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: 0.8421052631578947}, 'idp': {0: 0.8888888888888888}, | |
| 'idr': {0: 0.8}, 'recall': {0: 0.8}, 'precision': {0: 0.8888888888888888}, | |
| 'num_unique_objects': {0: 3}, 'mostly_tracked': {0: 2}, | |
| 'partially_tracked': {0: 1}, 'mostly_lost': {0: 0}, | |
| 'num_false_positives': {0: 1}, 'num_misses': {0: 2}, | |
| 'num_switches': {0: 0}, 'num_fragmentations': {0: 0}, | |
| 'mota': {0: 0.7}, 'motp': {0: 0.02981870229007634}, | |
| 'num_transfer': {0: 0}, 'num_ascend': {0: 0}, | |
| 'num_migrate': {0: 0}} | |
| }, | |
| ] |