JonathanLoscalzo

JonathanLoscalzo

import torch
import torchvision as tv


class ImagesDataset(torch.utils.data.Dataset):
    def __init__(self, df, transform=None,
                 loader=tv.datasets.folder.default_loader):
        self.df = df
        self.transform = transform
        self.loader = loader

JonathanLoscalzo

class ImagesDataset(torch.utils.data.Dataset):
    pass

class Net(nn.Module):
    pass

model = Net()
optimizer = torch.optim.SGD(model.parameters(), lr=0.01)
scheduler = lr_scheduler.StepLR(optimizer, step_size=30, gamma=0.1)
criterion = torch.nn.MSELoss()

JonathanLoscalzo

{
0: "tench, Tinca tinca",
1: "goldfish, Carassius auratus",
2: "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
3: "tiger shark, Galeocerdo cuvieri",
4: "hammerhead, hammerhead shark",
5: "electric ray, crampfish, numbfish, torpedo",
6: "stingray",
7: "cock",
8: "hen",

JonathanLoscalzo

import torch
import torchvision
def get_model():
  return torchvision.models.resnet18(pretrained=True)
def get_pred(model):
  return model(torch.rand([1,3,224,224]))

model = get_model()
for i in range(1,10000):
  get_pred(model)

JonathanLoscalzo

JonathanLoscalzo

def make_weights_for_balanced_classes(images, nclasses):                        
    count = [0] * nclasses                                                      
    for item in images:                                                         
        count[item[1]] += 1                                                     
    weight_per_class = [0.] * nclasses                                      
    N = float(sum(count))                                                   
    for i in range(nclasses):                                                   
        weight_per_class[i] = N/float(count[i])                                 
    weight = [0] * len(images)                                              
    for idx, val in enumerate(images):                                          

JonathanLoscalzo

#!/bin/sh

if [ "$PYENV_VERSION" -ne "" ]
then
    name=`pyenv version-name`
    python=`pyenv which python`
else
    name=`basename "$VIRTUAL_ENV"`
    python="$VIRTUALENV/bin/python"
fi

JonathanLoscalzo

JonathanLoscalzo

const AWS = require('aws-sdk')
const rek = new AWS.Rekognition();

var configuration = {
    AWSAccessKeyId: process.env.AWSAccessKeyId,
    AWSSecretKey: process.env.AWSSecretKey
}

AWS.config.update({
    accessKeyId: configuration.AWSAccessKeyId,