lorenzob

# boxes are numbered from 1 to 100 (hence all the +1...)

import random

prisoners=24
attempts=prisoners//2

DEBUG = True

lorenzob

def trim_border(base_img, th=255, m=(1, 1, 1, 1)):

    if not isinstance(m, tuple):
        m = (m, m, m, m)

    if base_img.size == 0:
        return base_img, [0,0,0,0]

    img = base_img

lorenzob

import sys
import time
import cv2
import numpy as np

'''
Based on this code by Abid Rahman K:

https://dsp.stackexchange.com/questions/2564/opencv-c-connect-nearby-contours-based-on-distance-between-them

lorenzob

#!/usr/bin/env th
--
-- Outputs the number of parameters in a network for a single image
-- in evaluation mode.

require 'torch'
require 'nn'
require 'dpnn'

-- binary to ascii

lorenzob

        double learningRate = 0.01;
        int numHiddenNodes = 64*2;
        int numInnerNodes = 32;
        int numOutputs = 2;

        double regularization = 0.1;

		MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
                .seed(seed)
                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)