Caffe-Faster RCNN错误：TypeError: 'numpy.float64' object cannot be interpreted as an index

在训练Faster RCNN时候出现以下错误：

Solving...
Process Process-3:
Traceback (most recent call last):
  File "/usr/lib/python2.7/multiprocessing/process.py", line 267, in _bootstrap
    self.run()
  File "/usr/lib/python2.7/multiprocessing/process.py", line 114, in run
    self._target(*self._args, **self._kwargs)
  File "./tools/train_faster_rcnn_alt_opt.py", line 197, in train_fast_rcnn
    max_iters=max_iters)
  File "/home/liguangyao/Programming/caffe-faster-rcnn/tools/../lib/fast_rcnn/train.py", line 161, in train_net
    model_paths = sw.train_model(max_iters)
  File "/home/liguangyao/Programming/caffe-faster-rcnn/tools/../lib/fast_rcnn/train.py", line 102, in train_model
    self.solver.step(1)
  File "/home/liguangyao/Programming/caffe-faster-rcnn/tools/../lib/roi_data_layer/layer.py", line 144, in forward
    blobs = self._get_next_minibatch()
  File "/home/liguangyao/Programming/caffe-faster-rcnn/tools/../lib/roi_data_layer/layer.py", line 63, in _get_next_minibatch
    return get_minibatch(minibatch_db, self._num_classes)
  File "/home/liguangyao/Programming/caffe-faster-rcnn/tools/../lib/roi_data_layer/minibatch.py", line 55, in get_minibatch
    num_classes)
  File "/home/liguangyao/Programming/caffe-faster-rcnn/tools/../lib/roi_data_layer/minibatch.py", line 100, in _sample_rois
    fg_inds, size=fg_rois_per_this_image, replace=False)
  File "mtrand.pyx", line 1192, in mtrand.RandomState.choice
TypeError: 'numpy.float64' object cannot be interpreted as an index

在训练stage1 rpn时，出现’numpy.float64’ object cannot be interpreted as an index 的提示错误，几乎所有的博客中都指出，需要更换numpy 的版本，照做之后，出现ImportError: numpy.core.multiarray failed to import，这个问题又是numpy不匹配造成的，这样就形成了恶性循环，所以，可以考虑从根源上解决’numpy.float64’ object cannot be interpreted as an index的问题。
需要修改一下几个文件：

1. /home/xxx/py-faster-rcnn/lib/roi_data_layer/minibatch.py

将第26行：
fg_rois_per_image = np.round(cfg.TRAIN.FG_FRACTION * rois_per_image)
改为：
fg_rois_per_image = np.round(cfg.TRAIN.FG_FRACTION * rois_per_image).astype(np.int)

第174，175行改为：
for ind in inds:
cls = clss[ind]
start =int( 4 * cls)		//改这句
end = int(start + 4)		//改这句
bbox_targets[ind, start:end] = bbox_target_data[ind, 1:]
bbox_inside_weights[ind, start:end] = cfg.TRAIN.BBOX_INSIDE_WEIGHTS

2. /home/xxx/py-faster-rcnn/lib/datasets/ds_utils.py

将第12行：hashes = np.round(boxes * scale).dot(v)
改为：hashes = np.round(boxes * scale).dot(v).astype(np.int)

3. /home/xxx/py-faster-rcnn/lib/fast_rcnn/test.py

将第129行： hashes = np.round(blobs['rois'] * cfg.DEDUP_BOXES).dot(v)
改为： hashes = np.round(blobs['rois'] * cfg.DEDUP_BOXES).dot(v).astype(np.int)

4. /home/xxx/py-faster-rcnn/lib/rpn/proposal_target_layer.py

将第60行：fg_rois_per_image = np.round(cfg.TRAIN.FG_FRACTION * rois_per_image)
改为：fg_rois_per_image = np.round(cfg.TRAIN.FG_FRACTION * rois_per_image).astype(np.int)

解决完上一个问题后，又出现 TypeError: slice indices must be integers or None or have an index method的问题，如果没有改变numpy的版本。

5. 修改 /home/XXX/py-faster-rcnn/lib/rpn/proposal_target_layer.py，转到123行：

for ind in inds:
        cls = clss[ind]
        start = 4 * cls
        end = start + 4
        bbox_targets[ind, start:end] = bbox_target_data[ind, 1:]
        bbox_inside_weights[ind, start:end] = cfg.TRAIN.BBOX_INSIDE_WEIGHTS
    return bbox_targets, bbox_inside_weights

这里的ind，start，end都是 numpy.int 类型，这种类型的数据不能作为索引，所以必须对其进行强制类型转换，转化结果如下：

for ind in inds:
        ind = int(ind)
        cls = clss[ind]
        start = int(4 * cos)
        end = int(start + 4)
        bbox_targets[ind, start:end] = bbox_target_data[ind, 1:]
        bbox_inside_weights[ind, start:end] = cfg.TRAIN.BBOX_INSIDE_WEIGHTS
    return bbox_targets, bbox_inside_weight

再次编译运行，顺利通过~

参考资料：TypeError: ‘numpy.float64’ object cannot be interpreted as an index