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21_22-J-02
Commit cc7f90b1 authored by NaweenTharuka's avatar NaweenTharuka
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updated: prosodic features

parent d84ae894
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Showing with 84 additions and 132 deletions
Presently/presently/users/emotiondetectionvideo.py
View file @ cc7f90b1
# -*- coding: utf-8 -*-
"""emotionDetection.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1o8opa083KfLohUfWs-oGfkdo9kuRN_eS
**Importing dependencies**
* pip install fer
* List item
"""
from fer import Video
from fer import FER
import os
......@@ -20,13 +5,9 @@ import sys
import pandas as pd
import numpy as np
"""Upload the video to the Google colab and get the path of the video and xml file"""
location_videofile = "F:\\CDAP-PRESENTLY\\21_22-j-02\\Presently\\presently\\media\\video\\22\\testvideo.mp4"
cascPath = "F:\\CDAP-PRESENTLY\\21_22-j-02\\Presently\\presently\\users\\models\\abc.xml"
"""Get labels to each emotion"""
def _get_labels():
return {
0: "angry",
......@@ -38,10 +19,7 @@ def _get_labels():
6: "neutral",
}
"""Build a square (around the face)"""
def tosquare(bbox):
"""Convert bounding box to square by elongating shorter side."""
x, y, w, h = bbox
if h > w:
diff = h - w
......@@ -56,15 +34,11 @@ def tosquare(bbox):
return (x, y, w, h)
"""Builded square around the face"""
def __apply_offsets(face_coordinates):
x, y, width, height = face_coordinates
x_off, y_off = (10, 10)
return (x - x_off, x + width + x_off, y - y_off, y + height + y_off)
"""To correct numbers"""
def __preprocess_input(x, v2=False):
x = x.astype("float32")
x = x / 255.0
......@@ -73,8 +47,6 @@ def __preprocess_input(x, v2=False):
x = x * 2.0
return x
"""Add padding to the image"""
def pad(image):
PADDING = 40
row, col = image.shape[:2]
......@@ -106,7 +78,6 @@ def detect_emotions(location_videofile, NumberofFrames):
success,image = vidcap.read()
frame_count = vidcap.get(cv2.CAP_PROP_FRAME_COUNT)
print("Frame Count: ", frame_count)
count = 0
faceCascade = cv2.CascadeClassifier(cascPath)
......@@ -116,7 +87,7 @@ def detect_emotions(location_videofile, NumberofFrames):
if success:
if frame_count > NumberofFrames+1:
count += frame_count/(NumberofFrames+1) # i.e. at 30 fps, this advances one second
count += frame_count/(NumberofFrames+1)
else:
count += 1
vidcap.set(cv2.CAP_PROP_POS_FRAMES, count)
......@@ -135,7 +106,6 @@ def detect_emotions(location_videofile, NumberofFrames):
face_coordinates = tosquare(face_coordinates)
x1, x2, y1, y2 = __apply_offsets(face_coordinates)
# adjust for padding
x1 += PADDING
x2 += PADDING
y1 += PADDING
......@@ -154,10 +124,8 @@ def detect_emotions(location_videofile, NumberofFrames):
try:
gray_face = cv2.resize(gray_face, model.input_shape[1:3])
except Exception as e:
#print("Cannot resize")
continue
# Local Keras model
gray_face = __preprocess_input(gray_face, True)
gray_face = np.expand_dims(np.expand_dims(gray_face, 0), -1)
......@@ -170,9 +138,6 @@ def detect_emotions(location_videofile, NumberofFrames):
emotions.append(
dict(box=face_coordinates, emotions=labelled_emotions)
)
#print("Prediction : ", emotions[0]["emotions"])
#plt.imshow(gray_img, interpolation='nearest')
#plt.show()
top_emotions = [max(e["emotions"], key=lambda key: e["emotions"][key]) for e in emotions]
if len(top_emotions):
for top_emotion in emotions[0]["emotions"]:
......@@ -190,4 +155,3 @@ def detect_emotions(location_videofile, NumberofFrames):
return max(arry, key=arry.get), arry
emo, arr1 = detect_emotions(location_videofile, 300)
