我在对象检测项目中使用了预训练的Yolo模型。我有downloaded the weight from someone else google drive，并使用了this GitHub repo中的“ YOLOv2”模型。
我的conda环境配置：
Python 3.6.7 :: Anaconda，Inc。
keras 2.2.4
Tensorflow 1.13.1后端 运行该程序时，出现以下错误：
编辑：完成追溯
/home/anubh/anaconda3/envs/cMLdev/bin/python /snap/pycharm-professional/121/helpers/pydev/pydevconsole.py --mode=client --port=42727
import sys; print('Python %s on %s' % (sys.version, sys.platform))
sys.path.extend(['/home/anubh/PycharmProjects/add_projects/blendid_data_challenge'])
PyDev console: starting.
Python 3.6.7 |Anaconda, Inc.| (default, Oct 23 2018, 19:16:44)
[GCC 7.3.0] on linux
runfile('/home/anubh/PycharmProjects/codingforfun/machine_learning/deepLearningAI-ANG/week3/car_detection_for_autonomous_driving/pretrain_yolo_model_car_detection.py', wdir='/home/anubh/PycharmProjects/codingforfun/machine_learning/deepLearningAI-ANG/week3/car_detection_for_autonomous_driving')
Using TensorFlow backend.
2019-03-20 11:08:41.522694: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
XXX lineno: 31, opcode: 0
Traceback (most recent call last):
File "<input>", line 1, in <module>
File "/snap/pycharm-professional/121/helpers/pydev/_pydev_bundle/pydev_umd.py", line 197, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "/snap/pycharm-professional/121/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/home/anubh/PycharmProjects/codingforfun/machine_learning/deepLearningAI-ANG/week3/car_detection_for_autonomous_driving/pretrain_yolo_model_car_detection.py", line 89, in <module>
main()
File "/home/anubh/PycharmProjects/codingforfun/machine_learning/deepLearningAI-ANG/week3/car_detection_for_autonomous_driving/pretrain_yolo_model_car_detection.py", line 86, in main
out_scores, out_boxes, out_classes = predict(sess, "test.jpg")
File "/home/anubh/PycharmProjects/codingforfun/machine_learning/deepLearningAI-ANG/week3/car_detection_for_autonomous_driving/pretrain_yolo_model_car_detection.py", line 66, in predict
yolo_model,class_names, scores, boxes,classes = build_graph(summary_needed=1)
File "/home/anubh/PycharmProjects/codingforfun/machine_learning/deepLearningAI-ANG/week3/car_detection_for_autonomous_driving/pretrain_yolo_model_car_detection.py", line 30, in build_graph
yolo_model = load_model("model_data/yolo.h5") # (m, 19, 19, 5, 85) tensor
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/engine/saving.py", line 419, in load_model
model = _deserialize_model(f, custom_objects, compile)
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/engine/saving.py", line 225, in _deserialize_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/engine/saving.py", line 458, in model_from_config
return deserialize(config, custom_objects=custom_objects)
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/layers/__init__.py", line 55, in deserialize
printable_module_name='layer')
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/utils/generic_utils.py", line 145, in deserialize_keras_object
list(custom_objects.items())))
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/engine/network.py", line 1032, in from_config
process_node(layer, node_data)
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/engine/network.py", line 991, in process_node
layer(unpack_singleton(input_tensors), **kwargs)
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/engine/base_layer.py", line 457, in __call__
output = self.call(inputs, **kwargs)
File "/home/anubh/anaconda3/envs/cMLdev/lib/python3.6/site-packages/keras/layers/core.py", line 687, in call
return self.function(inputs, **arguments)
File "/home/don/tensorflow/yad2k/yad2k/models/keras_yolo.py", line 31, in space_to_depth_x2
SystemError: unknown opcode
我发现2个线程1和2试图回答 如何编译TensorFlow二进制文件以支持我的CPU指令。
我也很容易找到someone's GitHub issue，但是原因还不清楚。他们只是在尝试打击游戏。
但是，我的问题是，
在相同的环境配置中，我将ResNet-50和VGG-16模型用于图像分类任务，并将keras的许多其他功能用作tensorflow后端并直接与tensorflow一起使用。一切正常，没有任何错误！
然后，Yolo_v2模型有什么特别的不兼容Tensorflow问题？在这方面，任何人都可以提供帮助吗？为什么使用哪个tensorflow版本以及在使用任何模型之前如何决定？