I am trying to run some prediction on pictures with Keras with pre-trained model vgg16. Here is my code:
from keras.applications import VGG16
from PIL import Image
from keras.applications import VGG19
from keras.applications import imagenet_utils
from keras.applications.inception_v3 import preprocess_input
from keras.preprocessing.image import img_to_array
from keras.preprocessing.image import load_img
import numpy as np
inputShape = (224, 224)
preprocess = imagenet_utils.preprocess_input
image = load_img("/home/pi/Pictures/cam_test/test.jpg",
target_size=inputShape)
image = img_to_array(image)
image = np.expand_dims(image, axis=0)
print(image.shape)
image = preprocess(image)
print("image")
# Loads arhitecture, weights, optimizer etc.
model = load_model('keras/src/vgg16_model.h5')
print("Prediction")
preds = model.predict(image)
print(preds)
P = imagenet_utils.decode_predictions(preds)
for (i, (imagenetID, label, prob)) in enumerate(P[0]):
print("{}. {}: {:.2f}%".format(i + 1, label, prob * 100))
I have installed all needed packages and I am using Python 3.4.2.
My hardware specifications are Raspberry Pi 3 with:
- 1GB RAM
- 4× ARM Cortex-A53, 1.2GHz (I clocked all CPU processors to 1.2GHz with command cpufreq-set)
- Added 1GB of swap with ZRAM (instructions here)
- Added 2GB of swap by changing this file (/etc/dphys-swapfile -> line CONF_SWAPSIZE=100 to CONF_SWAPSIZE=2048)
- Changed swappines from 60 to 80 in file /etc/sysctl.conf (because I have more swap than RAM, I sacrifice speed for more virtual RAM)
- Disabled oom-killer and overcommitting in file /etc/sysctl.conf (now programs cannot allocate more space that actually is free)
- OS: raspbian jessie
Now my question is can I optimise my Raspberry Pi even more (add more CPU power or RAM)?
Because now OS freezes or kills my python process even if I run this command:
sudo nice -n -20 sudo python3 vgg16_keras.py
Any links or suggestions will be highly appreciated.
