Update dependencies to make the app run again

app/__init__.py

@@ -1,10 +1,12 @@
 import logging
 import os
-from flask_uploads import UploadSet, IMAGES, configure_uploads
+from logging.handlers import RotatingFileHandler
+
 from flask import Flask
+from flask_bootstrap import Bootstrap4
+from flask_uploads import IMAGES, UploadSet, configure_uploads
+
 from config import Config
-from flask_bootstrap import Bootstrap
-from logging.handlers import RotatingFileHandler
 
 app = Flask(__name__)
 app.config.from_object(Config)
@@ -24,7 +26,7 @@
     file_handler.setLevel(logging.INFO)
     app.logger.addHandler(file_handler)
 
-bootstrap = Bootstrap(app)
+bootstrap = Bootstrap4(app)
 
 images = UploadSet('images', IMAGES)
 configure_uploads(app, images)

app/forms.py

@@ -1,11 +1,9 @@
-from flask_uploads import IMAGES, UploadSet, configure_uploads
 from flask_wtf import FlaskForm
+from flask_wtf.file import FileAllowed, FileField, FileRequired
 from wtforms import IntegerField
-from flask_wtf.file import FileField, FileAllowed, FileRequired
 from wtforms.fields.simple import SubmitField
 
 from app import images
-from app import app
 
 
 class UploadForm(FlaskForm):

app/routes.py

@@ -1,17 +1,14 @@
 import os
-import numbers
 
-from flask import render_template, request, abort
-from flask.helpers import url_for
-from werkzeug import redirect, secure_filename
+from flask import render_template, request
+from flask.json import jsonify
+from webcolors import hex_to_rgb
+from werkzeug.utils import secure_filename
 
 from app import app
-from app import images
 from app.forms import UploadForm
 from app.utils.kmeans import Kmeans
 from app.utils.knn import Knn
-from webcolors import hex_to_rgb
-from flask.json import jsonify
 
 ALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg'])
 

app/utils/kmeans.py

@@ -1,6 +1,5 @@
 import cv2
 import imutils
-
 from sklearn.cluster import KMeans
 from webcolors import rgb_to_hex
 
@@ -18,7 +17,6 @@ def clusterize(self):
         # and improve the quality of the clustering
         self.model = KMeans(n_clusters = self.clusters,
                             init = 'k-means++',
-                            n_jobs = -1,
                             n_init = 10,
                             max_iter = 300,
                             algorithm='elkan')

app/utils/knn.py

@@ -1,6 +1,7 @@
-from sklearn.neighbors import KNeighborsClassifier
-from sklearn import preprocessing
 import pandas as pd
+from sklearn import preprocessing
+from sklearn.neighbors import KNeighborsClassifier
+
 
 class Knn:
 

config.py

@@ -1,5 +1,6 @@
 import os
 
+
 class Config(object):
     SECRET_KEY = os.environ.get('SECRET_KEY') or 'you-will-never-guess'
     UPLOADS_DEFAULT_DEST = os.environ.get('UPLOADS_DEFAULT_DEST') or '/tmp'

requirements.txt

@@ -1,17 +1,17 @@
-Flask==1.1.2
-opencv-python==4.2.0.34
-opencv-python-headless==4.2.0.34
-Werkzeug<1
+Flask==3.0.0
+opencv-python==4.8.1.78
+opencv-python-headless==4.8.1.78
+Werkzeug==3.0.0
 sklearn==0.0
-python-dotenv==0.13.0
-Flask-WTF==0.14.3
-WTForms==2.3.1
-Flask-Uploads==0.2.1
-numpy==1.18.4
-Pillow==7.1.2
-psycopg2==2.8.5
-gunicorn==20.0.4
-webcolors==1.11.1
-pandas==1.0.3
-Bootstrap-Flask==1.3.1
-imutils==0.5.3
+python-dotenv==1.0.0
+Flask-WTF==1.2.1
+WTForms==3.1.0
+Flask-Reuploaded==1.4.0
+numpy==1.26.1
+Pillow==10.1.0
+psycopg2==2.9.9
+gunicorn==21.2.0
+webcolors==1.13
+pandas==2.1.1
+Bootstrap-Flask==2.3.2
+imutils==0.5.4