Merge branch 'it18255720_jayakody' into 'master'

Update microwave detection

See merge request !27

Child_detection/electricalObject-detection.py

@@ -5,27 +5,30 @@ from imageai.Detection import ObjectDetection, VideoObjectDetection
 import sys
 import os
 import cv2
-
 import time
 from shapely.geometry import box
 
 THRESHOLD_ITEM = 0.5
 THRESHOLD_PERSON = 0.5
 
-print("Sharp Object Detection Begins")
+execution_path = "input/"
+Output_Path = "output/"
+
+#print("Sharp Object Detection Begins")
 
 detector = VideoObjectDetection()
 detector2 = VideoObjectDetection()
 
 
+detector = VideoObjectDetection()
+detector2 = VideoObjectDetection()
+
 detector.setModelTypeAsYOLOv3()
-detector.setModelPath("../model/yolo.h5")
+detector.CustomObjects(microwave=True,oven=True,person=True)
+detector.setModelPath("models/yolo.h5")
+detector.loadModel(detection_speed="fast")
 detector.loadModel()
 
-detector2.setModelTypeAsRetinaNet()
-detector2.setModelPath("model/resnet50_coco_best_v2.1.0.h5")
-detector2.loadModel()
-
 
 def forFrame(frame_number, output_array, output_count, returned_frame):
     microwave_count = 0
@@ -39,7 +42,7 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
     count = 0
     persons = []
 
-
+    # YOLO Model (Person) and RetinaModel (Toaster, Microwave and Oven, Hair Dryer) both - Single Frame - Person
     for detection in output_array:
         print(
             detection['name'] + " - " + str(detection['percentage_probability']) + " - " + str(detection['box_points']))
@@ -71,7 +74,8 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
             powercords.append(detection['box_points'])
             print(detection["name"], " : ", detection["percentage_probability"], " : ", detection["box_points"])
 
-
+    # Check if Child is in 100 Pixels to Left and 100 Pixels to Right of the Identified Object(s)
+    # Check if there is a person in view
     if (len(persons) == 0):
         print("There is no Person in the Room!")
 
@@ -80,33 +84,38 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
 
     if (len(persons) >= 1):
         for person in persons:
-
+            # Create Person(minx, miny, maxx, maxy)
             person_box = box(person[0], person[3], person[1], person[2])
 
-            coords = person
+            coords = person  # (x1, x2, y1, y2)
             x1 = person[0]
             x2 = person[1]
             y1 = person[2]
             y2 = person[3]
 
             person_midpoint = ((x1 + x2) / 2, (y1 + y2) / 2)
-            x_center = (x1 + x2) / 2
-            y_center = (y1 + y2) / 2
-
-
+            x_center = (x1 + x2) / 2  # Center X Coordinate
+            y_center = (y1 + y2) / 2  # Center Y Coordinate
+
+            # x1 => Left, x2 => Right, y1 => Top, y2 => Bottom
+            # (x1, y1) - Top Left
+            # (x2, y2) - Bottom Right
+            # (x2, y1) - Top Right
+            # (x1, y2) - Bottom Left
             if microwave_count > 0:
-
+                # Iterate each Microwave
                 for microwave in microwaves:
-
+                    # Create Microwave(minx, miny, maxx, maxy)
                     microwave_box = box(microwave[0] + 50, microwave[3] + 50, microwave[1] + 50, microwave[2] + 50)
-
-                    e_x1 = microwave[0] + 50
-                    e_x2 = microwave[1] + 50
-                    e_y1 = microwave[2] + 50
-                    e_y2 = microwave[3] + 50
+                    # Check if Microwave Overlaps with the Person's Safety Boundary
+                    # We Add 50px in all directions of the Bounding Box - Top+50, Bottom+50, Left+50, Right+50
+                    e_x1 = microwave[0] + 50  # Left
+                    e_x2 = microwave[1] + 50  # Right
+                    e_y1 = microwave[2] + 50  # Top
+                    e_y2 = microwave[3] + 50  # Bottom
                     overlap = False
 
-
+                    # Check if the Microwave Oven is in the Persons Danger Region
                     if (microwave_box.intersection(person_box) != None):
                         print("Microwave/Oven - Person is in the Microwave/Oven's Danger Region!")
                         overlap = True
@@ -125,7 +134,8 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
                         overlap = True
 
                     if (overlap == True):
-
+                        # If the Bounding Boxes Overlap at some point
+                        # Calculate Distnace between center point of two boxes
                         microwave_midpoint = ((e_x1 + e_x2) / 2, (e_y1 + e_y2) / 2)
                         distance = ((((microwave_midpoint[0] - person_midpoint[0]) ** 2) + (
                                     (microwave_midpoint[1] - person_midpoint[1]) ** 2)) ** 0.5)
@@ -196,7 +206,7 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
                         powercord_thresh = cv2.dilate(powercord_thresh, None, iterations=4)
 
 # detections = detector.detectObjectsFromImage(input_image="input/electric1.jpg", output_image_path="output/electric1.jpg")
-detector.detectObjectsFromVideo(input_file_path=os.path.join("output/video1.mp4", "video1.mp4"),output_file_path=os.path.join("output/video1.mp4", "video_frame_analysis"),frames_per_second=24, per_frame_function=forFrame,minimum_percentage_probability=50, return_detected_frame=True)
+detector.detectObjectsFromVideo(input_file_path=os.path.join(execution_path, "oven1.mp4"), output_file_path=os.path.join(Output_Path, "video_frame_analysis_oven1.mp4") ,  frames_per_second=24, per_frame_function=forFrame,  minimum_percentage_probability=50, return_detected_frame=True)
 
 # detections2 = detector2.detectObjectsFromImage(input_image="input/sharp2.jpg", output_image_path="output/sharp2.jpg")
-detector2.detectObjectsFromVideo(input_file_path=os.path.join("output/video1.mp4", "video1.mp4"),output_file_path=os.path.join("output/video1.mp4", "video_frame_analysis"),frames_per_second=24, per_frame_function=forFrame,minimum_percentage_probability=50, return_detected_frame=True)
\ No newline at end of file
+# detector2.detectObjectsFromVideo(input_file_path=os.path.join(execution_path, "oven1.mp4"), output_file_path=os.path.join(execution_path, "video_frame_analysis_oven1.mp4") ,  frames_per_second=24, per_frame_function=forFrame,  minimum_percentage_probability=50, return_detected_frame=True)
\ No newline at end of file