def evaluation(loader, lane_agent, index=-1, thresh=p.threshold_point, name=None): result_data = deepcopy(loader.test_data) progressbar = tqdm(range(loader.size_test // 4)) for test_image, target_h, ratio_w, ratio_h, testset_index, gt in loader.Generate_Test( ): x, y, _ = test(lane_agent, test_image, thresh, index) x_ = [] y_ = [] for i, j in zip(x, y): temp_x, temp_y = util.convert_to_original_size( i, j, ratio_w, ratio_h) x_.append(temp_x) y_.append(temp_y) #x_, y_ = find_target(x_, y_, target_h, ratio_w, ratio_h) x_, y_ = fitting(x_, y_, target_h, ratio_w, ratio_h) result_data = write_result_json(result_data, x_, y_, testset_index) #util.visualize_points_origin_size(x_[0], y_[0], test_image[0], ratio_w, ratio_h) #print(gt.shape) #util.visualize_points_origin_size(gt[0], y_[0], test_image[0], ratio_w, ratio_h) progressbar.update(1) progressbar.close() if name == None: save_result(result_data, "test_result.json") else: save_result(result_data, name)
def evaluation(loader, lane_agent, thresh = p.threshold_point, name = None): result_data = deepcopy(loader.test_data) for test_image, target_h, ratio_w, ratio_h, testset_index in loader.Generate_Test(): x, y, _ = test(lane_agent, np.array([test_image]), thresh) x, y = util.convert_to_original_size(x[0], y[0], ratio_w, ratio_h) x, y = find_target(x, y, target_h, ratio_w, ratio_h) result_data = write_result_json(result_data, x, y, testset_index) if name == None: save_result(result_data, "test_result.json") else: save_result(result_data, name)
def evaluation(loader, lane_agent, thresh = p.threshold_point, index= -1, name = None): progressbar = tqdm(range(loader.size_test//4)) for test_image, ratio_w, ratio_h, path, target_h, target_lanes in loader.Generate_Test(): x, y, _ = test(lane_agent, test_image, thresh, index= index) x_ = [] y_ = [] for i, j in zip(x, y): temp_x, temp_y = util.convert_to_original_size(i, j, ratio_w, ratio_h) x_.append(temp_x) y_.append(temp_y) #x_, y_ = find_target(x_, y_, ratio_w, ratio_h) x_, y_ = fitting(x_, y_, ratio_w, ratio_h) #util.visualize_points_origin_size(x_[0], y_[0], test_image[0]*255, ratio_w, ratio_h) #print(target_lanes) #util.visualize_points_origin_size(target_lanes[0], target_h[0], test_image[0]*255, ratio_w, ratio_h) result_data = write_result(x_, y_, path) progressbar.update(1) progressbar.close()