From a3ffd69a0412dbe1da7a2f788dcf060ce7c83391 Mon Sep 17 00:00:00 2001
From: Caroline DE POURTALES <cdepourt@montana.irit.fr>
Date: Mon, 27 Jun 2022 11:15:50 +0200
Subject: [PATCH] assets
---
assets/course_data_format.html | 6 +++---
assets/course_decision_tree.html | 8 +++++---
assets/course_random_forest.html | 16 ++++++++++++++++
assets/typography.css | 4 ++++
callbacks.py | 24 ++++++++++++++++++++----
5 files changed, 48 insertions(+), 10 deletions(-)
create mode 100644 assets/course_random_forest.html
diff --git a/assets/course_data_format.html b/assets/course_data_format.html
index 59a3085..a717f14 100644
--- a/assets/course_data_format.html
+++ b/assets/course_data_format.html
@@ -11,7 +11,7 @@
<h2> An option to add information on model </h2>
<h3> Why ? </h3>
-<p> There is a switch button, you can use it when you want to attach the csv you trained your model on or a feature mapping. This is useful when the values are categorical.
+<p> There is a switch button, you can use it when you want to attach the data (csv) you trained your model on or a feature mapping (txt). This is useful when the values are categorical.
</p>
<h3> How ? </h3>
@@ -22,11 +22,11 @@ If you decide to upload the feature mapping, it is a .txt file.
<h2> What kind of model can I upload ? </h2>
-<p> You can only import .pkl models.</p>
+<p> You can only import .pkl models. But it works with joblib and pickle libraries. </p>
<h2> What should the format of the instance be ? </h2>
-<p> You can either upload a .txt file containing hte instance with the format : feature1=value1,feature2=value2,... where feature1, feature2 are the names of the columns.
+<p> You can either upload a .txt file containing the instance with the format : feature1=value1,feature2=value2,... where feature1, feature2 are the names of the columns.
But you can also upload a json of your instance.</p>
diff --git a/assets/course_decision_tree.html b/assets/course_decision_tree.html
index b07a373..f20dff9 100644
--- a/assets/course_decision_tree.html
+++ b/assets/course_decision_tree.html
@@ -2,13 +2,15 @@
<html lang="en">
<head>
<meta charset="UTF-8">
- <title>What kinf of model, data, or instance can I upload ?</title>
+ <title>Decision Tree</title>
</head>
<body>
-<h1> What library am I able to use on the platform ?</h1>
-
+<h2> What library am I able to use on the platform ?</h2>
<p> Only models from scikit-learn are allowed.</p>
+<h2> Do I have to upload data ?</h2>
+You have to upload data or feature mapping when you have categorical data.
+
</body>
</html>
\ No newline at end of file
diff --git a/assets/course_random_forest.html b/assets/course_random_forest.html
new file mode 100644
index 0000000..d71522e
--- /dev/null
+++ b/assets/course_random_forest.html
@@ -0,0 +1,16 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+ <meta charset="UTF-8">
+ <title>Random Forest</title>
+</head>
+<body>
+
+<h2> What library am I able to use on the platform ?</h2>
+<p> You can upload RandomForestClassifier from sklearn library or RF2001 models (from Aniti's team).</p>
+
+<h2> Do I have to upload data ?</h2>
+You need to upload the dataset your machine learning model trained on.
+
+</body>
+</html>
\ No newline at end of file
diff --git a/assets/typography.css b/assets/typography.css
index d7e5154..6fdf27a 100644
--- a/assets/typography.css
+++ b/assets/typography.css
@@ -2,6 +2,10 @@ body {
font-family: sans-serif;
}
+H1 {
+ font-family:Georgia, 'Times New Roman', Times, serif;
+}
+
H4 {
font-size: 20px;
text-decoration-line:underline;
diff --git a/callbacks.py b/callbacks.py
index 906b09c..8213b61 100644
--- a/callbacks.py
+++ b/callbacks.py
@@ -29,12 +29,28 @@ def register_callbacks(app):
page_list = ['home', 'course', 'application']
# For home directory
- page_home = dbc.Row([])
+ welcome_message = html.Div(html.Iframe(
+ src=app.get_asset_url("welcome.html"),
+ style={"height": "1067px", "width": "100%"},
+ ))
+ page_home = dbc.Row([welcome_message])
# For course directory
+ course_data_format = html.Div(html.Iframe(
+ src=app.get_asset_url("course_data_format.html"),
+ style={"height": "1067px", "width": "100%"},
+ ))
+ course_decision_tree = html.Iframe(
+ src="assets/course_decision_tree.html",
+ style={"height": "1067px", "width": "100%"},
+ )
+ course_random_forest = html.Iframe(
+ src="assets/course_random_forest.html",
+ style={"height": "1067px", "width": "100%"},
+ )
main_course = dcc.Tabs(children=[
- dcc.Tab(label='Data format', children=[]),
- dcc.Tab(label='Course Decision Tree', children=[]),
- dcc.Tab(label='Course Random Forest', children=[])])
+ dcc.Tab(label='Data format', children=[course_data_format]),
+ dcc.Tab(label='Course Decision Tree', children=[course_decision_tree]),
+ dcc.Tab(label='Course Random Forest', children=[course_random_forest])])
page_course = dbc.Row([main_course])
# For the application
--
GitLab