在对象检测的Tensorflow API中训练期间,Tensorflow 1.15显示损失= 10.34,步长= 0

问题描述 投票:0回答:1
我已经尝试实现Tensorflow对象检测API,并且在培训期间,我的结果低于预期,并且运行时间很长,而没有得到更多的结果。

我在测试集中只使用了7张图像和3张图像,仍然没有得到更多结果

我正在使用Tensorflow1.15

INFO:tensorflow:Done calling model_fn. I1207 15:04:32.265669 9380 estimator.py:1150] Done calling model_fn. INFO:tensorflow:Create CheckpointSaverHook. I1207 15:04:32.267668 9380 basic_session_run_hooks.py:541] Create CheckpointSaverHook. INFO:tensorflow:Graph was finalized. I1207 15:04:37.474951 9380 monitored_session.py:240] Graph was finalized. 2019-12-07 15:04:37.478682: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 2019-12-07 15:04:37.494165: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll 2019-12-07 15:04:37.832387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: name: GeForce 830M major: 5 minor: 0 memoryClockRate(GHz): 1.15 pciBusID: 0000:0a:00.0 2019-12-07 15:04:37.841191: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll 2019-12-07 15:04:37.853644: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_100.dll 2019-12-07 15:04:37.865194: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_100.dll 2019-12-07 15:04:37.875714: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_100.dll 2019-12-07 15:04:37.889732: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_100.dll 2019-12-07 15:04:37.905515: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_100.dll 2019-12-07 15:04:37.924530: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll 2019-12-07 15:04:37.932013: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0 2019-12-07 15:04:39.474886: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix: 2019-12-07 15:04:39.480670: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0 2019-12-07 15:04:39.488584: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N 2019-12-07 15:04:39.493975: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1389 MB memory) -> physical GPU (device: 0, name: GeForce 830M, pci bus id: 0000:0a:00.0, compute capability: 5.0) INFO:tensorflow:Restoring parameters from training/model.ckpt-0 I1207 15:04:39.522326 9380 saver.py:1284] Restoring parameters from training/model.ckpt-0 WARNING:tensorflow:From C:\Users\milan\Downloads\models-master\TFO\lib\site-packages\tensorflow_core\python\training\saver.py:1069: get_checkpoint_mtimes (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version. Instructions for updating: Use standard file utilities to get mtimes. W1207 15:04:42.039816 9380 deprecation.py:323] From C:\Users\milan\Downloads\models-master\TFO\lib\site-packages\tensorflow_core\python\training\saver.py:1069: get_checkpoint_mtimes (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version. Instructions for updating: Use standard file utilities to get mtimes. INFO:tensorflow:Running local_init_op. I1207 15:04:43.612918 9380 session_manager.py:500] Running local_init_op. INFO:tensorflow:Done running local_init_op. I1207 15:04:44.214592 9380 session_manager.py:502] Done running local_init_op. INFO:tensorflow:Saving checkpoints for 0 into training/model.ckpt. I1207 15:04:57.934353 9380 basic_session_run_hooks.py:606] Saving checkpoints for 0 into training/model.ckpt. 2019-12-07 15:05:11.850788: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll 2019-12-07 15:05:12.891584: W tensorflow/stream_executor/cuda/redzone_allocator.cc:312] Internal: Invoking ptxas not supported on Windows Relying on driver to perform ptx compilation. This message will be only logged once. 2019-12-07 15:05:13.030221: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_100.dll INFO:tensorflow:loss = 10.3425045, step = 0 I1207 15:05:22.538612 9380 basic_session_run_hooks.py:262] loss = 10.3425045, step = 0

python tensorflow deep-learning object-detection-api
1个回答
0
投票
您解决问题了吗?我有同样的问题。我使用自己的数据集,该数据集可以很好地与r-cnn网络配合使用,但是当我使用SSD网络时,它总是卡在步骤0上。
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