ankitshekhawat

import kmc2
from sklearn.cluster import MiniBatchKMeans
from skimge.color import lab2rgb, rgb2lab

def get_colors(array, clusters=3):
    labs = rgb2lab([array]).squeeze()
    seeding = kmc2.kmc2(labs, clusters)
    kmeans = MiniBatchKMeans(n_clusters = clusters, init=seeding)
    kmeans.fit(np.squeeze(labs))
    LABELS = kmeans.labels_

ankitshekhawat

from scipy.ndimage.morphology import binary_erosion
from keras.utils import to_categorical
from fast_slic.avx2 import SlicAvx2


def clip_to_superpixel(image, z, num_segments=100, erosion=12, threshold=0.5, iou_thresh=0.5):
    fast_slic = SlicAvx2(num_components=num_segments, compactness=10, quantize_level=1)
    segments = fast_slic.iterate(image)
    onehot = to_categorical(segments,  num_classes=num_segments, dtype='uint8')
    threshold = (np.max(z)+np.min(z))*threshold

ankitshekhawat

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

ankitshekhawat

def recall_top_k(y_true, y_pred):
    # get batch size
    batch_size = y_pred.shape[0]
    
    # get pairwise distances
    dists  = _pairwise_distances(y_pred)
    
    # get indexes of the closest item in the batch predictions 
    # (item itself is always the top_k, so hence getting the second top K)
    # top_k function gives indexes for the highest values so subtracting from 2(or a high enough number) to invert the matrix

ankitshekhawat

#!/bin/env bash

pip3 uninstall pillow

apt install \
    libjpeg-turbo8-dev \
    zlib1g-dev \
    libtiff5-dev \
    liblcms2-dev \
    libfreetype6-dev \

ankitshekhawat

{
    "lines": {
        "blueline": {
            "name": "Blue Line",
            "color": "blue",
            "type": "subway"
        },
        "redline": {
            "name": "Red Line",
            "color": "red",

ankitshekhawat

ankitshekhawat

ankitshekhawat

import aria2p


# parellel run:
# aria2c --enable-rpc --rpc-listen-all
# Spawn aria server
import subprocess
subprocess.call(['gnome-terminal', '-e', 'aria2c --enable-rpc --rpc-listen-all'])

ankitshekhawat

import thinplate as tps
from PIL import Image
import morphops
import cv2
# helper function for https://github.com/cheind/py-thin-plate-spline

import thinplate as tps
from PIL import Image
import cv2