Merge branch 'monitoring_student_behavior_IT17138000' into 'QA_RELEASE'

Monitoring student behavior it17138000

See merge request !48

FirstApp/MongoModels.py

@@ -79,6 +79,10 @@ class DailyTimeTable(models.Model):
     subject = models.ForeignKey(Subject, on_delete=models.CASCADE)
     lecturer = models.ForeignKey(Lecturer, on_delete=models.CASCADE)
     location = models.CharField(max_length=10)
+    # new temp fields
+    lecturer_name = models.CharField(max_length=20, default='')
+    subject_name = models.CharField(max_length=20, default='')
+    no_of_students = models.IntegerField(default=4)
 
     def __str__(self):
         return self.location

FirstApp/api.py

@@ -11,11 +11,16 @@ each method will return an HttpResponse that allows its data to be rendered into
 arbitrary media types.
 
 """
+import json
 from random import Random
 
+from apscheduler.jobstores.mongodb import MongoDBJobStore
+
 from MonitorLecturerApp.models import LectureRecordedVideo, LecturerVideoMetaData
 from MonitorLecturerApp.serializers import LectureRecordedVideoSerializer, LecturerVideoMetaDataSerializer
 from rest_framework.views import *
+
+from integrated_slpes.wsgi import application
 from .logic import activity_recognition as ar
 from . import emotion_detector as ed, automation_process as ap
 from .logic import id_generator as ig
@@ -23,10 +28,15 @@ from .logic import pdf_file_generator as pdf
 from .logic import head_gaze_estimation as hge
 from .logic import video_extraction as ve
 from . logic import student_behavior_process as sbp
+from .logic.scheduler_tasks import task_scheduler
 from .serializers import *
 from braces.views import CsrfExemptMixin
 
+from django.core.handlers.wsgi import WSGIRequest
+from django.http.request import HttpRequest
+
 import datetime
+import os
 
 
 class LectureViewSet(APIView):
@@ -1539,19 +1549,36 @@ class CheckStudentBehaviorAvailability(APIView):
 
     def get(self, request):
         video_name = request.query_params.get('video_name')
-        #
-        # isActivityExist = LectureActivityFrameGroupings.objects.filter(
-        #     lecture_activity_id__lecture_video_id__video_name=video_name).exists()
-        #
-        # isEmotionExist = LectureEmotionFrameGroupings.objects.filter(
-        #     lecture_emotion_id__lecture_video_id__video_name=video_name).exists()
-        #
-        # isGazeExist = LectureGazeFrameGroupings.objects.filter(
-        #     lecture_gaze_id__lecture_video_id__video_name=video_name).exists()
+        print('video name: ', video_name)
+
+        # retrieve the 'MongoDbJobStore' instance
+        jobs = MongoDBJobStore().get_all_jobs()
+
+        print('jobs: ', jobs)
+
+        # initialize the variables
+        isActivityExist = False
+        isEmotionExist = False
+        isGazeExist = False
+
+        # if there are scheduled jobs
+        if len(jobs) > 0:
+
+            # retrieve the activity frame groupings
+            isActivityExist = LectureActivityFrameGroupings.objects.filter(lecture_activity_id__lecture_video_id__video_name=video_name).exists()
+            # retrieve the emotion frame groupings
+            isEmotionExist = LectureEmotionFrameGroupings.objects.filter(lecture_emotion_id__lecture_video_id__video_name=video_name).exists()
+            # retrieve the gaze frame groupings
+            isGazeExist = LectureGazeFrameGroupings.objects.filter(lecture_gaze_id__lecture_video_id__video_name=video_name).exists()
 
-        isActivityExist = bool(Random().randint(0,2))
-        isEmotionExist = bool(Random().randint(0,2))
-        isGazeExist = bool(Random().randint(0,2))
+        else:
+
+            isActivityExist = True
+            isEmotionExist = True
+            isGazeExist = True
+            # isActivityExist = bool(Random().randint(0,2))
+            # isEmotionExist = bool(Random().randint(0,2))
+            # isGazeExist = bool(Random().randint(0,2))
 
         return Response({
             "isActivityExist": isActivityExist,
@@ -1657,13 +1684,28 @@ class AutomationProcess(APIView):
         })
 
     def post(self, request):
-        lecturer = request.data['lecturer']
-        subject = request.data['subject']
-        subject_code = request.data['subject_code']
-        video_length = request.data['video_length']
 
-        processed = ap.automation_process(lecturer=lecturer, subject=subject, subject_code=subject_code, video_length=video_length)
+        processed = False
 
