人体姿态估计的输出的形式

def get_max_preds(batch_heatmaps):
    '''
    get predictions from score maps
    heatsmaps numpy.ndarray([batch_size,num_joints,height,width])
    '''
    batch_size=batch_heatmaps.shape[0]
    num_joints=batch_heatmaps.shape[1]
    width=batch_heatmaps.shape[3]
    #The shape of heatmaps_reshaped is[batch_size,num_joints,height*width]
    heatmaps_reshaped=batch_heatmaps.reshape((batch_size,num_joints,-1))
    #chance the max idx of heatmaps_reshaped
    idx=np.argmax(heatmaps_reshaped,2)

    maxvals=np.amax(heatmaps_reshaped,2)

    maxvals=maxvals.reshape((batch_size,num_joints,1))


    idx=idx.reshape((batch_size,num_joints,1))

    preds=np.tile(idx,(1,1,2)).astype(np.float32)

    preds[:,:,0]=(preds[:,:,0])%width
    preds[:,:,1]=(preds[:,:,1])/width

    pred_mask=np.tile(np.greater(maxvals,0.0),(1,1,2))
    pred_mask=pred_mask.astype(np.float32)

    preds*=pred_mask


    return preds ,maxvals

preds、最后的输出preds分别如下的结果。 preds.shape（）=[batch-size,joints,2]

preds= [[[3298. 3298.]
  [2718. 2718.]
  [2010. 2010.]
  [1886. 1886.]
  [2594. 2594.]
  [3173. 3173.]
  [1948. 1948.]
  [1112. 1112.]
  [ 983.  983.]
  [ 468.  468.]
  [1942. 1942.]
  [1620. 1620.]
  [1235. 1235.]
  [ 988.  988.]
  [1440. 1440.]
  [1825. 1825.]]

 [[3554. 3554.]
  [2913. 2913.]
  [2147. 2147.]
  [2276. 2276.]
  [2979. 2979.]
  [3556. 3556.]
  [2211. 2211.]
  [1380. 1380.]
  [1251. 1251.]
  [ 799.  799.]
  [1953. 1953.]
  [1701. 1701.]
  [1442. 1442.]
  [1318. 1318.]
  [1706. 1706.]
  [2020. 2020.]]]
pred_mask_0= [[[1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]]

 [[1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]
  [1. 1.]]]
preds= [[[34. 51.]
  [30. 42.]
  [26. 31.]
  [30. 29.]
  [34. 40.]
  [37. 49.]
  [28. 30.]
  [24. 17.]
  [23. 15.]
  [20.  7.]
  [22. 30.]
  [20. 25.]
  [19. 19.]
  [28. 15.]
  [32. 22.]
  [33. 28.]]

 [[34. 55.]
  [33. 45.]
  [35. 33.]
  [36. 35.]
  [35. 46.]
  [36. 55.]
  [35. 34.]
  [36. 21.]
  [35. 19.]
  [31. 12.]
  [33. 30.]
  [37. 26.]
  [34. 22.]
  [38. 20.]
  [42. 26.]
  [36. 31.]]]