示例#1
0
def test_align_gt(runs_dirpath, ori_image, ori_metadata, ori_gt_polygons, batch_size, ds_fac_list, run_name_list,
                  model_disp_max_abs_value, output_dir=None, output_name=None, output_shapefiles=True, properties_list=None):
    # --- Run the model --- #
    print("# --- Run the model --- #")
    aligned_gt_polygons, _ = multires_pipeline.multires_inference(runs_dirpath, ori_image,
                                                                                     ori_metadata,
                                                                                     ori_gt_polygons,
                                                                                     model_disp_max_abs_value,
                                                                                     batch_size, ds_fac_list,
                                                                                     run_name_list)

    # --- Save polygons as shapefiles --- #
    if output_shapefiles:
        if output_dir is not None and output_name is not None:
            import geo_utils
            print("# --- Save polygons as shapefiles --- #")
            shapefile_filename_format = "{}.aligned_gt_polygons.shp"
            output_shapefile_filename = shapefile_filename_format.format(output_name, "ori")
            output_shapefile_filepath = os.path.join(output_dir, output_shapefile_filename)
            geo_utils.save_shapefile_from_polygons(aligned_gt_polygons, ori_metadata["filepath"],
                                                   output_shapefile_filepath, properties_list=properties_list)
        else:
            print_utils.print_warning("Could not save shapefile as output_dir and/or output_name was not specified.")

    return aligned_gt_polygons
示例#2
0
def test_detect_new_buildings(runs_dirpath, image_name, ori_image, ori_metadata, ori_gt_polygons, batch_size, ds_fac_list,
                              run_name_list, model_disp_max_abs_value, polygonization_params, thresholds,
                              test_output_dir, output_shapefiles=True):
    ori_gt_polygons = polygon_utils.polygons_remove_holes(ori_gt_polygons)  # TODO: Remove
    ori_gt_polygons = polygon_utils.simplify_polygons(ori_gt_polygons, tolerance=1)  # Remove redundant vertices
    ori_disp_polygons = []  # Don't input any polygons

    output_name = image_name
    seg_image_plot_filename_format = "{}.segmentation.png"
    ious_filename_format = "{}.iou.npy"
    new_polygons_filename_format = "{}.new_polygons.npy"
    aligned_new_polygons_filename_format = "{}.aligned_new_polygons.npy"
    polygons_image_plot_filename_format = "{}.polygons.png"

    shapefile_filename_format = "{}.{}_polygons.shp"
    accuracies_filename_format = "{}.accuracy.npy"

    # --- Get the segmentation output --- #
    seg_ds_fac_list = ds_fac_list[-1:]
    seg_run_name_list = run_name_list[-1:]
    print("# --- Run the model --- #")
    _, segmentation_image = multires_pipeline.multires_inference(runs_dirpath, ori_image, ori_metadata,
                                                                 ori_disp_polygons,
                                                                 model_disp_max_abs_value,
                                                                 batch_size, seg_ds_fac_list,
                                                                 seg_run_name_list)
    # segmentation_image = np.zeros((ori_image.shape[0], ori_image.shape[1], 4))
    print("# --- Save segmentation_output --- #")
    plot_segmentation_image_filename = seg_image_plot_filename_format.format(output_name)
    plot_segmentation_image_filepath = os.path.join(test_output_dir, plot_segmentation_image_filename)
    visualization.save_plot_segmentation_image(plot_segmentation_image_filepath, segmentation_image)

    seg_image = segmentation_image[:, :, 1:]  # Remove background channel

    # --- Measure IoUs --- #
    print("# --- Measure accuracies --- #")
    print(seg_image.min())
    print(seg_image.max())
    iou_thresholds = np.arange(0, 1.01, 0.01)
    ious_filename = ious_filename_format.format(output_name)
    ious_filepath = os.path.join(test_output_dir, ious_filename)
    ious = measure_ious(ori_gt_polygons, seg_image, iou_thresholds, ious_filepath)
    print("IoUs:")
    print(ious)

