JonathonLuiten / TrackEval

HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).
MIT License
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a method to modify the result file to csv #129

Open unfollow7 opened 1 year ago

unfollow7 commented 1 year ago

trackeval/metrics/_base_metric.py def summary_results(self, table_res): """Returns a simple summary of final results for a tracker""" res = {} for k in table_res.keys(): res[k] = dict(zip(self.summary_fields, self._summary_row(table_res[k]))) return res

trackeval/utils.py from pandas import DataFrame def write_summary_results(summaries, cls, output_folder): """Write summary results to file""" out_file = os.path.join(output_folder, cls + '_summary.csv') if os.path.exists(out_file): os.remove(out_file) os.makedirs(os.path.dirname(out_file), exist_ok=True) for sums in summaries: x = DataFrame(sums) x = DataFrame(x.values.T, index=x.columns, columns=x.index) with open(out_file, 'a', newline='') as f: x.to_csv(f, mode="a", index=True) f.write("\n")

def write_detailed_results(details, cls, output_folder): """Write detailed results to file""" out_file = os.path.join(output_folder, cls + '_detailed.csv') if os.path.exists(out_file): os.remove(out_file) os.makedirs(os.path.dirname(out_file), exist_ok=True) for detail in details: x = DataFrame(detail) x = DataFrame(x.values.T, index=x.columns, columns=x.index) col_classes = {"ori": []} for col in x.columns.tolist(): if "_" in col: theclass = col.split("", 1)[0] if the_class not in col_classes.keys(): col_classes[the_class] = [col] else: col_classes[the_class].append(col) else: col_classes["ori"].append(col) for v in col_classes.values(): tmp_df = x[v] with open(out_file, 'a', newline='') as f: tmp_df.to_csv(f, mode="a", index=True) f.write("\n")