目标检测文集

 

 

1. 深度学习目标检测系列：faster RCNN实现｜附python源码

https://yq.aliyun.com/articles/679245

2. 目标检测算法图解：

译文：一文看懂RCNN系列算法

https://zhuanlan.zhihu.com/p/52379393

原文：A Step-by-Step Introduction to the Basic Object Detection Algorithms (Part 1)

https://www.analyticsvidhya.com/blog/2018/10/a-step-by-step-introduction-to-the-basic-object-detection-algorithms-part-1/

3. Github下的项目：keras-frcnn

https://github.com/kbardool/keras-frcnn

该项目在运行时，出现了如下错误：

Traceback (most recent call last):
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 1864, in _create_c_op
    c_op = c_api.TF_FinishOperation(op_desc)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shape must be rank 1 but is rank 0 for 'bn_conv1/Reshape_4' (op: 'Reshape') with input shapes: [1,1,1,64], [].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train_frcnn.py", line 122, in 
    shared_layers = nn.nn_base(img_input, trainable=True)
  File "D:\OneDrive - Continental AG\Develop\PCB\Code-Ref\keras-frcnn-master\keras_frcnn\resnet.py", line 180, in nn_base
    x = FixedBatchNormalization(axis=bn_axis, name='bn_conv1')(x)
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\engine\base_layer.py", line 457, in __call__
    output = self.call(inputs, **kwargs)
  File "D:\OneDrive - Continental AG\Develop\PCB\Code-Ref\keras-frcnn-master\keras_frcnn\FixedBatchNormalization.py", line 73, in call
    epsilon=self.epsilon)
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\keras\backend\tensorflow_backend.py", line 1908, in batch_normalization
    mean = tf.reshape(mean, (-1))
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 7714, in reshape
    "Reshape", tensor=tensor, shape=shape, name=name)
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
    op_def=op_def)
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 3616, in create_op
    op_def=op_def)
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 2027, in __init__
    control_input_ops)
  File "C:\Users\uidt8491\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\ops.py", line 1867, in _create_c_op
    raise ValueError(str(e))
ValueError: Shape must be rank 1 but is rank 0 for 'bn_conv1/Reshape_4' (op: 'Reshape') with input shapes: [1,1,1,64], [].

解决方案有2种：

https://github.com/kbardool/keras-frcnn/issues/23

https://github.com/keras-team/keras/commit/e3a2f7d29f2f1c21ecc978bd0038b1d1330d33c2

4. 在Jetson下进行训练，安装Keras：

尝试用pip方式安装，安装失败

用apt-get安装，成功：

$ sudo apt-get install python3-keras

查看keras的版本：

$ python3 -W ignore -c "import keras; print('Keras Version:',keras.__version__)"

发现在Arm64位的Ubuntu 18.0.4下，Keras的最高版本是2.1.1-1.， 运行时会产生如下错误：

Exception: Error when checking target: expected rpn_out_class to have shape (None, None, None, 9) but got array with shape (1, 56, 38, 18)

我在Windows里面可以正常运行，而Windows里的Keras是2.2.4版本，所以需要手动升级Ubuntu下的Keras

方法：

1. 从github下载2.2.4版本的Keras

https://github.com/keras-team/keras/tree/2.2.4

2. 下载后，解压缩到某个文件夹。

3. 编辑解压缩文件夹中的keras/backend/tensorflow_backend.py文件。

由于Keras 2.2.4会出现如下错误：

Shape must be rank 1 but is rank 0 for 'bn_conv1/Reshape_4' (op: 'Reshape') with input shapes: [1,1,1,64], [].

根据上面文章的提示，对keras/backend/tensorflow_backend.py进行编辑，更改如下：

原文链接：https://github.com/keras-team/keras/commit/e3a2f7d29f2f1c21ecc978bd0038b1d1330d33c2

4. 根据github上面的Readme.md的指导，在该文件夹下执行如下命令安装：

sudo python3 setup.py install

根据以上步骤，keras-fcnn的training可以在Arm64的Ubuntu 18.0.4下顺利运行。