asanakoy

import os
from os.path import join
import json
import cv2
import numpy as np
from tqdm import tqdm
import json
from pycocotools import mask as maskUtils
from scipy import ndimage
from PIL import Image

asanakoy

import cv2
from pathlib import Path
import os
import re
import pandas as pd
import numpy as np
from tqdm import tqdm


def main(input_dirs, output_dir):

asanakoy

import numpy as np
from scipy.signal import convolve
from numpy import linalg

# implementation of RGB2SUV http://vision.ucsd.edu/~spmallick/research/suv/index.html


def get_rot_mat(rot_v, unit=None):

asanakoy

#Proxy list graper
# https://github.com/abdallahelsokary/Proxy-Collector-/blob/master/Proxy_Collector.py
import urllib.request
import urllib.error
import time

def proxy_list():
    try:

asanakoy

Collecting horovod
  Using cached horovod-0.10.1.tar.gz
Building wheels for collected packages: horovod
  Running setup.py bdist_wheel for horovod: started
  Running setup.py bdist_wheel for horovod: still running...
  Running setup.py bdist_wheel for horovod: finished with status 'error'
  Complete output from command /beegfs/home/hd/hd_hd/hd_tn445/.venvs/tf_r1/bin/python -u -c "import setuptools, tokenize;__file__='/tmp/hd_tn445_job_5405240/pip-build-o4EglG/horovod/setup.py';f=getattr(tokenize, 'open', open)(__file__);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, __file__, 'exec'))" bdist_wheel -d /tmp/hd_tn445_job_5405240/tmpABgSLhpip-wheel- --python-tag cp27:
  running bdist_wheel
  running build
  running build_py

asanakoy

from tsne import bh_sne
import numpy as np
from skimage.transform import resize

from matplotlib import pyplot as plt

def gray_to_color(img):
    if len(img.shape) == 2:
        img = np.dstack((img, img, img))
    return img

asanakoy

# 23.03.16, Artsiom Sanakoyeu
import caffe
from caffe import layers as L, params as P


def alexnet(train_data_source, test_data_source, mean_file, train_batch_size=128, test_batch_size=50, database_backend=P.Data.LEVELDB):
    """
    Generate the caffe's network specification train_val.prototxt file for Alexnet model,
    described in the [AlexNet](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) publication.
    """

asanakoy

from caffeext import *
import caffe
import os.path
from scipy import misc
import time


def run_test_on_images(net, transformer, data, batch_size):
    data_blob_shape = net.blobs['data'].data.shape
    data_blob_shape = list(data_blob_shape)

asanakoy

name: "art_cnn"
input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 227
  dim: 227
}
layer {
  name: "conv1"