Check Model - Mask Detection

detect.py

def check(image):
    image_np = cv2.imread(image)
    input_tensor = tf.convert_to_tensor(
        np.expand_dims(image_np, 0), dtype=tf.float32)

    detections = detect_fn(input_tensor)
    category_index = label_map_util.create_category_index_from_labelmap(
        ANNOTATION_PATH+'/label_map.pbtxt')

    num_detections = int(detections.pop('num_detections'))
    detections = {key: value[0, :num_detections].numpy()
                  for key, value in detections.items()}
    detections['num_detections'] = num_detections
    detections['detection_classes'] = detections['detection_classes'].astype(
        np.int64)

    label_id_offset = 1
    image_np_with_detections = image_np.copy()

    viz_utils.visualize_boxes_and_labels_on_image_array(
        image_np_with_detections,
        detections['detection_boxes'],
        detections['detection_classes']+label_id_offset,
        detections['detection_scores'],
        category_index,
        use_normalized_coordinates=True,
        max_boxes_to_draw=1,
        min_score_thresh=0.1,
        agnostic_mode=False)

    cv2.imwrite('Tensorflow/workspace/images/check/results/six.png',
                image_np_with_detections)
    print(
        f"Class - {detections['detection_classes'][0] + label_id_offset}\nScores - {detections['detection_scores'][0]}\nBoxes - {detections['detection_boxes'][0]}")