shangshang-wang

def fib_bottom_up(n):
    if n == 1 or n == 2:
        return 1
    bottom_up = [None] * (n+1)
    bottom_up[1] = 1
    bottom_up[2] = 1
    for i in range(3, n+1):
        bottom_up[i] = bottom_up[i-1] + bottom_up[i-2]
    return bottom_up[n]

jeasinema

import numpy as np 
import matplotlib.pyplot as plt 
import seaborn as sns


def smooth(y, box_pts):
    box_pts = max(box_pts, 1) if len(y) > box_pts else 1
    box = np.ones(box_pts)/box_pts
    y_smooth = np.convolve(y, box, mode='valid')
    return y_smooth

jeasinema

import torch
from torchvision import transforms
import cv2
import numpy as np
import types
from numpy import random


def intersect(box_a, box_b):
    max_xy = np.minimum(box_a[:, 2:], box_b[2:])

jubjamie

import tensorflow as tf
from tensorflow.python.platform import gfile
with tf.Session() as sess:
    model_filename ='PATH_TO_PB.pb'
    with gfile.FastGFile(model_filename, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        g_in = tf.import_graph_def(graph_def)
LOGDIR='/logs/tests/1/'
train_writer = tf.summary.FileWriter(LOGDIR)