8ef6a1f133a9b18e1bd530d2dd550a93082fa59f,keras_layer_DecodeDetections.py,DecodeDetections,__init__,#DecodeDetections#,39

Before Change

        if coords != "centroids":
            raise ValueError("The DetectionOutput layer currently only supports the "centroids" coordinate format.")

        self.confidence_thresh = tf.constant(confidence_thresh, name="confidence_thresh")
        self.iou_threshold = tf.constant(iou_threshold, name="iou_threshold")
        self.top_k = tf.constant(top_k, name="top_k")
        self.normalize_coords = tf.constant(normalize_coords, name="normalize_coords")
        self.img_height = tf.constant(img_height, dtype=tf.float32, name="img_height")
        self.img_width = tf.constant(img_width, dtype=tf.float32, name="img_width")
        self.coords = coords

After Change

            raise ValueError("The DetectionOutput layer currently only supports the "centroids" coordinate format.")

        // We need these members for the config.
        self.confidence_thresh = confidence_thresh
        self.iou_threshold = iou_threshold
        self.top_k = top_k
        self.normalize_coords = normalize_coords
        self.img_height = img_height
        self.img_width = img_width
        self.coords = coords
        self.nms_max_output_size = nms_max_output_size

        // We need these members for TensorFlow.
        self.tf_confidence_thresh = tf.constant(self.confidence_thresh, name="confidence_thresh")
        self.tf_iou_threshold = tf.constant(self.iou_threshold, name="iou_threshold")
        self.tf_top_k = tf.constant(self.top_k, name="top_k")
        self.tf_normalize_coords = tf.constant(self.normalize_coords, name="normalize_coords")
        self.tf_img_height = tf.constant(self.img_height, dtype=tf.float32, name="img_height")
        self.tf_img_width = tf.constant(self.img_width, dtype=tf.float32, name="img_width")
        self.tf_nms_max_output_size = tf.constant(self.nms_max_output_size, name="nms_max_output_size")

Instances