Created image detector

src/detector/detect_traffic_light_color_image.py

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+"""This program uses a trained neural network to detect the color of a traffic light in images."""
+
+import logging
+from pathlib import Path
+
+# import cv2
+# import numpy as np
+from detector.object_detection import load_ssd_coco, perform_object_detection
+from detector.paths import IMAGES_IN_PATH, LOGS_PATH, MODEL_PATH
+from tensorflow import keras
+# from tensorflow.keras.applications import imagenet_utils
+# from tensorflow.keras.applications.inception_v3 import InceptionV3, preprocess_input
+
+# Set up logging
+logger = logging.getLogger(__name__)
+handler = logging.FileHandler(str(Path.joinpath(LOGS_PATH, f"{__name__}.log")))
+formatter = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
+handler.setFormatter(formatter)
+logger.addHandler(handler)
+
+
+def detect_traffic_light_color_image() -> None:
+    model_traffic_lights_nn = keras.models.load_model(str(MODEL_PATH))
+
+    # Go through all image files, and detect the traffic light color.
+    for file in Path.iterdir(IMAGES_IN_PATH):
+        image, out, file_name = perform_object_detection(load_ssd_coco(), file, save_annotated=True, model_traffic_lights=model_traffic_lights_nn)
+        logger.info(f"{file} {out}")