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Commit 5b85bdb4 authored by A. Unique TensorFlower's avatar A. Unique TensorFlower
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official/projects/edgetpu/vision/README.md
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<figcaption>Performance of AutosegEdgeTPU and MobilenetEdgeTPUV2+DeeplabV3+ models on the 32-class ADE20K semantic segmentation task.</figcaption>
</figure>
| Backbone | Segmentation | #Parameters | ADE20K | Pixel 6 Edge |
: : Head : (million) : 32-class : TPU latency :
: : : : mIOU : (ms) :
| --------------------- | ------------ | ----------- | -------- | ------------ |
| MobileNet V2 | DeeplabV3+ | 2.34 | 54.06% | 7.5 |
: (baseline) : : : : :
| MobilenetEdgeTPUV2-XS | DeeplabV3+ | 3.6 | 56.02% | 5.2 |
| MobilenetEdgeTPUV2-S | DeeplabV3+ | 5.2 | 59.43% | 5.9 |
| MobilenetEdgeTPUV2-M | DeeplabV3+ | 7.7 | 59.81% | 7.2 |
| AutosegEdgeTPU-XS | BiFPN | 2.9 | 59.64% | 5.4 |
| AutosegEdgeTPU-S | BiFPN | 3.1 | 61.31% | 5.7 |
| Backbone | Segmentation Head| #Parameters (million)| ADE20K 32-class mIOU| Pixel 6 EdgeTPU latency (ms)|
|------------------------|------------------|----------------------|---------------------|-----------------------------|
| MobileNet V2 (baseline)| DeeplabV3+ | 2.34 | 54.06% | 7.5 |
| MobilenetEdgeTPUV2-XS | DeeplabV3+ | 3.6 | 56.02% | 5.2 |
| MobilenetEdgeTPUV2-S | DeeplabV3+ | 5.2 | 59.43% | 5.9 |
| MobilenetEdgeTPUV2-M | DeeplabV3+ | 7.7 | 59.81% | 7.2 |
| AutosegEdgeTPU-XS | BiFPN | 2.9 | 59.64% | 5.4 |
| AutosegEdgeTPU-S | BiFPN | 3.1 | 61.31% | 5.7 |
By fusing argmax with resize operator as shown above, it is possible to further
improve the on-device latency of the segmentation models without significantly
impacting the quality:
| Backbone | Segmentation | #Parameters | ADE20K | Pixel 6 Edge |
: : Head : (million) : 32-class : TPU latency :
: : : : mIOU : (ms) :
| --------------------- | ------------ | ----------- | -------- | ------------ |
| MobilenetEdgeTPUV2-XS | DeeplabV3+ | 3.6 | 56% | 3.4 |
| MobilenetEdgeTPUV2-S | DeeplabV3+ | 5.2 | 59.41% | 4.2 |
| MobilenetEdgeTPUV2-M | DeeplabV3+ | 7.7 | 59.79% | 5.5 |
| AutosegEdgeTPU-XS | BiFPN | 2.9 | 59.62% | 3.6 |
| AutosegEdgeTPU-S | BiFPN | 3.1 | 61.28% | 3.9 |
| Backbone | Segmentation Head| #Parameters (million)| ADE20K 32-class mIOU| Pixel 6 EdgeTPU latency (ms)|
|----------------------|------------------|----------------------|---------------------|-----------------------------|
| MobilenetEdgeTPUV2-XS| DeeplabV3+ | 3.6 | 56% | 3.4 |
| MobilenetEdgeTPUV2-S | DeeplabV3+ | 5.2 | 59.41% | 4.2 |
| MobilenetEdgeTPUV2-M | DeeplabV3+ | 7.7 | 59.79% | 5.5 |
| AutosegEdgeTPU-XS | BiFPN | 2.9 | 59.62% | 3.6 |
| AutosegEdgeTPU-S | BiFPN | 3.1 | 61.28% | 3.9 |
### Training the models
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