# rm_summer_camp2020

**Repository Path**: StudyingLover/rm_summer_camp2020

## Basic Information

- **Project Name**: rm_summer_camp2020
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-12-15
- **Last Updated**: 2021-12-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

0.运行需要有numpy，tensorflow，keras，PIL，matplotlib等库
keras要单独再下载一遍！！！
1.运行时可能会出现关于tensorflow的警告
如：W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU 
set up on your machine.
 W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
 W tensorflow/stream_executor/cuda/cuda_driver.cc:312] failed call to cuInit: UNKNOWN ERROR (303)
 I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: LAPTOP-01SAUGPJ
 I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: LAPTOP-01SAUGPJ
 I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep 
Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
 I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1fee3c24270 initialized for platform Host 
(this does not guarantee that XLA will be used). Devices:
I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version      
WARNING:tensorflow:From e:/机器人/2019RM/summer-camp/官方营算法/my_code/main.py:34: Sequential.predict_classes (from tensorflow.python.keras.engine.sequential) is deprecated and will be removed after 2021-01-01.
Instructions for updating:
Please use instead:* `np.argmax(model.predict(x), axis=-1)`,   if your model does multi-class classification   (e.g. if it uses a `softmax` last-layer activation).* `(model.predict(x) > 0.5).astype("int32")`,   if your model does binary classification   (e.g. if it uses a `sigmoid` last-layer activation).

请无视！！！
2.双击运行后请稍等
3.如无法运行，请先运行model-train