FYP-eVision / keras-retinanet-library / validation_results_resnet50_800p_29+.txt
validation_results_resnet50_800p_29+.txt
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1324 instances of class vehicle with average precision: 0.7290
mAP using the weighted average of precisions among classes: 0.7290
mAP: 0.7290
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1324 instances of class vehicle with average precision: 0.7248
mAP using the weighted average of precisions among classes: 0.7248
mAP: 0.7248
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1324 instances of class vehicle with average precision: 0.7153
mAP using the weighted average of precisions among classes: 0.7153
mAP: 0.7153
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1324 instances of class vehicle with average precision: 0.7352
mAP using the weighted average of precisions among classes: 0.7352
mAP: 0.7352
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1324 instances of class vehicle with average precision: 0.7360
mAP using the weighted average of precisions among classes: 0.7360
mAP: 0.7360
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1324 instances of class vehicle with average precision: 0.7378
mAP using the weighted average of precisions among classes: 0.7378
mAP: 0.7378
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1324 instances of class vehicle with average precision: 0.7360
mAP using the weighted average of precisions among classes: 0.7360
mAP: 0.7360
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1324 instances of class vehicle with average precision: 0.7390
mAP using the weighted average of precisions among classes: 0.7390
mAP: 0.7390
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1324 instances of class vehicle with average precision: 0.7383
mAP using the weighted average of precisions among classes: 0.7383
mAP: 0.7383
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1324 instances of class vehicle with average precision: 0.7382
mAP using the weighted average of precisions among classes: 0.7382
mAP: 0.7382
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1324 instances of class vehicle with average precision: 0.7398
mAP using the weighted average of precisions among classes: 0.7398
mAP: 0.7398
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1324 instances of class vehicle with average precision: 0.7398
mAP using the weighted average of precisions among classes: 0.7398
mAP: 0.7398
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1324 instances of class vehicle with average precision: 0.7389
mAP using the weighted average of precisions among classes: 0.7389
mAP: 0.7389
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1324 instances of class vehicle with average precision: 0.7397
mAP using the weighted average of precisions among classes: 0.7397
mAP: 0.7397
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1324 instances of class vehicle with average precision: 0.7405
mAP using the weighted average of precisions among classes: 0.7405
mAP: 0.7405
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1324 instances of class vehicle with average precision: 0.7411
mAP using the weighted average of precisions among classes: 0.7411
mAP: 0.7411
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1324 instances of class vehicle with average precision: 0.7405
mAP using the weighted average of precisions among classes: 0.7405
mAP: 0.7405
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1324 instances of class vehicle with average precision: 0.7404
mAP using the weighted average of precisions among classes: 0.7404
mAP: 0.7404
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1324 instances of class vehicle with average precision: 0.7424
mAP using the weighted average of precisions among classes: 0.7424
mAP: 0.7424
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1324 instances of class vehicle with average precision: 0.7417
mAP using the weighted average of precisions among classes: 0.7417
mAP: 0.7417
resnet50_csv_01.h5
resnet50_csv_02.h5
resnet50_csv_03.h5
resnet50_csv_04.h5
resnet50_csv_05.h5
resnet50_csv_06.h5
resnet50_csv_07.h5
resnet50_csv_08.h5
resnet50_csv_09.h5
resnet50_csv_10.h5
resnet50_csv_11.h5
resnet50_csv_12.h5
resnet50_csv_13.h5
resnet50_csv_14.h5
resnet50_csv_15.h5
resnet50_csv_16.h5
resnet50_csv_17.h5
resnet50_csv_18.h5
resnet50_csv_19.h5
resnet50_csv_20.h5
Validations completed