From 8a0ea7e5db8696a466e01d0b93d996e528afe8e8 Mon Sep 17 00:00:00 2001
From: Pawel Pieta <papi@dtu.dk>
Date: Wed, 29 Mar 2023 14:48:29 +0200
Subject: [PATCH] Type hints removed for better Python version compatibility
---
Chapter09/netEval.py | 23 ++++++++++++++++-------
Chapter09/sampleNetwork.py | 7 +++----
2 files changed, 19 insertions(+), 11 deletions(-)
diff --git a/Chapter09/netEval.py b/Chapter09/netEval.py
index b0a934f..6f3af21 100644
--- a/Chapter09/netEval.py
+++ b/Chapter09/netEval.py
@@ -11,20 +11,29 @@ import os
import glob
import skimage.io
import time
-from collections.abc import Callable
from sampleNetwork import netFunc
-def netEval(netFunc: Callable[np.array], dataPath: str, targetPath: str) -> tuple[float,float]:
- """
+def netEval(netFunc, dataPath, targetPath):
+ '''
Evaluates the accuracy of a classification model using provided dataset.
Parameters
----------
- netFunc - function of the network that takes an image and outputs a predicted class,\n
- dataPath - path to a folder with data,\n
- targetPath - path to a file with target labels (either .txt or .npy).
- """
+ netFunc : function
+ Function of the network that takes an image and outputs a predicted class
+ dataPath: string
+ Path to a folder with data
+ targetPath: string
+ Path to a file with target labels (either .txt or .npy)
+
+ Returns
+ -------
+ accuracy: float
+ Accuracy of the network on provided dataset
+ execTime:
+ Network prediction execution time
+ '''
assert callable(netFunc), "The first argument is not callable, it should be a network function."
assert os.path.exists(dataPath), f"Provided path: {dataPath} does not exist."
diff --git a/Chapter09/sampleNetwork.py b/Chapter09/sampleNetwork.py
index e659b5f..76c1bed 100644
--- a/Chapter09/sampleNetwork.py
+++ b/Chapter09/sampleNetwork.py
@@ -5,9 +5,8 @@ Created on Tue Mar 28 14:31:20 2023
@author: Pawel Pieta, papi@dtu.dk
"""
import numpy as np
-from collections.abc import Iterable
-def netFunc(images: np.array) -> Iterable[int]:
+def netFunc(images):
'''
Loads a feed forward neural network, and predicts the labels of each image in an array.
@@ -16,8 +15,8 @@ def netFunc(images: np.array) -> Iterable[int]:
images : numpy array
An array with grayscale images loaded with "skimage.io.imread(fname,as_gray=True)",
float datatype with pixel values between 0 and 1. The array has \n
- dimension N x H x W x C where N is the number of images, H is the height of the images \n
- , W is the width of the images and C is the number of channels in each image.
+ dimension N x H x W x C where N is the number of images, H is the height of the images, \n
+ W is the width of the images and C is the number of channels in each image.
Returns
-------
--
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