metric update (#1103)

README.md

@@ -306,10 +306,10 @@ to find instruction and links to exact configuration files and final checkpoints
 |MobileNet V2|INT8 (per-tensor for weights)|ImageNet|71.66 (0.19)|
 |MobileNet V2|Sparsity 50% (RB)|ImageNet|71.34 (0.51)|
 |MobileNet V2|INT8 (per-tensor for weights) + Sparsity 52% (RB)|ImageNet|71.0 (0.85)|
-|MobileNet V3 small|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) |ImageNet|67.7 (0.68)|
-|MobileNet V3 small|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) + Sparsity 42% (RB)|ImageNet|67.7 (0.68)|
-|MobileNet V3 large|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) |ImageNet|75.0 (0.81)|
-|MobileNet V3 large|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) + Sparsity 42% (RB)|ImageNet|75.15 (0.66)|
+|MobileNet V3 small|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) |ImageNet|67.75 (0.63)|
+|MobileNet V3 small|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) + Sparsity 42% (RB)|ImageNet|67.55 (0.83)|
+|MobileNet V3 large|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) |ImageNet|75.02 (0.79)|
+|MobileNet V3 large|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations) + Sparsity 42% (RB)|ImageNet|75.28 (0.53)|
 |ResNet50|INT8 (per-tensor for weights)|ImageNet|75.0 (0.04)|
 |ResNet50|Sparsity 80% (RB)|ImageNet|74.36 (0.68)|
 |ResNet50|INT8 (per-tensor for weightsy) + Sparsity 65% (RB)|ImageNet|74.3 (0.74)|
@@ -322,10 +322,10 @@ to find instruction and links to exact configuration files and final checkpoints
 
 |TensorFlow Model|Compression algorithm|Dataset|mAP (drop) %|
 | :---: | :---: | :---: | :---: |
-|RetinaNet|INT8 (per-tensor for weights)|COCO2017|33.22 (0.22)|
+|RetinaNet|INT8 (per-tensor for weights)|COCO2017|33.18 (0.26)|
 |RetinaNet|Sparsity 50% (Magnitude)|COCO2017|33.13 (0.31)|
 |RetinaNet|Filter Pruning 40%, geometric_median criterion|COCO2017|32.7 (0.74)|
-|RetinaNet|Filter Pruning 40%, geometric_median criterion + INT8 (per-tensor for weights)|COCO2017|32.53 (0.91)|
+|RetinaNet|Filter Pruning 40%, geometric_median criterion + INT8 (per-tensor for weights)|COCO2017|32.68 (0.76)|
 |YOLOv4|INT8 (per-channel, symmetric for weights; per-tensor, asymmetric for activations)|COCO2017|46.30 (0.74)|
 |YOLOv4|Sparsity 50% (Magnitude)|COCO2017|46.54 (0.50)|
 
@@ -334,7 +334,7 @@ to find instruction and links to exact configuration files and final checkpoints
 
 |TensorFlow Model|<img width="110" height="1">Compression algorithm<img width="110" height="1">|Dataset|mAP (drop) %|
 | :---: | :---: | :---: | :---: |
-|MaskRCNN|INT8 (per-tensor for weights)|COCO2017|bbox: 37.14 (0.19)<br/>segm: 33.53 (0.03)|
+|MaskRCNN|INT8 (per-tensor for weights)|COCO2017|bbox: 37.27 (0.06)<br/>segm: 33.54 (0.02)|
 |MaskRCNN|Sparsity 50% (Magnitude)|COCO2017|bbox: 36.93 (0.40)<br/>segm: 33.23 (0.33)|
 
 ## Citing