Merge branch 'IT18052152_Givindu' into 'master'

V1.16.2

See merge request !91

abnormal_behavior_detection/HumanDetection/Human_Detection_Video.py

@@ -20,14 +20,12 @@ def capture_humans(path):
     # detector.setPreferableBackend(cv2.dnn.DNN_BACKEND_INFERENCE_ENGINE)
     # detector.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)
 
-    CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat",
-               "bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
-               "dog", "horse", "motorbike", "person", "pottedplant", "sheep",
-               "sofa", "train", "tvmonitor"]
+    CLASSES = []
+    classFile = 'E:/BACKBONE/abnormal_behavior_detection/Models/Human Detection/class.names'
+    with open(classFile, 'rt') as f:
+        CLASSES = f.read().rstrip('\n').split('\n')
 
     print("STEP 1 ON PROGRESS...")
-    print("test12345")
-    print("test11")
 
 
     #Get input video
@@ -50,7 +48,7 @@ def capture_humans(path):
     while True:
         ret, frame = cap.read()
         if ret != False:
-            frame = imutils.resize(frame, width=500)
+            frame = imutils.resize(frame, width=800)
             total_frames = total_frames + 1
 
             (H, W) = frame.shape[:2]

abnormal_behavior_detection/WeaponDetection/Knife_Detection.py

@@ -36,7 +36,7 @@ def weaponDetection():
 
     ## Model Files
     modelConfiguration = "E:/BACKBONE/abnormal_behavior_detection/Models/Knife Detection/yolov4-custom.cfg"
-    modelWeights = "E:/BACKBONE/abnormal_behavior_detection/Models/Knife Detection/yolov4-custom_last.weights"
+    modelWeights = "E:/BACKBONE/abnormal_behavior_detection/Models/Knife Detection/yolov4-custom_best.weights"
     net = cv.dnn.readNetFromDarknet(modelConfiguration, modelWeights)
     net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
     net.setPreferableTarget(cv.dnn.DNN_TARGET_CPU)
@@ -70,32 +70,8 @@ def weaponDetection():
             box = bbox[i]
             x, y, w, h = box[0], box[1], box[2], box[3]
 
-            # Detect handguns
-            if classIds[i] == 0:
-                # print(x,y,w,h)
-                text = "{:.4f}%".format((confs[i]) * 100)
-                print("Suspect Detected : ", "[", text, "]")
-                cv.rectangle(img, (x, y), (x + w, y + h), (255, 0, 255), 2)
-                cv.putText(img, f'{classNames[classIds[i]].upper()} {int(confs[i] * 100)}%',
-                           (x, y - 10), cv.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 2)
-
-                # save detected frames
-                cv2.imwrite('C:/Users/Givindu/Desktop/New folder/frames/Suspects with Weapons/frame%d.jpg' % count, img)
-                count += 1
-
-                # Create and save in a CSV file
-                type = "Abnormal Activity"
-                weapon = "The Pistol was used as a weapon"
-                with open('C:/Users/Givindu/Desktop/New folder/frames/Abnormal Activity.csv', 'w', newline='') as file:
-                    Num += 1
-                    TimeD = start - time.time()
-                    arr = [Num, type, weapon, TimeD]
-                    writer = csv.writer(file)
-                    writer.writerow(field)
-                    writer.writerow(arr)
-
-
 
+            # Detect Knives
             if classIds[i] == 1:
             # print(x,y,w,h)
                 text = "{:.4f}%".format((confs[i])*100)
@@ -120,6 +96,8 @@ def weaponDetection():
                     writer.writerow(arr)
 
 
+
+
     while True:
         success, img = cap.read()
         if success != False:

abnormal_behavior_detection/WeaponDetection/Weapon_Detection.py

@@ -36,7 +36,7 @@ def weaponDetection():
 
