mahxn0

#coding=utf-8

import numpy as np
import cv2
import matplotlib.pyplot as plt
import os
import PIL
from PIL import Image
caffe_root = '/home/mahxn0/caffe/'
work_dir='/home/mahxn0/workspace/src/detectAndRecog/src/caffenet/model-googlenet-watch/'

mahxn0

import cv2 as cv
import argparse
import numpy as np
import os.path
import sys
import random

# Initialize the parameters
confThreshold = 0.3  # Confidence threshold
maskThreshold = 0.5  # Mask threshold

mahxn0

import argparse
import numpy as np
from tf_text_graph_common import *

parser = argparse.ArgumentParser(description='Run this script to get a text graph of '
                                             'Mask-RCNN model from TensorFlow Object Detection API. '
                                             'Then pass it with .pb file to cv::dnn::readNetFromTensorflow function.')
parser.add_argument('--input', required=True, help='Path to frozen TensorFlow graph.')
parser.add_argument('--output', required=True, help='Path to output text graph.')
parser.add_argument('--config', required=True, help='Path to a *.config file is used for training.')

mahxn0

#  codinf=utf-8
import sys
sys.path.append('./utils/')
from matplotlib import pyplot as plt
import numpy as np
from PIL import Image
import tensorflow as tf
import get_dataset_colormap
import os
import matplotlib