Committing some implementations in saving the lecture activity frame groupings into the database .

FirstApp/MongoModels.py

@@ -124,28 +124,35 @@ class LectureActivity(models.Model):
         return self.lecture_activity_id
 
 
+# this abstract class will define the lecture activity frame group percentages
+class LectureActivityFrameGroupPercentages(models.Model):
+    phone_perct = models.DecimalField(default=0.0, max_digits=3, decimal_places=1)
+    listen_perct = models.DecimalField(default=0.0, max_digits=3, decimal_places=1)
+    note_perct = models.DecimalField(default=0.0, max_digits=3, decimal_places=1)
+
+    class Meta:
+        abstract = True
+
+
 # this abstract class will define the details for an activity frame group
 class LectureActivityFrameGroupDetails(models.Model):
     frame_group = models.CharField(max_length=10)
-    phone_perct = models.DecimalField(default=0.0, max_digits=3, decimal_places=1)
-    listening_perct = models.DecimalField(default=0.0, max_digits=3, decimal_places=1)
-    writing_perct = models.DecimalField(default=0.0, max_digits=3, decimal_places=1)
-
-    def __str__(self):
-        return self.frame_group
+    frame_group_percentages = models.EmbeddedField(
+       model_container=LectureActivityFrameGroupPercentages
+    )
 
-    class meta:
+    class Meta:
         abstract = True
 
 
 # this class will contain the activity frame groupings
 class LectureActivityFrameGroupings(models.Model):
-    name = models.CharField(max_length=15, default="")
+    lecture_activity_frame_groupings_id = models.CharField(max_length=15, default="")
     lecture_activity_id = models.ForeignKey(LectureActivity, on_delete=models.CASCADE)
-    frame_group_details = models.ArrayField(LectureActivityFrameGroupDetails)
+    frame_group_details = models.ArrayField(model_container=LectureActivityFrameGroupDetails)
 
     def __str__(self):
-        return self.name
+        return self.lecture_activity_frame_groupings_id
 
 
 # EMOTIONS section

FirstApp/api.py

@@ -784,11 +784,56 @@ class GetLectureActivitySummary(APIView):
 
     def get(self, request):
         video_name = request.query_params.get('video_name')
-        frame_landmarks, frame_group_dict = ve.getFrameLandmarks(video_name)
-        frame_group_percentages = ar.activity_frame_groupings(video_name, frame_landmarks, frame_group_dict)
 
-        return Response({
-            "frame_landmarks": frame_landmarks,
-            "frame_group_dict": frame_group_dict,
-            "frame_group_percentages": frame_group_percentages
-        })
+        # checking the existence of lecture activity frame grouping records in the db
+        lec_activity_frame_groupings = LectureActivityFrameGroupings.objects.filter(lecture_activity_id__lecture_video_id__video_name=video_name).exists()
+
+        if (lec_activity_frame_groupings):
+
\ No newline at end of file
+            return Response({
+                "frame_group_percentages": {}
+            })
+
+        else:
+            frame_landmarks, frame_group_dict = ve.getFrameLandmarks(video_name)
+            frame_group_percentages, activity_labels = ar.activity_frame_groupings(video_name, frame_landmarks, frame_group_dict)
+
+
+
+            # save the frame group details into db (temp method)
+
+            last_lec_activity_frame_grouping = LectureActivityFrameGroupings.objects.order_by('lecture_activity_frame_groupings_id').last()
+            new_lecture_activity_frame_grouping_id = "LAFG00001" if (last_lec_activity_frame_grouping is None) else \
+                ig.generate_new_id(last_lec_activity_frame_grouping.lecture_activity_frame_groupings_id)
+
+            # retrieve the lecture activity id
+            lec_activity = LectureActivity.objects.filter(lecture_video_id__video_name=video_name)
+            lec_activity_ser = LectureActivitySerializer(lec_activity, many=True)
+            lec_activity_id = lec_activity_ser.data[0]['id']
+
+            # create the frame group details
+            frame_group_details = []
+
+            for key in frame_group_percentages.keys():
+                obj = {}
+                obj['frame_group'] = key
+                obj['frame_group_percentages'] = frame_group_percentages[key]
+
+                frame_group_details.append(obj)
+
+
+            new_lec_activity_frame_groupings = LectureActivityFrameGroupings()
+            new_lec_activity_frame_groupings.lecture_activity_frame_groupings_id = new_lecture_activity_frame_grouping_id
+            new_lec_activity_frame_groupings.lecture_activity_id_id = lec_activity_id
+            new_lec_activity_frame_groupings.frame_group_details = frame_group_details
+
+            # save
+            new_lec_activity_frame_groupings.save()
+
+
+            return Response({
+                "frame_landmarks": frame_landmarks,
+                "frame_group_dict": frame_group_dict,
+                "frame_group_percentages": frame_group_percentages,
+                "activity_labels": activity_labels
+            })
\ No newline at end of file

