real-time-emotion-detection 排坑记录

news2024/9/25 3:22:00

real-time-emotion-detection 排坑记录

任务
踩坑回顾
- CV2包版本问题
- - 症状描述
  - 解决方法
- 模型文件路径问题
- - 症状描述
  - 解决办法
- tensorflow版本问题
- - 症状描述
  - 解决办法
其他

任务

我之前跑了一个CNN情绪识别的开源代码，现在我想尝试把他用到我的另一个项目里。但当时那个项目是用python3.8的虚拟环境跑的，我现在的项目的虚拟环境是python3.10，所以就会出点问题。这就是为什么我现在坚持什么项目都用python3.10跑通，并记录排坑博客的原因！方便再次用到。

踩坑回顾

CV2包版本问题

症状描述

我在python3.10环境下，pip3 install一通，直接默认最新的版本。原本运行没问题的代码，换新环境就找不到元素了：

AttributeError: module 'cv2' has no attribute 'haarcascades'

肯定是包版本问题。要么改版本，要么看新版本是不是同样的功能换了使用方法，如果新版本干脆没这个功能了，就比较棘手，可能得改版本。我不想改版本，就先网上搜下。这篇博客参考回答给了我答案。

解决方法

把源代码中的

face_path = cv2.haarcascades + 'haarcascade_frontalface_alt.xml'

改为

face_path = cv2.data.haarcascades + 'haarcascade_frontalface_alt.xml'

就行了。

模型文件路径问题

症状描述

运行到加载模型这一步报错：

OSError: No file or directory found at ./model/CNN-Emotion-Model

原项目中，脚本和模型的目录在同一个目录中，python也在这个目录下运行，所以是没问题的。但在新项目中,python不在这个目录下运行，所以相对路径的根不再是那个目录，而是python脚本的目录，自然找不到模型文件。这应该是挺常见的问题，但我工程实践太少了，现在才知道怎么处理：

要么用绝对路径：这太傻了，下次项目移植岂不更麻烦
要么保留这一模块的目录结构（也就是保留了相对路径关系），让脚本自己运行时确定自己的绝对路径，一拼接就没问题了：这是个好办法

解决办法

把源代码：

model_path = "./model/CNN-Emotion-Model"

改为：

current_dir = os.path.dirname(os.path.realpath(__file__))
model_path = os.path.join(current_dir, 'model/CNN-Emotion-Model')

就好了。

tensorflow版本问题

症状描述

运行报错很长，可把我吓了一跳。和运行原项目的提示信息一对比，发现主要变化是这几个部分：

2024-02-02 21:58:21.583946: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-02-02 21:58:21.583973: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-02-02 21:58:21.584533: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered

2024-02-02 21:58:24.336529: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1929] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 6100 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3070 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.6
2024-02-02 21:58:25.693790: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:447] Loaded runtime CuDNN library: 8.8.1 but source was compiled with: 8.9.4.  CuDNN library needs to have matching major version and equal or higher minor version. If using a binary install, upgrade your CuDNN library.  If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
2024-02-02 21:58:25.694223: W tensorflow/core/framework/op_kernel.cc:1839] OP_REQUIRES failed at conv_ops_impl.h:1199 : UNIMPLEMENTED: DNN library is not found.
Traceback (most recent call last):
  File "/home/lcy-magic/RaceCar_Demo/RaceCar_ShareControl/evaluate/run-realtime.py", line 85, in <module>
    main()
  File "/home/lcy-magic/RaceCar_Demo/RaceCar_ShareControl/evaluate/run-realtime.py", line 58, in main
    emotion = drawFace(frame, frame_grey)
  File "/home/lcy-magic/RaceCar_Demo/RaceCar_ShareControl/evaluate/run-realtime.py", line 36, in drawFace
    emotion = emotion_model.predict(face/255)
  File "/home/lcy-magic/anaconda3/envs/CARDEMO/lib/python3.10/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/home/lcy-magic/anaconda3/envs/CARDEMO/lib/python3.10/site-packages/tensorflow/python/eager/execute.py", line 53, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.UnimplementedError: Graph execution error:

  File "/home/lcy-magic/anaconda3/envs/CARDEMO/lib/python3.10/site-packages/keras/src/layers/convolutional/base_conv.py", line 262, in convolution_op

DNN library is not found.
	 [[{{node sequential_11/conv2d_57/Conv2D}}]] [Op:__inference_predict_function_1627]

看起来也是版本问题，网上搜了几个方法都不太管用，无奈只好给tensorflow降版本了。