tejas07psk / melanoma-detection Goto Github PK

hi,
I'd like to run your code but I have problems

I'm using debian 11 and python 3.9.2, I installed numpy, matplotlib, scipy, opencv-python, and sklearn

I removed dataset

when I run Main.py I got:

$python3 Main.py
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^WELCOME TO THE MELANOMA-PREDICTION PROGRAM^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

 This is a nascent approach towards detecting Melanoma-Skin-Lesion, using OpenCV, NumPY, Matplotlib and SciKit in Python Programming Language. 

 This project utilizes some of the core concepts of 'DIGITAL IMAGE PROCESSING' & 'MACHINE LEARNING'. 

 This program can categorize the cancerous-lesion as Malignant, Benign or Negative. 

 Try understanding the meaning of each option, before selecting the appropriate one. 

 Available options are given below : 

 1.Create 'training-dataset' from the images of known ->MELANOMA<- types!! 

 2.Train classifiers and regressors on the created 'training-dataset'!! 

 3.Create 'testing-dataset' from the supervised images in temp folder!! 

 4.Predict results from the 'testcase.npz' numpy file!! 

 5.Print 'feature-descriptors' of images strored in numpy files, 'dataset.npz' or 'testcase.npz'!! 

 6.Plot 'Classifier/Regressor' graphs!! 

 7.Add the 'feature-sets' to 'testcase.npz' or 'dataset.npz' numpy files, to make mlmodels more accurate!! 

 8.Print only the selected 'feature-sets' of an image!! 

 9.List files present in valid 'project-directories'!! 

 10.Get color plates of an image!! 

 Enter 'e' to exit!! 

Enter your choice -
1
If you see a 'results' folder in the root directory of the project, delete the 'dataset' folder in it.

Now, before you proceed, just make sure that you have your corresponding images in the 'images' folder under the 'malignant', 'benign' or 'negative' directories.

If you haven't already made the directories, please make them and place the corresponding images in them.

The image file-names must be numeric starting from 0 in sequence under each category folder.

Eg. - 0.jpg, 1.jpg, 2.jpg, ..... etc

You must provide images under each category!!!

Just press any key when your are ready :
y
Enter the number of images you placed under the 'images/malignant' directory -
1
Traceback (most recent call last):
File "/home/usert/Downloads/Melanoma-Detection/Main.py", line 541, in
main_menu()
File "/home/usert/Downloads/Melanoma-Detection/Main.py", line 377, in main_menu
__createDataSet("malignant", int(input("Enter the number of images you placed under the 'images/malignant' directory - \n")))
File "/home/usert/Downloads/Melanoma-Detection/Main.py", line 106, in __createDataSet
dset, featnames = (np.load('dataset.npz'))['dset'], (np.load('dataset.npz'))['featnames']
File "/usr/lib/python3/dist-packages/numpy/lib/npyio.py", line 253, in getitem
return format.read_array(bytes,
File "/usr/lib/python3/dist-packages/numpy/lib/format.py", line 727, in read_array
raise ValueError("Object arrays cannot be loaded when "
ValueError: Object arrays cannot be loaded when allow_pickle=False

do you have idea how to fix this?