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faster_rcnn_execution.ipynb

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class,detection_count
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person,1512
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chair,133
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bicycle,99
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car,77
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bottle,65
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pottedplant,52
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horse,47
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tvmonitor,44
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motorbike,36
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sofa,30
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diningtable,23
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boat,9
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dog,7
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bird,5
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bus,4
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aeroplane,2
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train,2
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cat,0
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cow,0
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sheep,0

rcnn_results_csv/faster_rcnn_detections.csv

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model,avg_inference_ms,std_inference_ms,avg_fps,num_batches_tested
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Faster R-CNN (ResNet-50 + FPN),155.3247,21.3388,6.4381,50
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model,num_epochs,final_train_loss,best_train_loss,mAP@0.5,mAP@0.5:0.95,avg_inference_ms,avg_fps,total_detections,avg_confidence,classes_detected,confidence_threshold
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Faster R-CNN (ResNet-50 + FPN),10,0.156,0.156,0.0,0.0,155.3247,6.4381,2147,0.8854,17,0.5
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epoch,train/loss
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1,0.39351986519002413
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2,0.28674892250943435
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3,0.2554258094279916
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4,0.19205157820369814
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5,0.1762298679148609
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6,0.16795804088192803
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7,0.15853910713971078
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8,0.1574449301052552
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9,0.15703138480601195
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10,0.15596147791541123
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