| from collections import defaultdict |
| import difflib |
| import os |
| import argparse |
| import pdb |
| import random |
| import cssutils |
| from tqdm import tqdm |
| from utils import * |
|
|
|
|
| if __name__ == '__main__': |
| parser = argparse.ArgumentParser() |
| parser.add_argument("-f", "--file", type=str) |
| args = parser.parse_args() |
|
|
| ref_file = load_json("dataset/NSR-1K/spatial/spatial.val.json") |
| ref_file = {x['id']: x for x in ref_file} |
|
|
| fname = args.file |
| basename = os.path.basename(fname) |
| dirname = os.path.dirname(fname) |
|
|
| assert "raw" not in basename |
| responses = load_json(fname) |
|
|
| n_correct = defaultdict(lambda: 0) |
| n_miss = defaultdict(lambda: 0) |
| n_type = defaultdict(lambda: 0) |
|
|
| print(f"Evaluating {basename}") |
| for r in tqdm(responses): |
| try: |
| ref_sample = ref_file[int(r['query_id'])] |
| except: |
| ref_sample = ref_file[int(r['id'])] |
| ref_relation = ref_sample['relation'] |
| obj1, _ = ref_sample['obj1'] |
| obj2, _ = ref_sample['obj2'] |
| prompt_type = ref_sample['type'] |
| n_type[prompt_type] += 1 |
| |
| pred_objects = [obj for obj in r['object_list'] if obj[1] != [0]*4 and obj[0] != None] |
| |
| all_objects = [pred_obj[0] for pred_obj in pred_objects] |
| close_obj1 = difflib.get_close_matches(obj1, all_objects)[:1] |
| pred_bbox1 = [obj[1] for i, obj in enumerate(pred_objects) if obj[0] in close_obj1] |
| |
| if len(pred_bbox1) == 0: |
| n_miss[prompt_type] += 1 |
| continue |
| |
| close_obj2 = difflib.get_close_matches(obj2, all_objects)[:1] |
| pred_bbox2 = [obj[1] for i, obj in enumerate(pred_objects) if obj[0] in close_obj2] |
| if len(pred_bbox2) == 0: |
| n_miss[prompt_type] += 1 |
| continue |
| |
| all_relations = [eval_spatial_relation(b1, b2) for b1 in pred_bbox1 for b2 in pred_bbox2] |
|
|
| if ref_relation in all_relations: |
| n_correct[prompt_type] += 1 |
| else: |
| if ref_relation == 'next to' and ('left' in all_relations or 'right' in all_relations): |
| n_correct[prompt_type] += 1 |
| else: |
| pass |
| |
| for prompt_type in n_correct.keys(): |
| print(f'{basename} {prompt_type} (#eg: {n_type[prompt_type]})') |
| acc = n_correct[prompt_type]/n_type[prompt_type] |
| score_info = {'acc': acc, 'n_miss': n_miss[prompt_type]} |
| print(f'\tAcc = {acc*100:.2f} %, #miss = {n_miss[prompt_type]}') |
|
|
| |
| args.output_dir = os.path.join('./eval_score/spatial/') |
| os.makedirs(args.output_dir, exist_ok=True) |
| output_filename = os.path.join(args.output_dir, 'layout_eval.'+basename) |
| with open(output_filename, 'w') as fout: |
| json.dump(score_info, fout) |
|
|
| print("{}, Overall, acc: {:.4f}, missing: {}".format(basename, sum(n_correct.values())/len(responses), sum(n_miss.values()))) |
|
|
