Merge pull request #40 from abhiramasonny/updates

updates to cloth and main

Author: abhiramasonny

main.py

@@ -8,7 +8,7 @@ def main(tryall=True):
     gun_detection = GunDetection(weight_path_gun, config_path_gun)
 
     if not tryall:
-        cam1 = cv2.VideoCapture(0)
+        cam1 = cv2.VideoCapture(1)
         #cam2 = cv2.VideoCapture(1)
         cameras = [
             (cam1, "Zone 1")#, (cam2, 'Zone 2')
@@ -37,7 +37,23 @@ def main(tryall=True):
             clothes_detection = ClothesDetection(len(cameras))
             wearing,colour = clothes_detection.run_detection(cameras)
             print(f"wearing {wearing} and RGB {colour}")
+            while True:
+                    for i in gun_detection.run_detection(cameras):
+                        #print(f'{i}')
+                        print(type(i))
+                        if type(i) == dict:
+                            if 1 in list(i.values()):
+                                for key, value in i.items():
+                                    if value == 1:
+                                        print(f'Gunman in {key}')
+                                        #sendP(key[-1])
+                            else:
+                                print('No Gunman found')
+
+                            #sendP(i)
+                            #if type(i) != int:
+                            #   break
 
 if __name__ == "__main__":
-    main()
+    main(tryall=False)
 

src/yolov3/__pycache__/detection.cpython-310.pyc

@@ -166,24 +166,4 @@ def get_avg_rgb(self, box_array: list, frame: np.ndarray) -> list:
         return avg_rgb_values
     def colour_from_RGB(avg_rgb_values):
         pass
-
-    def get_color_category(self, avg_rgb_values: list) -> str:
-        color_thresholds = {
-            'Red': (150, 30, 30),
-            'White': (220, 220, 220),
-            'Black': (30, 30, 30),
-            'Blue': (30, 30, 150),
-            'Green': (30, 150, 30)
-        }
-
-        min_distance = float('inf')
-        color_category = None
-
-        for category, threshold in color_thresholds.items():
-            distance = np.linalg.norm(np.array(avg_rgb_values) - np.array(threshold))
-            if distance < min_distance:
-                min_distance = distance
-                color_category = category
-
-        return color_category