Internal change

PiperOrigin-RevId: 433049448

official/projects/qat/vision/README.md

@@ -28,7 +28,7 @@ $ python3 train.py \
 --mode=train_and_eval
 ```
 
-## Model Accuracy
+## Image Classification
 
 <figure align="center">
 <img width=70% src=https://storage.googleapis.com/tf_model_garden/models/qat/images/readme-qat-classification-plot.png>
@@ -46,3 +46,18 @@ Note: The Top-1 model accuracy is measured on the validation set of [ImageNet](h
 |ResNet50              |224x224   |76.710%              |76.420%                  |77.200%                  |[config](https://github.com/tensorflow/models/blob/master/official/projects/qat/vision/configs/experiments/image_classification/imagenet_resnet50_qat_gpu.yaml)     |[TFLite(Int8/QAT)](https://storage.googleapis.com/tf_model_garden/vision/resnet50_imagenet/resnet_50_224_int8.tflite)                                |
 |MobileNetV3.5 MultiAVG|224x224   |75.212%              |74.122%                  |75.130%                  |[config](https://github.com/tensorflow/models/blob/master/official/projects/qat/vision/configs/experiments/image_classification/imagenet_mobilenetv3.5_qat_gpu.yaml)|[TFLite(Int8/QAT)](https://storage.googleapis.com/tf_model_garden/vision/mobilenet/v3.5multiavg_1.0_int8/mobilenet_v3.5multiavg_1.00_224_int8.tflite)|
 
+## Semantic Segmentation
+
+
+Model is pretrained using COCO train set. Two datasets, Pascal VOC segmentation
+dataset and Cityscapes dataset (only for DeepLab v3+), are used to train and
+evaluate models. Model accuracy is measured on full Pascal VOC segmentation
+validation set.
+
+### Pre-trained Models
+
+model                      | resolution | mIoU  | mIoU (FP32) | mIoU (FP16) | mIoU (INT8) | mIoU (QAT INT8) | download (tflite)
+:------------------------- | :--------: | ----: | ----------: | ----------: | ----------: | --------------: | ------------------------------------------------------: | ------------------------------------------------------: | -------------------------------------------------------: | ------------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | ----------------:
+MobileNet v2 + DeepLab v3  | 512x512    | 75.27 | 75.30       | 75.32       | 73.95       | 74.68             | [FP32](https://storage.googleapis.com/tf_model_garden/vision/qat/deeplabv3_mobilenetv2_pascal_coco_0.21/model_none.tflite) \| [FP16](https://storage.googleapis.com/tf_model_garden/vision/qat/deeplabv3_mobilenetv2_pascal_coco_0.21/model_fp16.tflite) \| [INT8](https://storage.googleapis.com/tf_model_garden/vision/qat/deeplabv3_mobilenetv2_pascal_coco_0.21model_int8_full.tflite) \| [QAT INT8](https://storage.googleapis.com/tf_model_garden/vision/qat/deeplabv3_mobilenetv2_pascal_coco_0.21/Fmodel_default.tflite)
+MobileNet v2 + DeepLab v3+ | 1024x2048  | 73.82 | 73.84       | 73.65       | 72.33       | 73.49                                                                  | [FP32](https://storage.googleapis.com/tf_model_garden/vision/qat/mnv2_deeplabv3plus_cityscapes/model_none.tflite) \| [FP16](https://storage.googleapis.com/tf_model_garden/vision/qat/mnv2_deeplabv3plus_cityscapes/Fmodel_fp16.tflite) \| [INT8](https://storage.googleapis.com/tf_model_garden/vision/qat/mnv2_deeplabv3plus_cityscapes/model_int8_full.tflite) \| [QAT INT8](https://storage.googleapis.com/tf_model_garden/vision/qat/mnv2_deeplabv3plus_cityscapes/Fmodel_default.tflite)
+