Spaces:
Sleeping
Sleeping
| import numpy as np | |
| test_cases = [ | |
| { | |
| "predictions": [np.array(a) for a in [ | |
| [1,1,10,20,30,40,0.85], | |
| [1,2,50,60,70,80,0.92], | |
| [1,3,80,90,100,110,0.75], | |
| [2,1,15,25,35,45,0.78], | |
| [2,2,55,65,75,85,0.95], | |
| [3,1,20,30,40,50,0.88], | |
| [3,2,60,70,80,90,0.82], | |
| [4,1,25,35,45,55,0.91], | |
| [4,2,65,75,85,95,0.89] | |
| ]], | |
| "references": [np.array(a) for a in [ | |
| [1, 1, 10, 20, 30, 40], | |
| [1, 2, 50, 60, 70, 80], | |
| [1, 3, 85, 95, 105, 115], | |
| [2, 1, 15, 25, 35, 45], | |
| [2, 2, 55, 65, 75, 85], | |
| [3, 1, 20, 30, 40, 50], | |
| [3, 2, 60, 70, 80, 90], | |
| [4, 1, 25, 35, 45, 55], | |
| [5, 1, 30, 40, 50, 60], | |
| [5, 2, 70, 80, 90, 100] | |
| ]], | |
| "result": {'idf1': 0.8421052631578947, 'idp': 0.8888888888888888, | |
| 'idr': 0.8, 'recall': 0.8, 'precision': 0.8888888888888888, | |
| 'num_unique_objects': 3,'mostly_tracked': 2, | |
| 'partially_tracked': 1, 'mostly_lost': 0, | |
| 'num_false_positives': 1, 'num_misses': 2, | |
| 'num_switches': 0, 'num_fragmentations': 0, | |
| 'mota': 0.7, 'motp': 0.02981870229007634, | |
| 'num_transfer': 0, 'num_ascend': 0, | |
| 'num_migrate': 0} | |
| }, | |
| ] |