cv2.imshowは1の代わりに9つの画面を表示します。

Question

ウェブカメラビデオから肌を適応的に検出するコードを構築しています。私はそれがほとんど働いている、しかし、ビデオを出力するとき、それはただ1つではなく "スキン"マスクの9画面を示します。私は単純なものを見逃しているようですが、私はそれを理解できません。

image shown here

以下のコード：

# first let's train the data 
data, labels = ReadData() 
classifier = TrainTree(data, labels) 

# get the webcam. The input is either a video file or the camera number 
# since using laptop webcam (only 1 cam), input is 0. A 2nd cam would be input 1 
camera = cv2.VideoCapture(0) 

while True: 
    # reads in the current frame 
    # .read() returns True if frame read correctly, and False otherwise 
    ret, frame = camera.read() # frame.shape: (480,640,3) 

    if ret: 
     # reshape the frame to follow format of training data (rows*col, 3) 
     data = np.reshape(frame, (frame.shape[0] * frame.shape[1], 3)) 
     bgr = np.reshape(data, (data.shape[0], 1, 3)) 
     hsv = cv2.cvtColor(np.uint8(bgr), cv2.COLOR_BGR2HSV) 
     # once we have converted to HSV, we reshape back to original shape of (245057,3) 
     data = np.reshape(hsv, (hsv.shape[0], 3)) 
     predictedLabels = classifier.predict(data) 

     # the AND operator applies the skinMask to the image 
     # predictedLabels consists of 1 (skin) and 2 (non-skin), needs to change to 0 (non-skin) and 255 (skin) 
     predictedMask = (-(predictedLabels - 1) + 1) * 255 # predictedMask.shape: (307200,) 

     # resize to match frame shape 
     imgLabels = np.resize(predictedMask, (frame.shape[0], frame.shape[1], 3)) # imgLabels.shape: (480,640,3) 
     # masks require 1 channel, not 3, so change from BGR to GRAYSCALE 
     imgLabels = cv2.cvtColor(np.uint8(imgLabels), cv2.COLOR_BGR2GRAY) # imgLabels.shape: (480,640) 

     # do bitwsie AND to pull out skin pixels. All skin pixels are anded with 255 and all others are 0 
     skin = cv2.bitwise_and(frame, frame, mask=imgLabels) # skin.shape: (480,640,3) 
     # show the skin in the image along with the mask, show images side-by-side 
     # **********THE BELOW LINE OUTPUTS 9 screens of the skin mask instead of just 1 **************** 
     cv2.imshow("images", np.hstack([frame, skin])) 

     # if the 'q' key is pressed, stop the loop 
     if cv2.waitKey(1) & 0xFF == ord("q"): 
      break 
    else: 
     break 

# release the video capture 
camera.release() 
cv2.destroyAllWindows() 

Answer 1

あなたはビットマップで作業しています。彼らが何を保持しているかを知るには、cv2.imshowを個別に入手してください。次に、データがどこに間違っているかを（文字通り）見てみましょう。

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今、犯人はおそらくnp.resize()である：

np.resize(a, new_shape)

Return a new array with the specified shape.

If the new array is larger than the original array, then the new array is filled with repeated copies of a. Note that this behavior is different from a.resize(new_shape) which fills with zeros instead of repeated copies of a .

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スケールビットマップ（=同じ視覚画像を保存するために努力しながらリサイズ）、OpenCV: Geometric Transformations of Imagesに従ってcv2.resize()を使用に。