# print(emo, arr1)
\ No newline at end of file
Presently/presently/users/myprosody.py
View file @ cc7f90b1
......@@ -25,8 +25,8 @@ def run_praat_file(m, p):
try:
objects= run_file(sourcerun, -20, 2, 0.3, "yes",sound,path, 80, 400, 0.01, capture_output=True)
print (objects[0]) # This will print the info from the sound object, and objects[0] is a parselmouth.Sound object
z1=str( objects[1]) # This will print the info from the textgrid object, and objects[1] is a parselmouth.Data object with a TextGrid inside
print (objects[0])
z1=str( objects[1])
z2=z1.strip().split()
return z2
except:
......@@ -39,10 +39,9 @@ def myspsyl(m,p):
Detect and count number of syllables
"""
z2 = run_praat_file(m, p)
z3=int(z2[0]) # will be the integer number 10
z4=float(z2[3]) # will be the floating point number 8.3
print ("number_ of_syllables=",z3)
return z3
z3=int(z2[0])
z4=float(z2[3])
return ("Number of syllables = ",z3)
def mysppaus(m,p):
"""
......@@ -51,8 +50,7 @@ def mysppaus(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[1]) # will be the integer number 10
z4=float(z2[3]) # will be the floating point number 8.3
print ("number_of_pauses=",z3)
return z3
return ("Number of pauses = ",z3)
def myspsr(m,p):
"""
......@@ -61,8 +59,7 @@ def myspsr(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[2]) # will be the integer number 10
z4=float(z2[3]) # will be the floating point number 8.3
print ("rate_of_speech=",z3,"# syllables/sec original duration")
return z3
return ("Rate of speech = ",z3," # syllables/sec original duration")
def myspatc(m,p):
"""
......@@ -71,8 +68,7 @@ def myspatc(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[3]) # will be the integer number 10
z4=float(z2[3]) # will be the floating point number 8.3
print ("articulation_rate=",z3,"# syllables/sec speaking duration")
return z3
return ("Articulation Rate =",z3," # syllables/sec speaking duration")
def myspst(m,p):
"""
......@@ -81,8 +77,7 @@ def myspst(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[3]) # will be the integer number 10
z4=float(z2[4]) # will be the floating point number 8.3
print ("speaking_duration=",z4,"# sec only speaking duration without pauses")
return z4
return ("Speaking duration = ",z4," # sec only speaking duration without pauses")
def myspod(m,p):
"""
......@@ -91,8 +86,7 @@ def myspod(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[3]) # will be the integer number 10
z4=float(z2[5]) # will be the floating point number 8.3
print ("original_duration=",z4,"# sec total speaking duration with pauses")
return z4
return ("Original duration = ",z4," # sec total speaking duration with pauses")
def myspbala(m,p):
"""
......@@ -101,8 +95,7 @@ def myspbala(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[3]) # will be the integer number 10
z4=float(z2[6]) # will be the floating point number 8.3
print ("balance=",z4,"# ratio (speaking duration)/(original duration)")
return z4
return ("Balance = ",z4," # ratio (speaking duration)/(original duration)")
def myspf0mean(m,p):
"""
......@@ -111,8 +104,7 @@ def myspf0mean(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[3]) # will be the integer number 10
z4=float(z2[7]) # will be the floating point number 8.3
print ("f0_mean=",z4,"# Hz global mean of fundamental frequency distribution")
return z4
return ("f0 mean = ",z4," # Hz global mean of fundamental frequency distribution")
def myspf0sd(m,p):
"""
......@@ -121,8 +113,7 @@ def myspf0sd(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[3]) # will be the integer number 10
z4=float(z2[8]) # will be the floating point number 8.3
print ("f0_SD=",z4,"# Hz global standard deviation of fundamental frequency distribution")
return z4
return ("f0 SD = ",z4," # Hz global standard deviation of fundamental frequency distribution")
def myspf0med(m,p):
"""
......@@ -131,8 +122,7 @@ def myspf0med(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[3]) # will be the integer number 10
z4=float(z2[9]) # will be the floating point number 8.3
print ("f0_MD=",z4,"# Hz global median of fundamental frequency distribution")
return z4
return ("f0 MD = ",z4," # Hz global median of fundamental frequency distribution")
def myspf0min(m,p):
"""
......@@ -141,8 +131,7 @@ def myspf0min(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[10]) # will be the integer number 10
z4=float(z2[10]) # will be the floating point number 8.3
print ("f0_min=",z3,"# Hz global minimum of fundamental frequency distribution")
return z3
return ("f0 min = ",z3," # Hz global minimum of fundamental frequency distribution")
def myspf0max(m,p):
"""
......@@ -151,8 +140,7 @@ def myspf0max(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[11]) # will be the integer number 10
z4=float(z2[11]) # will be the floating point number 8.3
print ("f0_max=",z3,"# Hz global maximum of fundamental frequency distribution")
return z3
return ("f0 max = ",z3," # Hz global maximum of fundamental frequency distribution")
def myspf0q25(m,p):
"""
......@@ -161,8 +149,7 @@ def myspf0q25(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[12]) # will be the integer number 10
z4=float(z2[11]) # will be the floating point number 8.3
print ("f0_quan25=",z3,"# Hz global 25th quantile of fundamental frequency distribution")
return z3
return ("f0 quan25 = ",z3," # Hz global 25th quantile of fundamental frequency distribution")
def myspf0q75(m,p):
"""
......@@ -171,22 +158,7 @@ def myspf0q75(m,p):
z2 = run_praat_file(m, p)
z3=int(z2[13]) # will be the integer number 10
z4=float(z2[11]) # will be the floating point number 8.3
print ("f0_quan75=",z3,"# Hz global 75th quantile of fundamental frequency distribution")
return z3
def mysptotal(m,p):
"""
Overview
"""
z2 = run_praat_file(m, p)
z3=np.array(z2)
z4=np.array(z3)[np.newaxis]
z5=z4.T
dataset=pd.DataFrame({"number_ of_syllables":z5[0,:],"number_of_pauses":z5[1,:],"rate_of_speech":z5[2,:],"articulation_rate":z5[3,:],"speaking_duration":z5[4,:],
"original_duration":z5[5,:],"balance":z5[6,:],"f0_mean":z5[7,:],"f0_std":z5[8,:],"f0_median":z5[9,:],"f0_min":z5[10,:],"f0_max":z5[11,:],
"f0_quantile25":z5[12,:],"f0_quan75":z5[13,:]})
print (dataset.T)
return dataset.T
return ("f0 quan75 = ",z3," # Hz global 75th quantile of fundamental frequency distribution")
def mysppron(m,p):
"""
......@@ -206,9 +178,9 @@ def mysppron(m,p):
db= binom.rvs(n=10,p=z4,size=10000)
a=np.array(db)
b=np.mean(a)*100/10
print ("Pronunciation_posteriori_probability_score_percentage= :%.2f" % (b))
return ("Pronunciation posteriori probability score percentage = : %.2f" % (b))
except:
print ("Try again the sound of the audio was not clear")
return ("Try again the sound of the audio was not clear")
return
def myspgend(m,p):
......@@ -266,21 +238,21 @@ def myspgend(m,p):
else:
mmm=0.35
if z4>97 and z4<=114:
print("a Male, mood of speech: Showing no emotion, normal, p-value/sample size= :%.2f" % (mmm), (nnn))
return ("A Male, Mood of speech: Showing no emotion | normal, p-value/sample size :%.2f" % (mmm), (nnn))
elif z4>114 and z4<=135:
print("a Male, mood of speech: Reading, p-value/sample size= :%.2f" % (mmm), (nnn))
return ("A Male, Mood of speech: Reading, p-value/sample size :%.2f" % (mmm), (nnn))
elif z4>135 and z4<=163:
print("a Male, mood of speech: speaking passionately, p-value/sample size= :%.2f" % (mmm), (nnn))
return ("A Male, Mood of speech: speaking passionately, p-value/sample size :%.2f" % (mmm), (nnn))
elif z4>163 and z4<=197:
print("a female, mood of speech: Showing no emotion, normal, p-value/sample size= :%.2f" % (mmm), (nnn))
return ("A Female, Mood of speech: Showing no emotion | normal, p-value/sample size :%.2f" % (mmm), (nnn))
elif z4>197 and z4<=226:
print("a female, mood of speech: Reading, p-value/sample size= :%.2f" % (mmm), (nnn))
return ("A Female, Mood of speech: Reading, p-value/sample size :%.2f" % (mmm), (nnn))
elif z4>226 and z4<=245:
print("a female, mood of speech: speaking passionately, p-value/sample size= :%.2f" % (mmm), (nnn))
return ("A Female, Mood of speech: speaking passionately, p-value/sample size :%.2f" % (mmm), (nnn))
else:
print("Voice not recognized")
return ("Voice not recognized")
except:
print ("Try again the sound of the audio was not clear")
return ("Try again the sound of the audio was not clear")
def myprosody(m,p):
"""
......@@ -299,11 +271,10 @@ def myprosody(m,p):
result_array = np.empty((0, 27))
try:
objects= run_file(sourcerun, -20, 2, 0.3, "yes",sound,path, 80, 400, 0.01, capture_output=True)
z1=( objects[1]) # This will print the info from the textgrid object, and objects[1] is a parselmouth.Data object with a TextGrid inside
z1=( objects[1])
z3=z1.strip().split()
z2=np.array([z3])
result_array=np.append(result_array,[z3], axis=0)
#print(z3)
np.savetxt(outo,result_array, fmt='%s',delimiter=',')
#Data and features analysis
df = pd.read_csv(outo,
......@@ -334,15 +305,15 @@ def myprosody(m,p):
if he==0:
he=25
dfout = "%s:\t %f (%s)" % (nsns[i],he,"% percentile ")
print(dfout)
return(dfout)
elif he>=25 and he<=75:
dfout = "%s:\t %f (%s)" % (nsns[i],he,"% percentile ")
print(dfout)
return(dfout)
else:
dfout = "%s:\t (%s)" % (nsns[i],":Out of Range")
print(dfout)
return(dfout)
except:
print ("Try again the sound of the audio was not clear")
return ("Try again the sound of the audio was not clear")
def mysplev(m,p):
import sys
......
Presently/presently/users/prosodydetectionaudio.py deleted 100644 → 0
View file @ d84ae894
import myprosody as mysp
import pickle
p="happy"
c="F:\\CDAP-PRESENTLY\\21_22-j-02\\Presently\\presently\\users\\myprosody"
mysp.myspsyl(p,c)
mysp.mysppaus(p,c)
mysp.myspsr(p,c)
mysp.myspatc(p,c)
mysp.myspst(p,c)
mysp.myspod(p,c)
mysp.myspbala(p,c)
mysp.myspf0mean(p,c)
mysp.myspf0sd(p,c)
mysp.myspf0med(p,c)
mysp.myspf0min(p,c)
mysp.myspf0max(p,c)
mysp.myspf0q25(p,c)
mysp.myspf0q75(p,c)
mysp.mysptotal(p,c)
mysp.myspgend(p,c)
mysp.mysppron(p,c)
mysp.myprosody(p,c)
mysp.mysplev(p,c)
Presently/presently/users/templates/users/base.html
View file @ cc7f90b1
......@@ -7,8 +7,7 @@
<link rel="stylesheet" href="{% static 'users/css/main.css' %}" type="text/css">
<link rel="stylesheet" href="{% static 'users/css/plugin.css' %}" type="text/css">
<link rel="stylesheet" href="{% static 'users/css/style.css' %}" type="text/css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css">
<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-eOJMYsd53ii+scO/bJGFsiCZc+5NDVN2yr8+0RDqr0Ql0h+rP48ckxlpbzKgwra6" crossorigin="anonymous">
<link rel="preconnect" href="https://fonts.gstatic.com">
<link href="https://fonts.googleapis.com/css2?family=Montserrat:wght@500&family=Open+Sans:wght@800&display=swap" rel="stylesheet">
......