FirstApp/logic/activity_recognition.py

@@ -656,6 +656,7 @@ def activity_frame_groupings(video_name, frame_landmarks, frame_group_dict):
         # assign the difference
         frame_group_diff[key] = diff if diff > 0 else 1
 
+
     # looping through the frames
     for frame in os.listdir(EXTRACTED_DIR):
         # getting the frame folder
@@ -665,6 +666,7 @@ def activity_frame_groupings(video_name, frame_landmarks, frame_group_dict):
         phone_count = 0
         note_count = 0
         listen_count = 0
+        detection_count = 0
 
         # looping through the detections in each frame
         for detections in os.listdir(FRAME_FOLDER):
@@ -698,6 +700,11 @@ def activity_frame_groupings(video_name, frame_landmarks, frame_group_dict):
                 elif label == class_labels[2]:
                     note_count += 1
 
+
+                # increment the detection count
+                detection_count += 1
+
+
                 # finding the time landmark that the current frame is in
                 for i in frame_landmarks:
                     index = frame_landmarks.index(i)
@@ -711,9 +718,13 @@ def activity_frame_groupings(video_name, frame_landmarks, frame_group_dict):
                         if (frame_count >= i) & (frame_count < next_value):
                             frame_name = "{}-{}".format(i, next_value)
 
+
                             frame_group_dict[frame_name]['phone_count'] += phone_count
                             frame_group_dict[frame_name]['listen_count'] += listen_count
                             frame_group_dict[frame_name]['note_count'] += note_count
+                            frame_group_dict[frame_name]['detection_count'] += detection_count
+
+
 
         # increment the frame count
         frame_count += 1
@@ -724,18 +735,36 @@ def activity_frame_groupings(video_name, frame_landmarks, frame_group_dict):
         frame_group_phone_count = frame_group_details['phone_count']
         frame_group_listen_count = frame_group_details['listen_count']
         frame_group_note_count = frame_group_details['note_count']
+        group_detection_count = frame_group_details['detection_count']
+
+        # print('frame group phone count: ', frame_group_phone_count)
+        # print('frame group listen count: ', frame_group_listen_count)
+        # print('frame group note count: ', frame_group_note_count)
+        # print('frame group detection count: ', group_detection_count)
 
         frame_diff = int(frame_group_diff[key])
 
-        frame_group_phone_perct = float(frame_group_phone_count / frame_diff) * 100
-        frame_group_listen_perct = float(frame_group_listen_count / frame_diff) * 100
-        frame_group_note_perct = float(frame_group_note_count / frame_diff) * 100
+        # print('frame difference: ', frame_diff)
+
+        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
 
         # assign the values to the same dictionary
-        frame_group_dict[key]['phone_perct'] = frame_group_phone_perct
-        frame_group_dict[key]['listen_perct'] = frame_group_listen_perct
-        frame_group_dict[key]['note_perct'] = frame_group_note_perct
+        frame_group_dict[key]['phone_perct'] = round(frame_group_phone_perct, 1)
+        frame_group_dict[key]['listen_perct'] = round(frame_group_listen_perct, 1)
+        frame_group_dict[key]['note_perct'] = round(frame_group_note_perct, 1)
+
+        # removing irrelevant items from the dictionary
+        frame_group_dict[key].pop('phone_count')
+        frame_group_dict[key].pop('listen_count')
+        frame_group_dict[key].pop('note_count')
+        frame_group_dict[key].pop('detection_count')
+
+    # print('frame group dict: ', frame_group_dict)
+    activity_labels = ['phone_perct', 'listen_perct', 'note_perct']
 