-        return Response({
-            "is_processed": processed
-        })
\ No newline at end of file
+        try :
+
+            lecturer = request.data['lecturer']
+            subject = request.data['subject']
+            subject_code = request.data['subject_code']
+            video_length = request.data['video_length']
+
+            # processed = ap.automation_process(lecturer=lecturer, subject=subject, subject_code=subject_code, video_length=video_length)
+            # run the scheduler
+            scheduler = task_scheduler(lecturer=lecturer, subject=subject, subject_code=subject_code, video_length=video_length)
+
+            processed = True
+
+            return Response({
+                "is_processed": processed,
+            })
+
+        except Exception as exc:
+            print('Exception: ', exc)
+            return Response({
+                "is_processed": processed,
+            })
\ No newline at end of file

FirstApp/automation_process.py

 import requests
 import json
 
+
+from .MongoModels import LectureVideo
 from . logic import batch_process as bp
 from MonitorLecturerApp.logic import lecturer_batch_process as lbp
 import datetime
 
+
 # this method will save the lecture video
 
 #
@@ -43,6 +46,11 @@ import datetime
 #     return response[0]
 
 # this method will handle the batch processing and video/audio saving pf the system
+from .logic.batch_process import student_behavior_batch_process
+from .serializers import LectureVideoSerializer
+
+
+# @background(schedule=5)
 def automation_process(lecturer, subject, subject_code, video_length="00:20:00"):
 
     current_date = datetime.datetime.now().date()
@@ -55,6 +63,7 @@ def automation_process(lecturer, subject, subject_code, video_length="00:20:00")
     lecturer_video_name = str(current_date) + "_{}_lecturer_video.mp4".format(subject_code)
     lecturer_audio_name = str(current_date) + "_{}_lecturer_audio.wav".format(subject_code)
 
+
     # this variable will be passed in the individual batch process
     student_video_id = 0
 
@@ -80,9 +89,11 @@ def automation_process(lecturer, subject, subject_code, video_length="00:20:00")
     # create the lecturer audio
     lecturer_audio_content = {}
 
+
     # save the student video
     student_video_response = bp.save_student_lecture_video(student_video_content)
     # student_video_response = save_student_lecture_video(student_video_content)
+    print('student video response: ', student_video_response)
     student_video_id = student_video_response['id']
 
     # save the lecturer video
@@ -93,6 +104,13 @@ def automation_process(lecturer, subject, subject_code, video_length="00:20:00")
     # save the lecturer audio
 
 
+    for i in range(100):
+        print('outer loop: ', i)
+
+        for j in range(10000):
+            print('inner loop: ', j)
+
+
     # start the batch processing for lecture summarization component
     # lecture_summary_batch_process = lecture_summarization_batch_process(audio_name)
     lecture_summary_batch_process = True
@@ -117,6 +135,7 @@ def automation_process(lecturer, subject, subject_code, video_length="00:20:00")
     # return the status
     return is_all_processed
 
+
 # test the above method using 'main' method
 # if __name__ == '__main__':
 #

FirstApp/emotion_detector.py

@@ -523,11 +523,11 @@ def emotion_frame_groupings(video_name, frame_landmarks, frame_group_dict):
         group_detection_count = frame_group_details['detection_count']
 
         # calculate the frame group emotion percentages
-        frame_group_happy_perct = float(frame_group_happy_count / group_detection_count) * 100
-        frame_group_sad_perct = float(frame_group_sad_count / group_detection_count) * 100
-        frame_group_angry_perct = float(frame_group_angry_count / group_detection_count) * 100
-        frame_group_surprise_perct = float(frame_group_surprise_count / group_detection_count) * 100
-        frame_group_neutral_perct = float(frame_group_neutral_count / group_detection_count) * 100
+        frame_group_happy_perct = float(frame_group_happy_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_sad_perct = float(frame_group_sad_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_angry_perct = float(frame_group_angry_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_surprise_perct = float(frame_group_surprise_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_neutral_perct = float(frame_group_neutral_count / group_detection_count) * 100 if group_detection_count > 0 else 0
 
         # assign the values to the same dictionary
         frame_group_dict[key]['happy_perct'] = round(frame_group_happy_perct, 1)

FirstApp/logic/activity_recognition.py

@@ -615,9 +615,9 @@ def activity_frame_groupings(video_name, frame_landmarks, frame_group_dict):
         group_detection_count = frame_group_details['detection_count']
 
