fix integrated system

boss_input.py

@@ -61,7 +61,6 @@ def read_image(file_path):
 def extract_data(path):
     images, labels = traverse_dir(path)
     images = np.array(images)
-    dic = dict([(label, i) for i, label in enumerate(set(labels))])
-    labels = np.array([dic[label] for label in labels])
+    labels = np.array([0 if label.endswith('boss') else 1 for label in labels])
 
     return images, labels

boss_train.py

@@ -143,8 +143,10 @@ def predict(self, image):
         if image.shape != (1, 3, IMAGE_SIZE, IMAGE_SIZE):
             image = resize_with_pad(image)
             image = image.reshape((1, 3, IMAGE_SIZE, IMAGE_SIZE))
+        result = self.model.predict_proba(image)
+        print(result)
         result = self.model.predict_classes(image)
-        # result = self.model.predict_proba(image)
+
 
         return result[0]
 
@@ -156,24 +158,30 @@ def evaluate(self, dataset):
 
     dataset = Dataset()
     dataset.read()
-
+    """
     model = Model()
     model.build_model(dataset)
     model.train(dataset, nb_epoch=10)
     model.save()
-
+    """
     model = Model()
     model.load()
     model.evaluate(dataset)
-    for image, label in zip(dataset.X_test, dataset.Y_test):
-        model.predict(image.reshape(1, 3, IMAGE_SIZE, IMAGE_SIZE))
-        print(label)
+    #for image, label in zip(dataset.X_test, dataset.Y_test):
+     #   model.predict(image.reshape(1, 3, IMAGE_SIZE, IMAGE_SIZE))
+      #  print(label)
     """
     import cv2
     import os
-
-    #image = cv2.imread('./data/other/Abdel_Nasser_Assidi_0002.jpg')
-
+    model = Model()
+    model.load()
+    image = cv2.imread('test.jpg')
+    image = resize_with_pad(image)
+    image = image.reshape((1, 3, IMAGE_SIZE, IMAGE_SIZE))
+    result = model.predict(image)
+    print(result)
+    """
+    """
     for file_name in os.listdir('./data/boss'):
         if file_name.endswith('.jpg'):
             print(file_name)

camera_reader.py

@@ -72,7 +72,8 @@ def run(self):
     model = Model()
     model.load()
     while True:
-        ret, frame = cap.read()
+        _, frame = cap.read()
+
         # グレースケール変換
         frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 
@@ -90,11 +91,13 @@ def run(self):
 
                 x, y = rect[0:2]
                 width, height = rect[2:4]
-                image = frame[y-50: y + height, x: x + width + 50]
-                cv2.imwrite('test.jpg', image)
+                #image = frame[y - 50: y + height, x: x + width + 50]
+                image = frame[y - 50: y + height, x: x + width]
+                #image = frame[y: y + height, x: x + width]
+                #now = datetime.now().strftime('%Y%m%d%H%M%S')
+                #cv2.imwrite(now + '.jpg', image)
                 result = model.predict(image)
-                print(result)
-                if result == 1:  # boss
+                if result == 0:  # boss
                     print('Boss is approaching')
                     show_image()
                 else: