From e838384a0abf227c67db9599d64d0b1c08180a94 Mon Sep 17 00:00:00 2001
From: Dv04 <62090715+Dv04@users.noreply.github.com>
Date: Sat, 26 Aug 2023 11:58:16 +0530
Subject: [PATCH] Forms.py has disease list

---
 forms.py              | 7 ++++++-
 templates/camera.html | 0
 train.py              | 7 +------
 3 files changed, 7 insertions(+), 7 deletions(-)
 create mode 100644 templates/camera.html

diff --git a/forms.py b/forms.py
index d7d00f4..282f24c 100644
--- a/forms.py
+++ b/forms.py
@@ -1,11 +1,16 @@
 from flask_wtf import FlaskForm
 from wtforms import StringField, SubmitField, PasswordField, SelectField, IntegerField, TextAreaField, RadioField
 from wtforms.validators import DataRequired
+from Disease import list_column_names
 
+column_names = list_column_names("dataset/Training.csv")
 class DiseaseDetailsForm(FlaskForm):
-    pass
+    name = StringField("Name", validators=[DataRequired()])
+    disease_list = SelectField("Disease", choices=[(column_name, column_name) for column_name in column_names])
+    submit = SubmitField("Submit")
 
 class PatientDetailsForm(FlaskForm):
+    
     pass
 
 class LoginUserForm(FlaskForm):
diff --git a/templates/camera.html b/templates/camera.html
new file mode 100644
index 0000000..e69de29
diff --git a/train.py b/train.py
index 9142835..b7b0aa7 100644
--- a/train.py
+++ b/train.py
@@ -26,7 +26,6 @@
 plt.figure(figsize = (18,8))
 sns.barplot(x = "Disease", y = "Counts", data = temp_df)
 plt.xticks(rotation=90)
-plt.show()
 
 # Encoding the target value into numerical
 # value using LabelEncoder
@@ -77,7 +76,6 @@ def cv_scoring(estimator, X, y):
 plt.figure(figsize=(12,8))
 sns.heatmap(cf_matrix, annot=True)
 plt.title("Confusion Matrix for SVM Classifier on Test Data")
-plt.show()
 
 # Training and testing Naive Bayes Classifier
 nb_model = GaussianNB()
@@ -92,7 +90,6 @@ def cv_scoring(estimator, X, y):
 plt.figure(figsize=(12,8))
 sns.heatmap(cf_matrix, annot=True)
 plt.title("Confusion Matrix for Naive Bayes Classifier on Test Data")
-plt.show()
 
 # Training and testing Random Forest Classifier
 rf_model = RandomForestClassifier(random_state=18)
@@ -108,7 +105,6 @@ def cv_scoring(estimator, X, y):
 plt.figure(figsize=(12,8))
 sns.heatmap(cf_matrix, annot=True)
 plt.title("Confusion Matrix for Random Forest Classifier on Test Data")
-plt.show()
 
 # Training the models on whole data
 final_svm_model = SVC()
@@ -141,7 +137,6 @@ def cv_scoring(estimator, X, y):
 
 sns.heatmap(cf_matrix, annot = True)
 plt.title("Confusion Matrix for Combined Model on Test Dataset")
-plt.show()
 
 symptoms = X.columns.values
 
@@ -189,5 +184,5 @@ def predictDisease(symptoms):
 	return predictions
 
 # Testing the function
-print(predictDisease("Itching,Skin Rash,Nodal Skin Eruptions"))
+print(predictDisease("Blister,Red Sore Around Nose,Yellow Crust Ooze"))