我正在raspberrypi 3上运行keras程序并获得以下细分失败。该程序在我的笔记本电脑上完美运行。使用pip安装和升级KERAS。使用.WHL为Raspberry Pi 3安装了TensorFlow。
Using TensorFlow backend.
Compiling Labels file...
Labels file compiled!
Loading pretrained model...
Adding additional layers...
Compiling new model file...
Model compiled!
Found 408 images belonging to 5 classes.
Found 87 images belonging to 5 classes.
Training model...
Epoch 1/2
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.281032] Internal error: Oops: 5 [#2] SMP ARM
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.385182] Process python (pid: 2199, stack limit = 0xb5382210)
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.391273] Stack: (0xb5383df0 to 0xb5384000)
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.395690] 3de0: b5383e1c b5383e00 80152ac8 8014cc54
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.403985] 3e00: ace00004 b65d4cd8 b65d4cd8 b6552960 b5383ea4 b5383e20 8012e588 80152a84
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.412279] 3e20: b5383e6c b5383e30 800894b4 8048d910 4b71ddf2 20000113 b601d500 20000113
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.420574] 3e40: b601d500 80869e00 80869e00 a7f77000 00000000 00000040 80869e00 b5802800
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.428869] 3e60: 80869e00 60000113 60000113 801306dc 6a6ff000 ace00000 b5383ea4 b5383fb0
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.437164] 3e80: ace00000 00000817 6a6ff000 a7df1c00 a7df1c38 00000055 b5383efc b5383ea8
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.445459] 3ea0: 805b9808 8012d680 805bde5c 8085d3c0 8086060c 8086a080 b5383ee4 b5383ec8
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.453754] 3ec0: 80028c74 00000000 00000800 00000000 00000009 80865584 00000817 805b94c8
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.462049] 3ee0: 6a6ff000 b5383fb0 00000000 00000000 b5383fac b5383f00 800091e8 805b94d4
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.470345] 3f00: 0000000a 60000193 00000000 00000000 01400000 00000000 6b9f71d0 3fcc5a7f
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.478639] 3f20: b5383f4c b5383f30 8007d258 800d96c8 b601cdc0 8085a4ec 00000000 00000000
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.486933] 3f40: b5383f64 b5383f50 800295e8 8007d1e4 00000000 8085a4ec b5383f8c b5383f68
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.495227] 3f60: 8007107c 80029550 b5383fb0 73cfc58c 20000010 ffffffff 10c5383d 10c5387d
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.503522] 3f80: b5383f9c 7498e034 80000010 7498e034 80000010 ffffffff 10c5383d 10c5387d
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.511817] 3fa0: 00000000 b5383fb0 805b90e4 800091ac 000000e0 6a6ff000 00a96780 6a6fefd0
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.520111] 3fc0: 000000f8 00000000 66bfed40 00000000 fffff800 00000000 00000000 66bfecfc
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.528405] 3fe0: 6a6feff0 66bfea80 7498df00 7498e034 80000010 ffffffff 00000000 00000000
Message from syslogd@raspberrypi at Sep 30 20:57:40 ...
kernel:[ 3638.608041] Code: e8bd4000 e5913004 ee1dcf90 e3130001 (e5903148)
代码段：
import numpy as np
import os, sys
import glob
import argparse
from keras import __version__
from keras.preprocessing import image
from keras.models import Model
from keras.layers import Input, Flatten, Dense, GlobalAveragePooling2D
from keras.preprocessing.image import ImageDataGenerator
from keras.applications.resnet50 import ResNet50, preprocess_input
...
#Code skipped
...
print ("Model compiled!") #Section causing the error begins here
train_datagen = ImageDataGenerator(
preprocessing_function=preprocess_input,
rotation_range = 30,
width_shift_range = 0.25,
height_shift_range = 0.25,
shear_range = 0.25,
zoom_range = 0.25,
horizontal_flip = True
)
test_datagen = ImageDataGenerator(
preprocessing_function=preprocess_input,
rotation_range = 30,
width_shift_range = 0.25,
height_shift_range = 0.25,
shear_range = 0.25,
zoom_range = 0.25,
horizontal_flip = True
)
train_generator = train_datagen.flow_from_directory(
args.train_dir,
target_size=(IM_WIDTH, IM_HEIGHT),
batch_size=batch_size,
)
validation_generator = test_datagen.flow_from_directory(
args.val_dir,
target_size=(IM_WIDTH, IM_HEIGHT),
batch_size=batch_size,
)
print ("Training model...")
history_tl = model_final.fit_generator(
train_generator,
validation_data = validation_generator,
class_weight = 'auto',
steps_per_epoch = num_training_steps,
epochs = num_epochs,
validation_steps = num_validation_steps)
print ("Model training completed!")
解决此问题的解决方案是否会以不同的方式安装TensorFlow？还是有一些更容易的运动能力？
分割故障通常与某些内存错误关联。这可能是因为RPI没有足够的内存。您可以尝试
sudo raspi-config
并将更多RAM分配给CPU（较少的RAM到GPU）。不过，我认为额外的64MB或32MB RAM不会有帮助。
我会避免在Raspberry Pi上训练任何深度学习模型。PI根本不够强大。您也许可以训练一些非常简单的神经网，但没有任何体面的神经网。我强烈建议您在桌面上培训您的模型，并将预训练的模型复制到Raspberry Pi，并加载模型和重量，并且仅运行向前计算。
resnet50是Raspberry Pi的大型型号。它包含超过20m的参数。在我的pi 3上运行一个向前的预测需要8秒钟。