def InferenceData(trainer): images = ImageIO.ReadImagesFromFolder("../data/monster/himax_processed/", '.jpg', 0) [x_live, y_live] = DataProcessor.ProcessInferenceData(images, 60, 108) live_set = Dataset(x_live, y_live) params = {'batch_size': 1, 'shuffle': False, 'num_workers': 0} live_generator = data.DataLoader(live_set, **params) y_pred_himax = trainer.Infer(live_generator) y_pred_himax = np.reshape(y_pred_himax, (-1, 4)) h_images = images images = ImageIO.ReadImagesFromFolder("../data/monster/bebop_processed/", '.jpg', 0) [x_live, y_live] = DataProcessor.ProcessInferenceData(images, 60, 108) live_set = Dataset(x_live, y_live) params = {'batch_size': 1, 'shuffle': False, 'num_workers': 0} live_generator = data.DataLoader(live_set, **params) y_pred_bebop = trainer.Infer(live_generator) y_pred_bebop = np.reshape(y_pred_bebop, (-1, 4)) combinedImages = [] for i in range(len(images)): img = ImageEffects.ConcatImages(images[i], h_images[i]) combinedImages.append(img) VizDroneBEV(combinedImages, y_pred_bebop, y_pred_himax)