goturn.py

track_model_def = 'tracker.prototxt'
track_model_weights = 'tracker.caffemodel'

track_net = caffe.Net(
    track_model_def,      # defines the structure of the model
    track_model_weights,  # contains the trained weights
    caffe.TEST)     # use test mode (e.g., don't perform dropout)

def run_tracker(track_net, target, image):
    target = np.array(target)
    image = np.array(image)
    mean_bgr = np.array([104, 117, 123])
    
    target = (np.array(target[..., ::-1]) - mean_bgr).transpose((2, 0, 1))[None, ...]
    image = (np.array(image[..., ::-1]) - mean_bgr).transpose((2, 0, 1))[None, ...]
    
    track_net.blobs['target'].data[...] = target
    track_net.blobs['image'].data[...] = image
    track_net.blobs['bbox'].data[...] = np.zeros((1,4,1,1)) + 100219 # makes sure this input is ignored
    track_net.forward()
    result = np.array(track_net.blobs['fc8'].data).squeeze()
    
    return result * 227 / 10.