Update README.md

Author: chilo-ms

quantization/image_classification/trt/resnet50/README.md

@@ -1,6 +1,52 @@
 # ONNX PTQ for using TensorRT EP
 Following is the end-to-end example using ORT quantization tool to quantize ONNX model and run/evaluate the quantized model with TRT EP.  
 
-## Note
+## Environment setup
+### dataset
 We suggest to use ImageNet 2012 classification dataset to do the model calibration and evaluation. In addition to the sample code we provide below, TensorRT model optimizer which leverages torchvision.datasets already provides
 the ability to work with ImageNet dataset.
+
+#### Prepare ImageNet dataset
+You can either download from [Kaggle](https://www.kaggle.com/c/imagenet-object-localization-challenge/data) or origianl image-net website: val [tarball](https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_val.tar) and devkit [tarball](https://image-net.org/data/ILSVRC/2012/ILSVRC2012_devkit_t12.tar.gz)
+```shell
+mkdir ILSVRC2012
+cd ILSVRC2012
+wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_val.tar --no-check-certificate
+wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_devkit_t12.tar.gz --no-check-certificate
+```
+Untar the tarballs to `val` and `ILSVRC2012_devkit_t12` folder separately.
+
+The dataset layout should look like this:
+
+```
+|-- ILSVRC2012_devkit_t12
+|   |-- COPYING
+|   |-- data
+|   |   |-- ILSVRC2012_validation_ground_truth.txt
+|   |   `-- meta.mat
+|   |-- evaluation
+|   |   |-- VOCreadrecxml.m
+|   |   |-- VOCreadxml.m
+|   |   |-- VOCxml2struct.m
+|   |   |-- compute_overlap.m
+|   |   |-- demo.val.pred.det.txt
+|   |   |-- demo.val.pred.txt
+|   |   |-- demo_eval.m
+|   |   |-- eval_flat.m
+|   |   |-- eval_localization_flat.m
+|   |   |-- get_class2node.m
+|   |   `-- make_hash.m
+|   `-- readme.txt
+|-- meta.bin
+`-- val
+    |-- n01440764
+    |   |-- ILSVRC2012_val_00000293.JPEG
+    |   |-- ILSVRC2012_val_00002138.JPEG
+    |   |-- ILSVRC2012_val_00003014.JPEG
+...
+```
+Note: If the data in `val` folder is not grouped by class, please run following command to reconstruct the layout
+```shell
+cd val/
+wget -qO- https://raw.githubusercontent.com/soumith/imagenetloader.torch/master/valprep.sh | bash
+```