trainer.py 文件源码

def evaluate_images():
    ssd = SSD()

    cv2.namedWindow("outputs", cv2.WINDOW_NORMAL)
    loader = coco.Loader(False)
    test_batches = loader.create_batches(1, shuffle=True)
    global i2name
    i2name = loader.i2name

    while True:
        batch = test_batches.next()
        imgs, anns = loader.preprocess_batch(batch)
        pred_labels_f, pred_locs_f, step = ssd.sess.run([ssd.pred_labels, ssd.pred_locs, ssd.global_step],
                                                        feed_dict={ssd.imgs_ph: imgs, ssd.bn: False})
        boxes_, confidences_ = matcher.format_output(pred_labels_f[0], pred_locs_f[0])
        draw_outputs(imgs[0], boxes_, confidences_, wait=0)