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ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 1

1,241 bytes removed, 09:06, 6 April 2021
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==Dataset==
[[File:FICS-PCB samples.png|bordercenter|thumb|500x500px|center|'''caption''']]
[[File:Samples per class in Microscope and DSLR subsets.png|bordercenter|thumb|500x500px|center|caption]]
[[File:Dataset processing and augmentation.png|bordercenter|thumb|500x500px|center|caption]]
[[File:Image augmentation for training samples.png|bordercenter|thumb|500x500px|center|caption]]
|-align="center"
|
|[[File:Resnet50 train and validation accuracy.png|borderthumb|500x500px|noneTrain and validation accuracy trend over 1000 training epochs for ResNet50 model]]
|
|[[File:Resnet50 train and validation loss.png|borderthumb|500x500px|noneTrain and validation loss trend over 1000 training epochs for ResNet50 model]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Train and validation accuracy trend over 1000 training epochs for ResNet50 model
|width="25"|
|width="100"|Train and validation loss trend over 1000 training epochs for ResNet50 model
|width="25"|
|}
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Host machine, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Resnet50 host confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of ResNet50 model on host machine before quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Host machine, classification report
|- style="font-weight:bold;"
! Class
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Target device, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Resnet50 target confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of ResNet50 model on target device after quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;" |+ Target device, classification report
|- style="font-weight:bold;"
! Class
|-align="center"
|
|[[File:Resnet50 cores utilization.png|borderthumb|500x500px|noneUtilization of CPU and DPU cores of ResNet50 model for 1, 2, and 4 threads]]
|
|[[File:Resnet50 DPU latency.png|borderthumb|500x500px|noneDPU latency of ResNet50 model for 1, 2, and 4 threads]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Utilization of CPU and DPU cores of ResNet50 model for 1, 2, and 4 threads
|width="25"|
|width="100"|DPU latency of ResNet50 model for 1, 2, and 4 threads
|width="25"|
|}
|-align="center"
|
|[[File:Resnet101 train and validation accuracy.png|borderthumb|500x500px|noneTrain and validation accuracy trend over 1000 training epochs for ResNet101 model]]
|
|[[File:Resnet101 train and validation loss.png|borderthumb|500x500px|noneTrain and validation loss trend over 1000 training epochs for ResNet101 model]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Train and validation accuracy trend over 1000 training epochs for ResNet101 model
|width="25"|
|width="100"|Train and validation loss trend over 1000 training epochs for ResNet101 model
|width="25"|
|}
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Host machine, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Resnet101 host confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of ResNet101 model on host machine before quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Host machine, classification report
|- style="font-weight:bold;"
! Class
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Target device, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Resnet101 target confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of ResNet101 model on target device after quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Target device, classification report
|- style="font-weight:bold;"
! Class
|-align="center"
|
|[[File:Resnet101 cores utilization.png|borderthumb|500x500px|noneUtilization of CPU and DPU cores of ResNet101 model for 1, 2, and 4 threads]]
|
|[[File:Resnet101 DPU latency.png|borderthumb|500x500px|noneDPU latency of ResNet101 model for 1, 2, and 4 threads]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Utilization of CPU and DPU cores of ResNet101 model for 1, 2, and 4 threads
|width="25"|
|width="100"|DPU latency of ResNet101 model for 1, 2, and 4 threads
|width="25"|
|}
|-align="center"
|
|[[File:Resnet152 train and validation accuracy.png|borderthumb|500x500px|noneTrain and validation accuracy trend over 1000 training epochs for ResNet152 model]]
|
|[[File:Resnet152 train and validation loss.png|borderthumb|500x500px|noneTrain and validation loss trend over 1000 training epochs for ResNet152 model]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Train and validation accuracy trend over 1000 training epochs for ResNet152 model
|width="25"|
|width="100"|Train and validation loss trend over 1000 training epochs for ResNet152 model
|width="25"|
|}
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Host machine, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Resnet152 host confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of ResNet152 model on host machine before quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Host machine, classification report
|- style="font-weight:bold;"
! Class
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Target device, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Resnet152 target confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of ResNet152 model on target device after quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Target device, classification report
|- style="font-weight:bold;"
! Class
|-align="center"
|
|[[File:Resnet152 cores utilization.png|borderthumb|500x500px|noneUtilization of CPU and DPU cores of ResNet152 model for 1, 2, and 4 threads]]
|
|[[File:Resnet152 DPU latency.png|borderthumb|500x500px|noneDPU latency of ResNet152 model for 1, 2, and 4 threads]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Utilization of CPU and DPU cores of ResNet152 model for 1, 2, and 4 threads
|width="25"|
|width="100"|DPU latency of ResNet152 model for 1, 2, and 4 threads
|width="25"|
|}
|-align="center"
|
|[[File:InceptionV4 train and validation accuracy.png|borderthumb|500x500px|noneTrain and validation accuracy trend over 1000 training epochs for InceptionV4 model]]