 
-        frame_group_phone_perct = float(frame_group_phone_count / group_detection_count) * 100
-        frame_group_listen_perct = float(frame_group_listen_count / group_detection_count) * 100
-        frame_group_note_perct = float(frame_group_note_count / group_detection_count) * 100
+        frame_group_phone_perct = float(frame_group_phone_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_listen_perct = float(frame_group_listen_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_note_perct = float(frame_group_note_count / group_detection_count) * 100 if group_detection_count > 0 else 0
 
         # assign the values to the same dictionary
         frame_group_dict[key]['phone_perct'] = round(frame_group_phone_perct, 1)

FirstApp/logic/batch_process.py

 import requests
 import json
+from background_task import background
 
 
 def student_behavior_batch_process(video_id, video_name):
@@ -30,6 +31,7 @@ def student_behavior_batch_process(video_id, video_name):
 
 
 # this method will save the student lecture video
+# @background(schedule=5)
 def save_student_lecture_video(student_video):
 
     data_dumps = json.dumps(student_video)

FirstApp/logic/head_gaze_estimation.py

@@ -854,11 +854,11 @@ def gaze_estimation_frame_groupings(video_name, frame_landmarks, frame_group_dic
 
 
 
-        frame_group_upright_perct = float(frame_group_upright_count / group_detection_count) * 100
-        frame_group_upleft_perct = float(frame_group_upleft_count / group_detection_count) * 100
-        frame_group_downright_perct = float(frame_group_downright_count / group_detection_count) * 100
-        frame_group_downleft_perct = float(frame_group_downleft_count / group_detection_count) * 100
-        frame_group_front_perct = float(frame_group_front_count / group_detection_count) * 100
+        frame_group_upright_perct = float(frame_group_upright_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_upleft_perct = float(frame_group_upleft_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_downright_perct = float(frame_group_downright_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_downleft_perct = float(frame_group_downleft_count / group_detection_count) * 100 if group_detection_count > 0 else 0
+        frame_group_front_perct = float(frame_group_front_count / group_detection_count) * 100 if group_detection_count > 0 else 0
 
         # assign the values to the same dictionary
         frame_group_dict[key]['upright_perct'] = round(frame_group_upright_perct, 1)

FirstApp/logic/scheduler_tasks.py

+from apscheduler.schedulers.background import BackgroundScheduler
+from apscheduler.jobstores.mongodb import MongoDBJobStore
+import datetime as d
+from datetime import datetime
+
+# this method will schedule the automation process task
+from FirstApp.automation_process import automation_process
+
+
+def task_scheduler(lecturer, subject, subject_code, video_length):
+
+    jobstores = {
+        'mongo': MongoDBJobStore(),
+    }
+
+    sched = BackgroundScheduler(jobstores=jobstores)
+    after_20s = datetime.now() + d.timedelta(seconds=30)
+    sched.add_job(automation_process, args=[lecturer, subject, subject_code, video_length], trigger='date', run_date=after_20s, id='Automation_1')
+    sched.start()
+
+    job = sched.get_job(job_id='Automation_1')
+    MongoDBJobStore().add_job(job=job)
+
+
+    return sched
\ No newline at end of file

FirstApp/templates/FirstApp/video_results.html

@@ -224,6 +224,12 @@
                 let video_id = $(this).attr("data-video-id");
                 let video_name = $(this).attr("data-video-name");
 
+                //display the 'processing' message
+                $('#processing').attr('hidden', false);
+
+                //hide the button
+                $(this).hide();
+
                 //display the activity loader
                 $('#activity_loader').attr("hidden", false);
 
@@ -278,7 +284,7 @@
                     //sending the get request to process the lecture gaze estimations
                     fetch('http://127.0.0.1:8000/process-lecture-gaze-estimation/?lecture_video_name=' + global_video_name + '&lecture_video_id=' + global_lecture_video_id)
                         .then((res) => res.json())
-                        .then((out) => handleGazeResponse(out.response, e))
+                        .then((out) => handleGazeResponse(out.response))
                         .catch((error) => alert('error: ' + error));
                 }
             }
@@ -297,20 +303,22 @@
                 }
             }
 
-            //this is a test function (delete later)
+
             /*
-            let interval = setInterval(() => {
+            //this is a test function (delete later)
+            //get the due lecture video name
+            var due_lecture_video_name = "{{ due_lecture_video_name }}";
 
+            let interval = setInterval(() => {
 
-            {#let url = 'http://127.0.0.1:8000/get-random_number';#}
-                let url = 'http://127.0.0.1:8000/check-availability';
+                let url = 'http://127.0.0.1:8000/check-availability/?video_name=' + due_lecture_video_name;
 
                 fetch(url)
                     .then((res) => res.json())
                     .then((out) => displayProcess(out))
                     .catch((err) => alert('error: ' + err))
 
