vseasky / yolo-for-k210 Goto Github PK

$  cmake .. –DPROJ=hello_world –G "MinGW Makefiles"
CMake Error: The source directory "/home/kearney/Downloads/k210/Yolo-for-k210/seasky_yolo/build/MinGW Makefiles" does not exist.
Specify --help for usage, or press the help button on the CMake GUI.

$  cmake .. –DPROJ=hello_world
CMake Error: The source directory "/home/kearney/Downloads/k210/Yolo-for-k210/seasky_yolo/build/–DPROJ=hello_world" does not exist.
Specify --help for usage, or press the help button on the CMake GUI.

$ make train MODEL=yolo_mobilev1 DEPTHMUL=0.75 MAXEP=10
ILR=0.001 DATASET=voc CLSNUM=20 IAA=False BATCH=8
python ./keras_train.py \
                --train_set voc \
                --class_num 20 \
                --pre_ckpt "" \
                --model_def yolo_mobilev1 \
                --depth_multiplier 0.75 \
                --augmenter False \
                --image_size 224 320 \
                --output_size 7 10 14 20 \
                --batch_size 32 \
                --rand_seed 3 \
                --max_nrof_epochs 10 \
                --init_learning_rate 0.0005 \
                --learning_rate_decay_factor 0 \
                --obj_weight 1 \
                --noobj_weight 1 \
                --wh_weight 1 \
                --obj_thresh 0.7 \
                --iou_thresh 0.5 \
                --vaildation_split 0.05 \
                --log_dir log \
                --is_prune False \
                --prune_initial_sparsity 0.5 \
                --prune_final_sparsity 0.9 \
                --prune_end_epoch 5 \
                --prune_frequency 100 
WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.

2022-03-15 16:21:52.145631: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2022-03-15 16:21:52.167418: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2096875000 Hz
2022-03-15 16:21:52.168281: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5643bd94b6a0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2022-03-15 16:21:52.168352: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2022-03-15 16:21:52.169885: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-03-15 16:21:52.169909: E tensorflow/stream_executor/cuda/cuda_driver.cc:318] failed call to cuInit: UNKNOWN ERROR (303)
2022-03-15 16:21:52.169922: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (xx): /proc/driver/nvidia/version does not exist
[ INFO  ] data augment is  False
WARNING:tensorflow:From /home/kearney/.conda/envs/k210/lib/python3.7/site-packages/tensorflow_core/python/data/util/random_seed.py:58: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
[ INFO  ] data augment is  False
WARNING:tensorflow:From /home/kearney/.conda/envs/k210/lib/python3.7/site-packages/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.
Instructions for updating:
If using Keras pass *_constraint arguments to layers.
Traceback (most recent call last):
  File "./keras_train.py", line 155, in <module>
    args.prune_frequency)
  File "./keras_train.py", line 51, in main
    yolo_model, yolo_model_warpper = network([image_size[0], image_size[1], 3], len(h.anchors[0]), class_num, alpha=depth_multiplier)
  File "/home/kearney/Downloads/k210/Yolo-for-k210/Yolo-for-k210/models/yolonet.py", line 19, in yolo_mobilev1
    base_model.load_weights('data/mobilenet_v1_base_7.h5')
  File "/home/kearney/.conda/envs/k210/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py", line 182, in load_weights
    return super(Model, self).load_weights(filepath, by_name)
  File "/home/kearney/.conda/envs/k210/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/network.py", line 1373, in load_weights
    saving.load_weights_from_hdf5_group(f, self.layers)
  File "/home/kearney/.conda/envs/k210/lib/python3.7/site-packages/tensorflow_core/python/keras/saving/hdf5_format.py", line 645, in load_weights_from_hdf5_group
    original_keras_version = f.attrs['keras_version'].decode('utf8')
AttributeError: 'str' object has no attribute 'decode'
make: *** [Makefile:35：train] 错误 1

$ pip list
Package                       Version
----------------------------- -----------
absl-py                       1.0.0
astor                         0.8.1
cached-property               1.5.2
certifi                       2021.10.8
cycler                        0.11.0
gast                          0.2.2
google-pasta                  0.2.0
grpcio                        1.44.0
h5py                          3.6.0
imageio                       2.9.0
imgaug                        0.2.9
importlib-metadata            4.11.3
Keras-Applications            1.0.8
Keras-Preprocessing           1.1.2
kiwisolver                    1.4.0
Markdown                      3.3.6
matplotlib                    3.0.3
networkx                      2.6.3
numpy                         1.16.2
opencv-python                 4.0.0.21
opt-einsum                    3.3.0
Pillow                        6.2.0
pip                           21.2.2
protobuf                      3.19.4
pyparsing                     3.0.7
python-dateutil               2.8.2
PyWavelets                    1.1.1
scikit-image                  0.15.0
scipy                         1.2.1
setuptools                    58.0.4
Shapely                       1.8.1.post1
six                           1.16.0
tensorboard                   1.15.0
tensorflow                    1.15.0
tensorflow-estimator          1.15.1
tensorflow-model-optimization 0.1.1
termcolor                     1.1.0
typing_extensions             4.1.1
Werkzeug                      2.0.3
wheel                         0.37.1
wrapt                         1.14.0
zipp                          3.7.0