im trying to figure out how to use SVM for image classification using images from my own dataset, to which im using the notebook from his link: https://github.com/whimian/SVM-Image-Classification. The problem is that, for whatever other project i use skimage it works alright, but for this one i get the error described above in the title in the following line:
img = skimage.io.imread(file)
I already used the commands pip uninstall scikit-image and install and still didn't work.
Moreover, the following errors occurs in the down lines, im not sure if they are related to this problem:
image_dataset.data, image_dataset.target, test_size=0.3,random_state=109
NameError: name 'image_dataset' is not defined
clf.fit(X_train, y_train)
NameError: name 'X_train' is not defined
And for visualization, here's the code snipped to which the error belongs to:
image_dir = Path(container_path)
folders = [directory for directory in image_dir.iterdir() if directory.is_dir()]
categories = [fo.name for fo in folders]
descr = "A image classification dataset"
images = []
flat_data = []
target = []
for i, direc in enumerate(folders):
for file in direc.iterdir():
img = skimage.io.imread(file)
img_resized = resize(img, dimension, anti_aliasing=True, mode='reflect')
flat_data.append(img_resized.flatten())
images.append(img_resized)
target.append(i)
flat_data = np.array(flat_data)
target = np.array(target)
images = np.array(images)
return Bunch(data=flat_data,
target=target,
target_names=categories,
images=images,
DESCR=descr)
As for the imports:
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
%matplotlib notebook
from sklearn import svm, metrics, datasets
from sklearn.utils import Bunch
from sklearn.model_selection import GridSearchCV, train_test_split
from skimage.io import imread
from skimage.transform import resize
