ilmonteux

import numpy as np
import keras.backend as K
import tensorflow as tf

def metrics_np(y_true, y_pred, metric_name, metric_type='standard', drop_last = True, mean_per_class=False, verbose=False):
    """ 
    Compute mean metrics of two segmentation masks, via numpy.
    
    IoU(A,B) = |A & B| / (| A U B|)
    Dice(A,B) = 2*|A & B| / (|A| + |B|)

scottsb

#!/bin/bash

# ---------------------------------------------------------
# Customizable Settings
# ---------------------------------------------------------

MOUNT_POINT="${CASE_SAFE_MOUNT_POINT:-${HOME}/casesafe}"
VOLUME_PATH="${CASE_SAFE_VOLUME_PATH:-${HOME}/.casesafe.dmg.sparseimage}"
VOLUME_NAME="${CASE_SAFE_VOLUME_NAME:-casesafe}"
VOLUME_SIZE="${CASE_SAFE_VOLUME_SIZE:-60g}"

masak

Ok, I geeked out, and this is probably more information than you need. But it completely answers the question. Sorry. ☺

Locally, I'm at this commit:

$ git show
commit d6cd1e2bd19e03a81132a23b2025920577f84e37
Author: jnthn <jnthn@jnthn.net>
Date:   Sun Apr 15 16:35:03 2012 +0200

When I added FIRST/NEXT/LAST, it was idiomatic but not quite so fast. This makes it faster. Another little bit of masak++'s program.