add fire detection script

tested with local images of unknown person and fire

+{
+    "labels" : [
+        "fire"
+    ],
+    "anchors" : [
+        [
+            129,
+            208,
+            183,
+            155,
+            198,
+            259
+        ],
+        [
+            73,
+            140,
+            109,
+            80,
+            119,
+            131
+        ],
+        [
+            22,
+            31,
+            31,
+            57,
+            54,
+            80
+        ]
+    ]
+}
\ No newline at end of file

 import process
+import base64
 
 if __name__ == '__main__':
     p = process.Process()
-    p.ProcessImage()
\ No newline at end of file
+
+    # image to base64 encoding
+    # you have to set 'encoded_image' to frame code
+    with open("./known_images/obama.jpg", "rb") as img_file:
+        encoded_obama_image = base64.b64encode(img_file.read())
+
+    with open("./test_images/Fire.jpg", "rb") as img_file:
+        encoded_fire_image = base64.b64encode(img_file.read())
+
+    with open("./test_images/unknown.jpg", "rb") as img_file:
+        encoded_unknown_image = base64.b64encode(img_file.read())
+    
+    p.ProcessImage(encoded_obama_image)
+    p.ProcessImage(encoded_fire_image)
+    p.ProcessImage(encoded_unknown_image)
\ No newline at end of file

+from imageai.Detection.Custom import CustomObjectDetection, CustomVideoObjectDetection
 import base64
 import face_recognition
 import numpy as np
 from cv2 import cv2
 import os
+import json
+import sys
 
 class Process:
     def __init__(self):
-        known_path = './images/' # directory path of known faces
+        known_path = './known_images/' # directory path of known faces
         image_format = 'jpg'
 
         known_list = os.listdir(known_path)
@@ -18,11 +21,17 @@ class Process:
             known_img = face_recognition.load_image_file(known_path+f)
             known_img_encoding = face_recognition.face_encodings(known_img)[0]
             self.known_faces.append(known_img_encoding)
-    def ProcessImage(self):
-        # image to base64 encoding
-        # you have to set 'encoded_image' to frame code
-        with open("./images/obama.jpg", "rb") as img_file:
-            encoded_image = base64.b64encode(img_file.read())
+        
+        self.execution_path = os.getcwd()
+
+        self.detector = CustomObjectDetection()
+        self.detector.setModelTypeAsYOLOv3()
+        self.detector.setModelPath(detection_model_path=os.path.join(self.execution_path, "detection_model-ex-33--loss-4.97.h5"))
+        self.detector.setJsonPath(configuration_json=os.path.join(self.execution_path, "detection_config.json"))
+        self.detector.loadModel()
+
+    def ProcessImage(self, data):
+        encoded_image = data
 
         #base64 to image(uint8) decoding
         img64_decode = base64.b64decode(encoded_image)
@@ -30,8 +39,9 @@ class Process:
         decoded_img = cv2.imdecode(im_arr, flags=cv2.IMREAD_COLOR)
 
         face = self.FaceRecognition(decoded_img) #True면 침입자 발생
+        fire = self.FireDetection(decoded_img) #True면 화재발생
 
-        result= {"unknown_person" : face}
+        result= {"unknown_person" : face, "fire_broken" : fire}
         print(result)
         return result
     def FaceRecognition(self, decoded_img):
@@ -44,4 +54,18 @@ class Process:
             return not True in results
         except IndexError:
             print("얼굴없음")
-            return False
\ No newline at end of file
+            return False
+
+    def FireDetection(self, decoded_img):
+        detections = self.detector.detectObjectsFromImage(input_image=decoded_img, input_type="array",
+                                                    output_image_path=os.path.join(self.execution_path, "fire_detected.jpg"),
+                                                    minimum_percentage_probability=40)
+
+        if len(detections) == 0 : fire_broken = False
+        else : fire_broken = True
+        
+        return fire_broken
+        '''
+        for detection in detections:
+            print(detection["name"], " : ", detection["percentage_probability"], " : ", detection["box_points"])
+        '''
\ No newline at end of file