score_writer = csv.DictWriter(scorefile, fieldnames=fieldnames2)
score_writer.writeheader()
rect_writer = csv.DictWriter(rect_precision_file, fieldnames=fieldnames)
rect_writer.writeheader()
# Read Ground Truth.
map_gt_list = [];
for m in range(1, 11):
map_name = ['1920-1.png', '1920-2.png', '1920-3.png', '1920-4.png', '1920-5.png',
'1920-6.png', '1920-7.png', '1920-8.png', '1920-9.png', '1920-10.png']
groundTruthFile = './GroundTruths/' + map_name[m - 1].split('.')[0] + '.geojson'
gt_obj = GeoJsonReader.load_json_file(groundTruthFile)
gt_list = GeoJsonReader.get_ground_truth_list(gt_obj, 1, 1)
map_gt_list.append(gt_list)
candidate_file = './narges result/candidates'
cf = open(candidate_file, 'r')
map_feature_list = []
map_result_obj_features = []
map_result_feature_count = []
map_result_rects = []
# Read result files.
count = 0
for i in range(1, MAP_NUM):
result_file_name = './narges result/1920-' + str(i) + '.png_EdditedByPixels.txt'
result_obj = GeoJsonReader.load_json_file(result_file_name)
def evaluate_result(gt_obj, result_obj, group_para=0, scale_w=1, scale_h=1):
gt_list = GeoJsonReader.get_ground_truth_list(gt_obj, scale_w, scale_h)
result_rect_list = GeoJsonReader.get_result_rectangles(result_obj)
return ResultEvaluation.evaluation_simple(result_rect_list, gt_list, area_threshold=0.7, group_para=group_para)