     ## Model Files
     modelConfiguration = "E:/BACKBONE/abnormal_behavior_detection/Models/Weapon Detection/yolov4-custom.cfg"
-    modelWeights = "E:/BACKBONE/abnormal_behavior_detection/Models/Weapon Detection/yolov4-custom_last.weights"
+    modelWeights = "E:/BACKBONE/abnormal_behavior_detection/Models/Weapon Detection/yolov4-custom_best.weights"
     net = cv.dnn.readNetFromDarknet(modelConfiguration, modelWeights)
     net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
     net.setPreferableTarget(cv.dnn.DNN_TARGET_CPU)
@@ -70,8 +70,34 @@ def weaponDetection():
             box = bbox[i]
             x, y, w, h = box[0], box[1], box[2], box[3]
 
+
             # Detect handguns
-            if classIds[i] == 0:
+            if classIds[i] == '0':
+            # print(x,y,w,h)
+                text = "{:.4f}%".format((confs[i])*100)
+                print("Suspect Detected : ", "[", text, "]")
+                # cv.rectangle(img, (x, y), (x + w, y + h), (255, 0, 255), 2)
+                # cv.putText(img, f'{classNames[classIds[i]].upper()} {int(confs[i] * 100)}%',
+                #           (x, y - 10), cv.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 2)
+
+                cv2.imwrite('E:/BACKBONE/abnormal_behavior_detection/frames/Suspects with Weapons/frame%d.jpg' % count, img)
+                count += 1
+
+                # Create and save in a CSV File
+                type = "Abnormal Activity"
+                weapon = "The Pistol was used as a weapon"
+                with open('E:/BACKBONE/abnormal_behavior_detection/CSV/Abnormal Activity.csv', 'w', newline='') as file:
+                    Num += 1
+                    TimeD = time.time() - start
+                    arr = [Num, type, weapon, TimeD]
+                    writer = csv.writer(file)
+                    writer.writerow(field)
+                    writer.writerow(arr)
+
+
+
+            # Detect knives
+            if classIds[i] == 1:
             # print(x,y,w,h)
                 text = "{:.4f}%".format((confs[i])*100)
                 print("Suspect Detected : ", "[", text, "]")
@@ -79,6 +105,7 @@ def weaponDetection():
                 #cv.putText(img, f'{classNames[classIds[i]].upper()} {int(confs[i] * 100)}%',
                 #           (x, y - 10), cv.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 2)
 
+                # save detected frames
                 cv2.imwrite('E:/BACKBONE/abnormal_behavior_detection/frames/Suspects with Weapons/frame%d.jpg' % count, img)
                 count += 1
 
@@ -94,6 +121,33 @@ def weaponDetection():
                     writer.writerow(arr)
 
 
+
+            # Detect grenades
+            if classIds[i] == '2':
+            # print(x,y,w,h)
+                text = "{:.4f}%".format((confs[i])*100)
+                print("Suspect Detected : ", "[", text, "]")
+                #cv.rectangle(img, (x, y), (x + w, y + h), (255, 0, 255), 2)
+                #cv.putText(img, f'{classNames[classIds[i]].upper()} {int(confs[i] * 100)}%',
+                #           (x, y - 10), cv.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 2)
+
+                # save detected frames
+                cv2.imwrite('E:/BACKBONE/abnormal_behavior_detection/frames/Suspects with Weapons/frame%d.jpg' % count, img)
+                count += 1
+
+                # Create and save in a CSV File
+                type = "Abnormal Activity"
+                weapon = "The Grenade was used as a weapon"
+                with open('E:/BACKBONE/abnormal_behavior_detection/CSV/Abnormal Activity.csv', 'w', newline='') as file:
+                    Num += 1
+                    TimeD = time.time() - start
+                    arr = [Num, type, weapon, TimeD]
+                    writer = csv.writer(file)
+                    writer.writerow(field)
+                    writer.writerow(arr)
+
+
+
     while True:
         success, img = cap.read()
         if success != False: