python OrderDict to Dict

od = OrderedDict([('name', 'signature'), ('pose', 'Unspecified'), ('bndbox', OrderedDict([('xmin', '423'), ('ymin', '1237'), ('xmax', '785'), ('ymax', '1349')]))])

print(od)

output_dict = json.loads(json.dumps(av))

print(output_dict)

reference is here : https://stackoverflow.com/questions/20166749/how-to-convert-an-ordereddict-into-a-regular-dict-in-python3

keras model summary, print out for each layers property

from keras.layers import Input

from keras.applications import VGG16

vgg_model = VGG16(weights="imagenet", include_top=False, input_tensor=Input(shape=(224, 224, 3))) #the head FC layer off

#how many layers

print(len(vgg_model.layers))

#last layer

print(vgg_model.layers[-1].name)

#print whole layer

for idx, layer in enumerate(vgg_model.layers):

print(idx+1, '-----')

print(layer.output_shape)

print(layer.name)

print('--------')

#summary of model

vgg_model.summary()

using specific gpu device for TensorFlow

setting first or second gpu machine

CUDA_VISIBLE_DEVICES=0 python script_one.py
CUDA_VISIBLE_DEVICES=1 python script_two.py

another way
use first (it didn't work for me)

export CUDA_VISIBLE_DEVICE=0
./train.py

use second (it didn't work for me)

export CUDA_VISIBLE_DEVICE=1
./train.py

use both (it didn't work for me)

export CUDA_VISIBLE_DEVICE=0,1
./train.py

refer to here:
https://stackoverflow.com/questions/44135538/tensorflow-using-2-gpu-at-the-same-time

monitoring gpu status in command (terminal)

pip install gpustat
>gpustat -cp




monitoring continuously
>watch -n 0.5 -c gpustat -cp --color

find pdf file (or some exe file) in directories and copy it to another directory, python sample code

import os

import glob

from shutil import copyfile

files = []

start_dir = '/Volumes/input/'

output_path = '/Volumes/output/'

pattern = "*.pdf"

total = 0

for dir,_,_ in os.walk(start_dir):

files.extend(glob.glob(os.path.join(dir,pattern)))

for i,v in enumerate(files):

#found pdf files

print(total,i,v)

#extract filename only

filename = v.split('/')[-1]

#make new filename and output path

output_filename = output_path + str(total) + '_' + filename

#if file exist? then no copy

exist = glob.glob(output_filename)

#if not copy

if len(exist) == 0:

copyfile(v, output_filename)

#print out copied filename

print('copy! : ', output_filename)

#increase global count

total += 1