Presently/presently/users/templates/users/test.html
View file @ cc7f90b1
......@@ -5,7 +5,7 @@
{% block content %}
<h2> {{ var1 }} {{ var2 }}</h2>
<!-- {% for key, value in predictions.items %}
<!-- {% for key, value in var2.items %}
<h2>{{ forloop.counter }}. {{ key }} : {{ value }}</h2>
{% endfor %} -->
......
Presently/presently/users/views.py
View file @ cc7f90b1
......@@ -10,11 +10,16 @@ from .models import Video
from django.template import Template, Context
import datetime
from . import emotiondetectionvideo
from . import emotiondetectionaudio
# from . import emotiondetectionaudio
import myprosody as mysp
import pickle
from . import myprosody
def test(request):
var1= emotiondetectionaudio.emo_list
var2= emotiondetectionaudio.total_predictions_np
p="happy"
c="F:\\CDAP-PRESENTLY\\21_22-j-02\\Presently\\presently\\users\\myprosody"
var2= myprosody.myspgend(p,c)
var1= myprosody.myprosody(p,c)
context= {
'var1': var1,
'var2': var2
......@@ -60,7 +65,46 @@ def emotionvideo(request):
return render(request, 'users/emotionvideo.html',context)
def emotionaudioprosody(request):
return render(request, 'users/prosody.html')
p="happy"
c="F:\\CDAP-PRESENTLY\\21_22-j-02\\Presently\\presently\\users\\myprosody"
myspsyl= myprosody.myspsyl(p,c)
mysppaus= myprosody.mysppaus(p,c)
myspsr= myprosody.myspsr(p,c)
myspatc= myprosody.myspatc(p,c)
myspst= myprosody.myspst(p,c)
myspod= myprosody.myspod(p,c)
myspbala= myprosody.myspbala(p,c)
myspf0mean= myprosody.myspf0mean(p,c)
myspf0sd= myprosody.myspf0sd(p,c)
myspf0med= myprosody.myspf0med(p,c)
myspf0min= myprosody.myspf0min(p,c)
myspf0max= myprosody.myspf0max(p,c)
myspf0q25= myprosody.myspf0q25(p,c)
myspf0q75= myprosody.myspf0q75(p,c)
myspgend= myprosody.myspgend(p,c)
mysppron= myprosody.mysppron(p,c)
prosody= myprosody.myprosody(p,c)
context= {
'myspsyl': myspsyl,
'mysppaus': mysppaus,
'myspsr': myspsr,
'myspatc': myspatc,
'myspst': myspst,
'myspod': myspod,
'myspbala': myspbala,
'myspf0mean': myspf0mean,
'myspf0sd': myspf0sd,
'myspf0med': myspf0med,
'myspf0min': myspf0min,
'myspf0max': myspf0max,
'myspf0q25': myspf0q25,
'myspf0q75': myspf0q75,
'myspgend': myspgend,
'mysppron': mysppron,
'prosody': prosody
}
return render(request, 'users/prosody.html',context)
def overallfeedback(request):
return render(request, 'users/overallfeedback.html')
......
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