+    print('frame group percentages: ', frame_group_dict)
 
     # return the dictionary
-    return frame_group_dict
+    return frame_group_dict, activity_labels
\ No newline at end of file

FirstApp/logic/video_extraction.py

@@ -100,7 +100,8 @@ def getTimeLandmarks(video_name):
 
     initial_landmark = 0
 
-    time_landmarks = ['0:00:00']
+    # time_landmarks = ['0:00:00']
+    time_landmarks = []
     time_landmarks_values = [0]
 
     # loop through the threshold gap limit to define the time landmarks
@@ -142,6 +143,7 @@ def getFrameLandmarks(video_name):
 
     # define frame landmarks
     frame_landmarks = [0]
+    # frame_landmarks = []
 
     # loop through the threshold gap limit to define the time landmarks
     for i in range(THRESHOLD_GAP):
@@ -175,7 +177,7 @@ def getFrameLandmarks(video_name):
 
     # loop through the group names to create a dictionary
     for name in frame_group_list:
-        frame_group_dict[name] = {'phone_count': 0, 'listen_count': 0, 'note_count': 0}
+        frame_group_dict[name] = {'phone_count': 0, 'listen_count': 0, 'note_count': 0, 'detection_count': 0}
 
 
     return frame_landmarks, frame_group_dict
\ No newline at end of file

FirstApp/migrations/0009_lectureactivityframegroupdetails_lectureactivityframegroupings.py

-# Generated by Django 2.2.11 on 2020-10-07 12:29
-
-import FirstApp.MongoModels
-from django.db import migrations, models
-import django.db.models.deletion
-import djongo.models.fields
-
-
-class Migration(migrations.Migration):
-
-    dependencies = [
-        ('FirstApp', '0008_auto_20200825_1821'),
-    ]
-
-    operations = [
-        migrations.CreateModel(
-            name='LectureActivityFrameGroupDetails',
-            fields=[
-                ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
-                ('frame_group', models.CharField(max_length=10)),
-                ('phone_perct', models.DecimalField(decimal_places=1, default=0.0, max_digits=3)),
-                ('listening_perct', models.DecimalField(decimal_places=1, default=0.0, max_digits=3)),
-                ('writing_perct', models.DecimalField(decimal_places=1, default=0.0, max_digits=3)),
-            ],
-        ),
-        migrations.CreateModel(
-            name='LectureActivityFrameGroupings',
-            fields=[
-                ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
-                ('name', models.CharField(default='', max_length=15)),
-                ('frame_group_details', djongo.models.fields.ArrayField(model_container=FirstApp.MongoModels.LectureActivityFrameGroupDetails)),
-                ('lecture_activity_id', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='FirstApp.LectureActivity')),
-            ],
-        ),
-    ]

FirstApp/serializers.py

@@ -210,6 +210,15 @@ class LectureActivitySerializer(serializers.ModelSerializer):
         fields = '__all__'
 
 
+class LectureActivityFrameGroupingsSerializer(serializers.ModelSerializer):
+
+    lecture_activity_id = LectureActivitySerializer()
+
+    class Meta:
+        model = LectureActivityFrameGroupings
+        fields = '__all__'
+
+
 # EMOTIONS section
 # lecture emotions serailzier
 class LectureEmotionSerializer(serializers.ModelSerializer):

FirstApp/templates/FirstApp/Home.html

@@ -36,6 +36,7 @@
         var global_video_name = '';
         var student_behavior_summary = {};
         var lecture_video_time_landmarks = [];
+        var lecture_activity_frame_group_percentages = {};
 
 
         $(document).ready(function () {
@@ -56,7 +57,7 @@
 
                 let counter = $(this).attr('data-counter');
 
-                alert('counter: ' + counter);
+                {#alert('counter: ' + counter);#}
 
                 let real_date = new Date(global_lecture_date);
                 //extract the day
@@ -250,20 +251,18 @@
 
 
             //this function will handle the activity 'summary' button
-            $('#activity_summary_btn').click(function () {
+            $('#activity_summary_btn').click(function (e) {
+
+                //change the innerHTML of the clicked button
+                e.target.innerHTML = "<span class='font-italic'>Processing</span>";
 
