caffe_functions.py 文件源码

def classify_video_frame(frame, faces, VGG_S_Net, categories=None):
    # Handle incorrect image dims for uncropped images
    # TODO: Get uncropped images to import correctly
    #if frame.shape[0] == 3:
    #    frame = np.swapaxes(np.swapaxes(frame, 0, 1), 1, 2)


    # Convert to float format:
    frame = frame.astype(np.float32)
    frame /= 255.0

    labels = []

    for x,y,w,h in faces:
        img = frame[y:y+h,x:x+w,:]

        # Input image should be WxHxK, e.g. 490x640x3
        prediction = VGG_S_Net.predict([img], oversample=False)

        labels.append(prediction.argmax())

    return labels