m1

app.py

@@ -1,5 +1,5 @@
 # from pydub import AudioSegment
-import function
+import model
 import streamlit as st
 
 
@@ -18,7 +18,7 @@ if option == 'Text':
     with col2:
         b = st.button("Post", key='bb', help='Click to Post')
     col3, col4 = st.columns(2)
-    de = function.detect([pred])
+    de = model.detect([pred])
     if a:
         st.markdown(de[0])
     if b:
@@ -37,7 +37,7 @@ if option == 'Sound File':
             e = st.button("Detect")
         with col7:
             f = st.button("Post")
-        fg = function.detect([function.voice_file(fileObject.name)])
+        fg = model.detect([model.voice_file(fileObject.name)])
         if d:
             audio_file = open(fileObject.name, 'rb')
             audio_bytes = audio_file.read()

function.py

@@ -1,41 +0,0 @@
-import model
-from sklearn.feature_extraction.text import CountVectorizer
-
-
-def detect_hate_speech(sample):
-    cv = CountVectorizer()
-    vect = cv.transform(sample).toarray()
-    pred_prob = np.max(model.predict_proba(vect))
-    pred = model.predict(vect)
-    return pred, pred_prob
-
-
-def detect(sample):
-    hatespeech = detect_hate_speech(sample)
-    mp = "Try again"
-    if hatespeech[0] == 0:
-        mp = "Hate Speech Detected"
-    elif hatespeech[0] == 1:
-        mp = "Offensive Language Detected"
-    elif hatespeech[0] == 2:
-        mp = "NO Hate Speech Detected"
-    return mp, hatespeech[1], hatespeech[0]
-
-
-def voice_file(file):
-    speech_config = speechsdk.SpeechConfig(subscription=api_key, endpoint=endpoint)
-    speech_config.speech_recognition_language = "en-US"
-    speech_config.set_profanity(speechsdk.ProfanityOption.Raw)
-    audio_config = speechsdk.audio.AudioConfig(filename=file)
-    speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config, audio_config=audio_config)
-    speech_recognition_result = speech_recognizer.recognize_once_async().get()
-    if speech_recognition_result.reason == speechsdk.ResultReason.RecognizedSpeech:
-        print(speech_recognition_result.text)
-        return speech_recognition_result.text
-    elif speech_recognition_result.text == "":
-        return "$empty$"
-    elif speech_recognition_result.reason == speechsdk.ResultReason.NoMatch:
-        return speech_recognition_result.no_match_details
-    elif speech_recognition_result.reason == speechsdk.ResultReason.Canceled:
-        cancellation_details = speech_recognition_result.cancellation_details
-        return cancellation_details.reason

model.py

@@ -23,3 +23,41 @@ model = LogisticRegression(max_iter=1000)
 model.fit(X_train,y_train)
 y_pred = model.predict(X_test)
 
+def detect_hate_speech(sample):
+    vect = cv.transform(sample).toarray()
+    pred_prob = np.max(model.predict_proba(vect))
+    pred = model.predict(vect)
+    return pred, pred_prob
+
+
+def detect(sample):
+    hatespeech = detect_hate_speech(sample)
+    mp = "Try again"
+    if hatespeech[0] == 0:
+        mp = "Hate Speech Detected"
+    elif hatespeech[0] == 1:
+        mp = "Offensive Language Detected"
+    elif hatespeech[0] == 2:
+        mp = "NO Hate Speech Detected"
+    return mp, hatespeech[1], hatespeech[0]
+
+
+def voice_file(file):
+    speech_config = speechsdk.SpeechConfig(subscription=api_key, endpoint=endpoint)
+    speech_config.speech_recognition_language = "en-US"
+    speech_config.set_profanity(speechsdk.ProfanityOption.Raw)
+    audio_config = speechsdk.audio.AudioConfig(filename=file)
+    speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config, audio_config=audio_config)
+    speech_recognition_result = speech_recognizer.recognize_once_async().get()
+    if speech_recognition_result.reason == speechsdk.ResultReason.RecognizedSpeech:
+        print(speech_recognition_result.text)
+        return speech_recognition_result.text
+    elif speech_recognition_result.text == "":
+        return "$empty$"
+    elif speech_recognition_result.reason == speechsdk.ResultReason.NoMatch:
+        return speech_recognition_result.no_match_details
+    elif speech_recognition_result.reason == speechsdk.ResultReason.Canceled:
+        cancellation_details = speech_recognition_result.cancellation_details
+        return cancellation_details.reason
+
+