                 //fetch the activity summary details
                 fetch('http://127.0.0.1:8000/get-lecture-activity-summary/?video_name=' + global_video_name)
                 .then((res) => res.json())
-                .then((out) => alert(out.frame_landmarks))
+                .then((out) => activityFrameGroupPercentages(out, e))
                 .catch((err) => alert('error: ' + err));
 
-                //open the modal
-                $('#summaryModal').modal();
-
 
-                //render the chart onto the modal body
-                renderChart();
             });
 
             //this function will handle the emotion 'summary' button
@@ -287,18 +286,81 @@
             });
 
 
+            //this function will handle the retrieved activity frame group percentages
+            function activityFrameGroupPercentages(response, e) {
+
+                lecture_activity_frame_group_percentages = response.frame_group_percentages;
+                let frame_landmarks = response.frame_landmarks;
+                let frame_group_dict = response.frame_group_dict;
+                let activity_labels = response.activity_labels;
+
+
+                //change the button back to original
+                e.target.innerHTML = "Summary";
+
+                //open the modal
+                $('#summaryModal').modal();
+
+
+                //render the chart onto the modal body
+                renderChart(activity_labels);
+            }
+
+
             //this function will call the chart function
-            function renderChart() {
+            function renderChart(activity_labels) {
+
+                //get the activity label length
+                let activity_label_length = activity_labels.length;
+
+                let data = [];
+
+
+                //loop through the activity labels
+                for (let k = 0; k < activity_label_length; k++) {
+                    let label = activity_labels[k];
+                    let datapoints = [];
+
+                    let count = 0;
+
+                    //loop through the activity frame groups
+                    for (let key in lecture_activity_frame_group_percentages) {
+                        let frame_group_details = lecture_activity_frame_group_percentages[key];
+
+                        let activity_perct = frame_group_details[label];
+
+                        let point = {label: lecture_video_time_landmarks[count], y: activity_perct};
 
-                let datapoints = [];
+                        datapoints.push(point);
+
+                        count++;
+                    }
+
+                    let obj = {
+                        type: "line",
+                        showInLegend: true,
+                        name: label,
+                        markerType: "square",
+                        {#xValueFormatString: "DD MMM, YYYY",#}
+                        xValueFormatString: "hh:mm:ss",
+                        color: getRandomColor(),
+                        dataPoints: datapoints
+                    };
+
+                    data.push(obj);
+
+                }
 
                 //iterate through the time landmarks
+                /*
                 for (let i = 0; i < lecture_video_time_landmarks.length; i++) {
                     let point = {label: lecture_video_time_landmarks[i], y: Number(Math.round(Math.random() * 1000), 0)};
 
                     datapoints.push(point);
                 }
 
+                 */
+
                 var chart = new CanvasJS.Chart("chartContainer", {
                     animationEnabled: true,
                     theme: "light2",
@@ -315,7 +377,7 @@
                         }
                     },
                     axisY: {
-                        title: "Number of Students",
+                        title: "Percentage",
                         includeZero: true,
                         crosshair: {
                             enabled: true
@@ -326,21 +388,12 @@
                     },
                     legend: {
                         cursor: "pointer",
-                        verticalAlign: "bottom",
-                        horizontalAlign: "left",
+                        verticalAlign: "top",
+                        horizontalAlign: "right",
                         dockInsidePlotArea: true,
                         itemclick: toogleDataSeries
                     },
-                    data: [{
-                        type: "line",
-                        showInLegend: true,
-                        name: "Activity",
-                        markerType: "square",
-                        {#xValueFormatString: "DD MMM, YYYY",#}
-                        xValueFormatString: "hh:mm:ss",
-                        color: "#000000",
-                        dataPoints: datapoints
-                    }]
+                    data: data
                 });
                 chart.render();
             }
@@ -380,7 +433,7 @@
                         name: label,
                         markerType: "square",
                         {#xValueFormatString: "DD MMM, YYYY",#}
-                        xValueFormatString: "Lec " + (i+1),
+                        xValueFormatString: "lec " + (i+1),
                         color: getRandomColor(),
                         dataPoints: datapoints
                     };