    # --- Polygonize segmentation --- #
    print("# --- Polygonize segmentation --- #")

    # TODO: remove:
    # seg_image_filepath = "test/bradbury_buildings.1_double.only_seg/SanFrancisco_01.disp_00.segmentation.png"
    # seg_image = image_utils.load_image(seg_image_filepath)
    # seg_image = seg_image / 255

    fill_threshold = polygonization_params["fill_threshold"]
    outline_threshold = polygonization_params["outline_threshold"]
    selem_width = polygonization_params["selem_width"]
    iterations = polygonization_params["iterations"]
示例#3
0
文件: test.py 项目: dtekeshe/ml
def test(ori_image,
         ori_metadata,
         ori_gt_polygons,
         ori_disp_polygons,
         batch_size,
         ds_fac_list,
         run_name_list,
         model_disp_max_abs_value,
         thresholds,
         test_output_dir,
         output_name,
         output_shapefiles=True,
         properties_list=None):
    if output_shapefiles:
        assert properties_list is not None and len(ori_disp_polygons) == len(
            properties_list
        ), "ori_disp_polygons and properties_list should have the same length"
    polygons_image_plot_filename_format = "{}.polygons.png"
    shapefile_filename_format = "{}.{}_polygons.shp"
    segmentation_image_plot_filename_format = "{}.segmentation.png"
    accuracies_filename_format = "{}.accuracy.npy"

    # --- Run the model --- #
    print("# --- Run the model --- #")
    aligned_disp_polygons, segmentation_image = multires_pipeline.multires_inference(
        ori_image, ori_metadata, ori_disp_polygons, model_disp_max_abs_value,
        batch_size, ds_fac_list, run_name_list)
    # aligned_disp_polygons = ori_disp_polygons
    # segmentation_image = np.zeros((ori_image.shape[0], ori_image.shape[1], 4))

    # --- Save segmentation_output --- #
    print("# --- Save segmentation_output --- #")
    plot_segmentation_image_filename = segmentation_image_plot_filename_format.format(
        output_name)
    plot_segmentation_image_filepath = os.path.join(
        test_output_dir, plot_segmentation_image_filename)
    visualization.save_plot_segmentation_image(
        plot_segmentation_image_filepath, segmentation_image)

    # --- Save polygons plot --- #
    plot_image_filename = polygons_image_plot_filename_format.format(
        output_name)
    plot_image_filepath = os.path.join(test_output_dir, plot_image_filename)
    visualization.save_plot_image_polygons(plot_image_filepath, ori_image,
                                           ori_gt_polygons, ori_disp_polygons,
                                           aligned_disp_polygons)
    # visualization.save_plot_image_polygons(plot_image_filepath, ori_image, [], ori_disp_polygons,
    #                                        aligned_disp_polygons)

    # --- Save polygons as shapefiles --- #
    if output_shapefiles:
        print("# --- Save polygons as shapefiles --- #")
        output_shapefile_filename = shapefile_filename_format.format(
            output_name, "ori")
        output_shapefile_filepath = os.path.join(test_output_dir,
                                                 output_shapefile_filename)
        geo_utils.save_shapefile_from_polygons(ori_gt_polygons,
                                               ori_metadata["filepath"],
                                               output_shapefile_filepath,
                                               properties_list=properties_list)
        output_shapefile_filename = shapefile_filename_format.format(
            output_name, "misaligned")
        output_shapefile_filepath = os.path.join(test_output_dir,
                                                 output_shapefile_filename)
        geo_utils.save_shapefile_from_polygons(ori_disp_polygons,
                                               ori_metadata["filepath"],
                                               output_shapefile_filepath,
                                               properties_list=properties_list)
        output_shapefile_filename = shapefile_filename_format.format(
            output_name, "aligned")
        output_shapefile_filepath = os.path.join(test_output_dir,
                                                 output_shapefile_filename)
        geo_utils.save_shapefile_from_polygons(aligned_disp_polygons,
                                               ori_metadata["filepath"],
                                               output_shapefile_filepath,
                                               properties_list=properties_list)

    # --- Measure accuracies --- #
    if len(ori_gt_polygons) == len(aligned_disp_polygons):
        print("# --- Measure accuracies --- #")
        accuracies_filename = accuracies_filename_format.format(output_name)
        accuracies_filepath = os.path.join(test_output_dir,
                                           accuracies_filename)
        accuracies = measure_accuracies(ori_gt_polygons, aligned_disp_polygons,
                                        thresholds, accuracies_filepath)
        print(accuracies)