-            }, 10000);
+            }, 5000);
 
 
             //this function will handle the displaying loaders and status in the workflow
@@ -356,6 +364,7 @@
 
 
             }
+
             */
 
 
@@ -440,6 +449,7 @@
                                                     <td class="font-weight-bolder">{{ lecture.start_time }}</td>
                                                     <td class="font-weight-bolder">{{ lecture.end_time }}</td>
                                                     <td>
+                                                        <span class="font-italic text-success" id="processing" hidden>Processing</span>
                                                         <button type="button" class="btn btn-success batch_process"
                                                                 data-video-id="{{ lecture.video_id }}"
                                                                 data-video-name="{{ lecture.video_name }}"

FirstApp/views.py

@@ -29,11 +29,18 @@ from django.contrib.auth import (
     logout,
 )
 from django.contrib.auth.decorators import login_required
+
 from . serializers import *
 from . forms import *
 import os
+import datetime as d
 from datetime import datetime
 
+from apscheduler.schedulers.background import BackgroundScheduler
+from apscheduler.triggers.date import DateTrigger
+from apscheduler.jobstores.mongodb import MongoDBJobStore
+
+
 
 # Create your views here.
 
@@ -53,6 +60,11 @@ def hello(request):
 
         print('user_type: ', user_type)
 
+        print('request type: ', type(request))
+
+        # test the scheduler
+        # test_scheduler()
+
 
         # retrieve the lecturer's timetable slots
         lecturer_timetable = FacultyTimetable.objects.filter()
@@ -122,6 +134,7 @@ def hello(request):
         return redirect('/401')
 
     except Exception as exc:
+        print('exception: ', exc)
         return redirect('/500')
 
 # this method will handle 404 error page
@@ -232,8 +245,9 @@ def video_result(request):
                 for item in to_do_lecture_list:
                     isDate = item['date'] == str(day_timetable['date'])
 
-                    print('item date: ', item['date'])
-                    print('timetable date: ', str(day_timetable['date']))
+                    # print('item date: ', item['date'])
+                    # print('timetable date: ', str(day_timetable['date']))
+
                     # isLecturer = item['lecturer'] ==
                     # check for the particular lecture on the day
                     if isDate:
@@ -246,6 +260,12 @@ def video_result(request):
                             isLecturer = item['lecturer'] == slot['lecturer']['id']
                             isSubject = item['subject'] == slot['subject']['id']
 
+                            print('item lecturer: ', item['lecturer'])
+                            print('timetable lecturer: ', slot['lecturer']['id'])
+
+                            print('item subject: ', item['subject'])
+                            print('timetable subject: ', slot['subject']['id'])
+
                             if isLecturer & isSubject:
                                 obj = {}
                                 obj['date'] = item['date']
@@ -265,13 +285,17 @@ def video_result(request):
 
     # handling the general exceptions
     except Exception as exc:
-        print('what is wrong?: ', exc)
+        print('Exception: ', exc)
         return redirect('/500')
 
     print('due lectures: ', due_lecture_list)
 
+    due_lecture_video_name = due_lecture_list[0]['video_name'] if len(due_lecture_list) > 0 else "Test.mp4"
+    # due_lecture_video_name = "Test.mp4"
+    print('due lecture video name: ', due_lecture_video_name)
+
     return render(request, "FirstApp/video_results.html",
-                  {"lecturer": lecturer, "due_lectures": due_lecture_list})
+                  {"lecturer": lecturer, "due_lectures": due_lecture_list, "due_lecture_video_name": due_lecture_video_name})
 
 
 # view for emotion page
@@ -377,6 +401,7 @@ def activity(request):
 
     # handling the general exception
     except Exception as exc:
+        print('exception: ', exc)
         return redirect('/500')
 
     return render(request, "FirstApp/activity.html", {"lecturer_subjects": lecturer_subjects, "subjects": subject_list, "lecturer": lecturer})

integrated_slpes/settings.py

@@ -43,7 +43,7 @@ INSTALLED_APPS = [
     'django.contrib.staticfiles',
     'bootstrap4',
     'rest_framework',
-    'os'
+    'os',
 ]
 
 MIDDLEWARE = [

integrated_slpes/urls.py

@@ -25,5 +25,5 @@ urlpatterns = [
     path('lecturer/', include('MonitorLecturerApp.urls')),
     # path('lecturer/', include('MonitorLecturerApp.urls')),
     path('summary/', include('LectureSummarizingApp.urls')),
-    path('record/', include('LectureSummarizingApp.urls'))
+    path('record/', include('LectureSummarizingApp.urls')),
 ]