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|[[File:InceptionV4 train and validation loss.png|borderthumb|500x500px|noneTrain and validation loss trend over 1000 training epochs for InceptionV4 model]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Train and validation accuracy trend over 1000 training epochs for InceptionV4 model
|width="25"|
|width="100"|Train and validation loss trend over 1000 training epochs for InceptionV4 model
|width="25"|
|}
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Host machine, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:InceptionV4 host confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of InceptionV4 model on host machine before quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Host machine, classification report
|- style="font-weight:bold;"
! Class
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Target device, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:InceptionV4 target confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of InceptionV4 model on target device after quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Target device, classification report
|- style="font-weight:bold;"
! Class
|-align="center"
|
|[[File:Inception v4 cores utilization.png|borderthumb|500x500px|noneUtilization of CPU and DPU cores of InceptionV4 model for 1, 2, and 4 threads]]
|
|[[File:Inception v4 DPU latency.png|borderthumb|500x500px|noneDPU latency of InceptionV4 model for 1, 2, and 4 threads]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Utilization of CPU and DPU cores of InceptionV4 model for 1, 2, and 4 threads
|width="25"|
|width="100"|DPU latency of InceptionV4 model for 1, 2, and 4 threads
|width="25"|
|}
|-align="center"
|
|[[File:Inception ResNet V1 train and validation accuracy.png|borderthumb|500x500px|noneTrain and validation accuracy trend over 1000 training epochs for Inception ResNet V1 model]]
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|[[File:Inception ResNet V1 train and validation loss.png|borderthumb|500x500px|noneTrain and validation loss trend over 1000 training epochs for Inception ResNet V1 model]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Train and validation accuracy trend over 1000 training epochs for Inception ResNet V1 model
|width="25"|
|width="100"|Train and validation loss trend over 1000 training epochs for Inception ResNet V1 model
|width="25"|
|}
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Host machine, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Inception ResNet V1 host confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of Inception ResNet V1 model on host machine before quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Host machine, classification report
|- style="font-weight:bold;"
! Class
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Target device, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Inception ResNet V1 target confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of Inception ResNet V1 model on target device after quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Target device, classification report
|- style="font-weight:bold;"
! Class
|-align="center"
|
|[[File:Inception resnet v1 cores utilization.png|borderthumb|500x500px|noneUtilization of CPU and DPU cores of Inception ResNet V1 model for 1, 2, and 4 threads]]
|
|[[File:Inception resnet v1 DPU latency.png|borderthumb|500x500px|noneDPU latency of Inception ResNet V1 model for 1, 2, and 4 threads]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Utilization of CPU and DPU cores of Inception ResNet V1 model for 1, 2, and 4 threads
|width="25"|
|width="100"|DPU latency of Inception ResNet V1 model for 1, 2, and 4 threads
|width="25"|
|}
|-align="center"
|
|[[File:Inception ResNet V2 train and validation accuracy.png|borderthumb|500x500px|noneTrain and validation accuracy trend over 1000 training epochs for Inception ResNet V2 model]]
|
|[[File:Inception ResNet V2 train and validation loss.png|borderthumb|500x500px|noneTrain and validation loss trend over 1000 training epochs for Inception ResNet V2 model]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Train and validation accuracy trend over 1000 training epochs for Inception ResNet V2 model
|width="25"|
|width="100"|Train and validation loss trend over 1000 training epochs for Inception ResNet V2 model
|width="25"|
|}
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Host machine, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Inception ResNet V2 host confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of Inception ResNet V2 model on host machine before quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Host machine, classification report
|- style="font-weight:bold;"
! Class
{| align="center" style = "background: transparent; margin: auto; width: 60%;"
|+ style="padding: 10px" | '''Target device, confusion matrix & classification report'''
|-
| width=200px style = " vertical-align: center; " |[[File:Inception ResNet V2 target confusion matrix.png|center|borderthumb|500x500px|Confusion matrix of Inception ResNet V2 model on target device after quantization]]
| width=200px style = " vertical-align: center; " |
{| class="wikitable" style="margin: auto; text-align: center;"
|+ Target device, classification report
|- style="font-weight:bold;"
! Class
|-align="center"
|
|[[File:Inception resnet v2 cores utilization.png|borderthumb|500x500px|noneUtilization of CPU and DPU cores of Inception ResNet V2 model for 1, 2, and 4 threads]]
|
|[[File:Inception resnet v2 DPU latency.png|borderthumb|500x500px|noneDPU latency of Inception ResNet V2 model for 1, 2, and 4 threads]]
|
|-align="center" valign="top"
|width="25"|
|width="100"|Utilization of CPU and DPU cores of Inception ResNet V2 model for 1, 2, and 4 threads
|width="25"|
|width="100"|DPU latency of Inception ResNet V2 model for 1, 2, and 4 threads
|width="25"|
|}
==Comparison==
<!--Start of table definition-->{|style="background:transparent; color:black" border="0" height="550" align="center" valign="bottom" cellpadding=10px cellspacing=0px|-align="center"||[[File:Inception resnet v2 cores utilization.png|thumb|250x250px|Utilization of CPU and DPU cores of Inception ResNet V2 model for 1, 2, and 4 threads]]||[[File:Inception resnet v2 DPU latency.png|thumb|250x250px|DPU latency of Inception ResNet V2 model for 1, 2, and 4 threads]]||}
==Useful links==
U0019
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edits
Retrieved from "https://wiki.dave.eu/index.php/Special:MobileDiff/13409"