| |
| import os |
|
|
| import fiona |
| import numpy as np |
| import shapely.geometry |
| import argparse |
| from multiprocess import Pool |
| from functools import partial |
| from tqdm import tqdm |
|
|
| try: |
| __import__("frame_field_learning.local_utils") |
| except ImportError: |
| print("ERROR: The frame_field_learning package is not installed! " |
| "Execute script setup.sh to install local dependencies such as frame_field_learning in develop mode.") |
| exit() |
|
|
| from lydorn_utils import polygon_utils, python_utils, print_utils, geo_utils |
|
|
|
|
| def get_args(): |
| argparser = argparse.ArgumentParser(description=__doc__) |
| argparser.add_argument( |
| '--im_filepath', |
| required=True, |
| type=str, |
| nargs='*', |
| help='Path(s) to tiff images (to get projection info).') |
| argparser.add_argument( |
| '--gt_filepath', |
| required=True, |
| type=str, |
| nargs='*', |
| help='Path(s) to ground truth.') |
| argparser.add_argument( |
| '--pred_filepath', |
| required=True, |
| type=str, |
| nargs='*', |
| help='Path(s) to predictions.') |
| argparser.add_argument( |
| '--overwrite', |
| action='store_true', |
| help='The default behavior is to not re-compute a metric if it already has been computed. ' |
| 'Add the --overwrite flag if you want to overwrite existing metric results.') |
|
|
| args = argparser.parse_args() |
| return args |
|
|
|
|
| def load_geom(geom_filepath, im_filepath): |
| ext = os.path.splitext(geom_filepath)[-1] |
| if ext == ".geojson": |
| file = fiona.open(geom_filepath) |
| assert len(file) == 1, "There should be only one feature per file" |
| feat = file[0] |
| geoms = shapely.geometry.shape(feat["geometry"]) |
| elif ext == ".shp": |
| polygons, _ = geo_utils.get_polygons_from_shapefile(im_filepath, geom_filepath, progressbar=False) |
| geoms = shapely.geometry.collection.GeometryCollection([shapely.geometry.Polygon(polygon[:, ::-1]) for polygon in polygons]) |
| else: |
| raise ValueError(f"Geometry can not be loaded from a {ext} file.") |
| return geoms |
|
|
|
|
| def extract_name(filepath): |
| basename = os.path.basename(filepath) |
| name = basename.split(".")[0] |
| return name |
|
|
|
|
| def match_im_gt_pred(im_filepaths, gt_filepaths, pred_filepaths): |
| im_names = list(map(extract_name, im_filepaths)) |
| gt_names = list(map(extract_name, gt_filepaths)) |
|
|
| im_gt_pred_filepaths = [] |
| for pred_filepath in pred_filepaths: |
| name = extract_name(pred_filepath) |
| im_index = im_names.index(name) |
| gt_index = gt_names.index(name) |
| im_gt_pred_filepaths.append((im_filepaths[im_index], gt_filepaths[gt_index], pred_filepath)) |
|
|
| return im_gt_pred_filepaths |
|
|
|
|
| def eval_one(im_gt_pred_filepath, overwrite=False): |
| im_filepath, gt_filepath, pred_filepath = im_gt_pred_filepath |
| metrics_filepath = os.path.splitext(pred_filepath)[0] + ".metrics.json" |
| iou_filepath = os.path.splitext(pred_filepath)[0] + ".iou.json" |
|
|
| metrics = False |
| iou = False |
| if not overwrite: |
| |
| metrics = python_utils.load_json(metrics_filepath) |
| iou = python_utils.load_json(iou_filepath) |
|
|
| if not metrics or not iou: |
| |
| gt_polygons = load_geom(gt_filepath, im_filepath) |
| fixed_gt_polygons = polygon_utils.fix_polygons(gt_polygons, |
| buffer=0.0001) |
| pred_polygons = load_geom(pred_filepath, im_filepath) |
| fixed_pred_polygons = polygon_utils.fix_polygons(pred_polygons) |
|
|
| if not metrics: |
| |
| max_angle_diffs = polygon_utils.compute_polygon_contour_measures(fixed_pred_polygons, fixed_gt_polygons, |
| sampling_spacing=1.0, min_precision=0.5, |
| max_stretch=2, progressbar=True) |
| max_angle_diffs = [value for value in max_angle_diffs if value is not None] |
| max_angle_diffs = np.array(max_angle_diffs) |
| max_angle_diffs = max_angle_diffs * 180 / np.pi |
| metrics = { |
| "max_angle_diffs": list(max_angle_diffs) |
| } |
| python_utils.save_json(metrics_filepath, metrics) |
|
|
| if not iou: |
| fixed_gt_polygon_collection = shapely.geometry.collection.GeometryCollection(fixed_gt_polygons) |
| fixed_pred_polygon_collection = shapely.geometry.collection.GeometryCollection(fixed_pred_polygons) |
| intersection = fixed_gt_polygon_collection.intersection(fixed_pred_polygon_collection).area |
| union = fixed_gt_polygon_collection.union(fixed_pred_polygon_collection).area |
| iou = { |
| "intersection": intersection, |
| "union": union |
| } |
| python_utils.save_json(iou_filepath, iou) |
|
|
| return { |
| "metrics": metrics, |
| "iou": iou, |
| } |
|
|
|
|
| def main(): |
| args = get_args() |
| print_utils.print_info(f"INFO: evaluating {len(args.pred_filepath)} predictions.") |
|
|
| |
| im_gt_pred_filepaths = match_im_gt_pred(args.im_filepath, args.gt_filepath, args.pred_filepath) |
|
|
| pool = Pool() |
| metrics_iou_list = list(tqdm(pool.imap(partial(eval_one, overwrite=args.overwrite), im_gt_pred_filepaths), desc="Compute eval metrics", total=len(im_gt_pred_filepaths))) |
|
|
| |
| aggr_metrics = { |
| "max_angle_diffs": [] |
| } |
| aggr_iou = { |
| "intersection": 0, |
| "union": 0 |
| } |
| for metrics_iou in metrics_iou_list: |
| if metrics_iou["metrics"]: |
| aggr_metrics["max_angle_diffs"] += metrics_iou["metrics"]["max_angle_diffs"] |
| if metrics_iou["iou"]: |
| aggr_iou["intersection"] += metrics_iou["iou"]["intersection"] |
| aggr_iou["union"] += metrics_iou["iou"]["union"] |
| aggr_iou["iou"] = aggr_iou["intersection"] / aggr_iou["union"] |
|
|
| aggr_metrics_filepath = os.path.join(os.path.dirname(args.pred_filepath[0]), "aggr_metrics.json") |
| aggr_iou_filepath = os.path.join(os.path.dirname(args.pred_filepath[0]), "aggr_iou.json") |
| python_utils.save_json(aggr_metrics_filepath, aggr_metrics) |
| python_utils.save_json(aggr_iou_filepath, aggr_iou) |
|
|
|
|
| if __name__ == '__main__': |
| main() |
|
|
