile(fileName):
+        if os.path.isfile(fileName + ".mkv"):
+            fileName = fileName + ".mkv"
+            break
         print("file doesn't exist!")
-        fileName = input("video path:")
+        fileName = input("video path: ./vid/")
+        fileName = "./vid/" + fileName
     cap = cv2.VideoCapture(fileName)
     if cap.isOpened():
         return cap
@@ -49,7 +55,7 @@ def getFrameRate(cap):
 
 # 给出左右画面，计算景深
 def getDepthMap(imgL, imgR):
-    stereo = cv2.StereoSGBM_create(numDisparities=64, blockSize=3)
+    stereo = cv2.StereoSGBM_create(numDisparities=32, blockSize=3)
     return stereo.compute(imgL, imgR)
 
 
@@ -76,7 +82,7 @@ if __name__ == "__main__":
     isDemo = int(input("is Demo(0/1)?"))
     frameRate = getFrameRate(cap)
     frameCount = getFrameCount(cap)
-
+    framesCalculated = 0
     isSuccess, img = cap.read()
     if not isSuccess:
         print("video read error.")
@@ -87,8 +93,8 @@ if __name__ == "__main__":
     imgR = np.split(img, 2, 1)[1]
     prvs = imgR  # 上一帧的右画面，用于运动矢量计算
 
-    # 每秒取10帧进行计算
+    # 每秒取4帧进行计算
-    for frameID in range(round(cap.get(cv2.CAP_PROP_POS_FRAMES)), round(frameCount), round(frameRate/10)):
+    for frameID in range(round(cap.get(cv2.CAP_PROP_POS_FRAMES)), round(frameCount), round(frameRate/4)):
         cap.set(cv2.CAP_PROP_POS_FRAMES, frameID)
         isSuccess, img = cap.read()
         if not isSuccess:
@@ -105,10 +111,17 @@ if __name__ == "__main__":
         # 计算深度图
         disparity = getDepthMap(imgL, imgR)
 
+        framesCalculated += 1
+
         # 显示计算结果
         print("time: ", round(frameID/frameRate, 2))
-        print("AVG depth: ", round(np.mean(disparity), 2))
+        print("AVG depth: ", round(np.mean(disparity), 2))      # 景深的平均值，偏大则意味着负视差，可能不适
-        print("AVG motion: ", round(np.mean(hsv[..., 2]), 2))
+        print("AVG motion: ", round(np.mean(hsv[..., 2]), 2))       # 运动矢量大小的平均值，可判断画面大致上是否稳定
+        print("Mode depth: ", stats.mode(disparity.reshape(-1))[0][0])      # 景深的众数，由于景深基本不连续，众数意义不大
+        print("Mode motion: ", stats.mode(hsv[..., 2].reshape(-1))[0][0])       # 运动矢量大小的众数，一般为0，若较大，说明画面中存在较大面积的快速运动，可能不适
+        print("STD depth: ", round(np.std(disparity),2))        # 景深的标准差，若偏大说明景深范围较大，可能不适，但同时也是3D感更强的特征
+        print("STD motion: ", round(np.std(hsv[...,2]),2))      # 运动矢量大小的标准差，若偏大说明各部分运动比较不一致，可能需要结合运动矢量的方向作进一步判断，若存在较复杂的运动形式，则可能不适
+
         print()
 
         # 当为demo模式时显示当前帧画面、运动矢量图和景深图
@@ -121,12 +134,16 @@ if __name__ == "__main__":
             bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)  # hsv转为rgb用于显示
             cv2.namedWindow("MotionVector", cv2.WINDOW_NORMAL)
             cv2.imshow("MotionVector", bgr)
-
+            # cv2.waitKey(1)
             # 显示当前帧的景深图
             plt.title("DepthMap")
             plt.imshow(disparity)
+            # 运动矢量的直方图，方便查看数值
+            # plt.title("MotionVector")
+            # plt.imshow(hsv[...,2])
+            # plt.show()
             plt.pause(0.2)
-
+            input("press to continue")
         prvs = next  # 当前帧覆盖上一帧，继续计算
     print("success")